+
+
+ {% endblock %}
diff --git a/app-engine/templates/one_device.html b/app-engine/templates/one_device.html
new file mode 100644
index 0000000..8e2abc6
--- /dev/null
+++ b/app-engine/templates/one_device.html
@@ -0,0 +1,57 @@
+{% extends 'base.html' %}
+{% block content %}
+
+
+
+
+
+
+
+
+ Device {{device.id}}
+
+
+
+
+
+
+
+
+
+ Prediction
+ {{ device.prediction }}
+
+
+ Probability
+ {{reading.accuracy}}
+
+
+ Device Type:
+ {{device.type}}
+
+
+ Location:
+ {{device.location}}
+
+
Notes
+
{{device.notes}}
+
+
+
+
+
+{% endblock %}
+
+{% block script %}
+
+
+
+{% endblock %}
diff --git a/app-engine/templates/setting.html b/app-engine/templates/setting.html
new file mode 100644
index 0000000..a5b7c9f
--- /dev/null
+++ b/app-engine/templates/setting.html
@@ -0,0 +1,50 @@
+{% extends 'base.html' %}
+{% block content %}
+
+
+
+
+
+
+
+
Application Settings
+
+
+
+
+{% endblock %}
diff --git a/app-engine/templates/setting_device.html b/app-engine/templates/setting_device.html
new file mode 100644
index 0000000..c5dcfea
--- /dev/null
+++ b/app-engine/templates/setting_device.html
@@ -0,0 +1,98 @@
+{% extends 'base.html' %}
+{% block content %}
+
+
+
+
+
+
+
+
Device {{device.id}} Setting
+
+
+
+
+
+{% endblock %}
diff --git a/app-engine/templates/user.html b/app-engine/templates/user.html
new file mode 100644
index 0000000..cff11bb
--- /dev/null
+++ b/app-engine/templates/user.html
@@ -0,0 +1,51 @@
+{% extends 'base.html' %}
+{% block content %}
+
+{% endblock %}
diff --git a/app-engine/test.py b/app-engine/test.py
new file mode 100644
index 0000000..9f16f1f
--- /dev/null
+++ b/app-engine/test.py
@@ -0,0 +1,7 @@
+from datetime import datetime
+
+string = '2018-11-28T16:27:43.627213+00:00'
+# print(string)
+
+date_time_obj = datetime.strptime(string, '%Y-%m-%dT%H:%M:%S.%f%z')
+print( date_time_obj.strftime('We are the %d, %B %Y') )
diff --git a/app-engine/user.py b/app-engine/user.py
new file mode 100644
index 0000000..6f73940
--- /dev/null
+++ b/app-engine/user.py
@@ -0,0 +1,164 @@
+"""
+This is the people module and supports all the REST actions for the
+people data
+"""
+
+from flask import make_response, abort
+from config import db
+from models import User, UserSchema
+
+
+def read_all():
+ """
+ This function responds to a request for /api/user
+ with the complete lists of users
+
+ :return: json string of list of users
+ """
+ # Create the list of people from our data
+ users = User.query.order_by(User.user_name).all()
+
+ # Serialize the data for the response
+ schema = UserSchema(many=True)
+ data = schema.dump(users).data
+ return data
+
+
+def read_one(user_name):
+ """
+ This function responds to a request for /api/user/{user_name}
+ with one matching user from settings
+
+ :param id_user: Id of user to find
+ :return: user matching id
+ """
+ # Get the person requested
+ user = User.query.filter(User.user_name == user_name).one_or_none()
+
+ # Did we find a person?
+ if user is not None:
+
+ # Serialize the data for the response
+ schema = UserSchema()
+ data = schema.dump(user).data
+ return data
+
+ # Otherwise, nope, didn't find that person
+ else:
+ abort(
+ 404,
+ "User not found for Id: {user_name}".format(user_name=user_name),
+ )
+
+
+def create(user):
+ """
+ This function creates a new entry in the default structure
+ based on the passed in user id data
+
+ :param user_name: user name to create in user structure
+ :param display_name: display name for the user
+ :param company: the user company
+ :param thumbnail: string url to the thumbnail image
+
+ :return: 201 on success, 406 on default exists
+ """
+
+
+ user_name = user.get("user_name")
+
+ existing = (
+ User.query.filter(User.user_name == user_name)
+ .one_or_none()
+ )
+
+ # Can we insert this person?
+ if existing is None:
+
+ # Create a person instance using the schema and the passed in person
+ schema = UserSchema()
+ users = schema.load(user, session=db.session).data
+
+ # Add the person to the database
+ db.session.add(users)
+ db.session.commit()
+
+ # Serialize and return the newly created person in the response
+ data = schema.dump(users).data
+
+ return data, 201
+
+ # Otherwise, nope, person exists already
+ else:
+ abort(
+ 409,
+ "User {user_name} exists already".format(
+ user_name=user_name
+ ),
+ )
+
+
+def update(user_name, user):
+ """
+ This function updates an existing user in the structure
+
+ :param user_name: id of the user to update in the default structure
+ :param user: user to update
+ :return: updated default structure
+ """
+ # Get the person requested from the db into session
+ update = User.query.filter(
+ User.user_name == user_name
+ ).one_or_none()
+
+ # Did we find a user?
+ if update is not None:
+
+ # turn the passed in person into a db object
+ schema = UserSchema()
+ updates = schema.load(user, session=db.session).data
+
+ # Set the id to the person we want to update
+ updates.user_name = user_name
+
+ # merge the new object into the old and commit it to the db
+ db.session.merge(updates)
+ db.session.commit()
+
+ # return updated person in the response
+ data = schema.dump(updates).data
+
+ return data, 200
+
+ # Otherwise, nope, didn't find that person
+ else:
+ abort(
+ 404,
+ "User not found for Id: {user_name}".format(user_name=user_name),
+ )
+
+
+def delete(user_name):
+ """
+ This function deletes a user from the default structure
+
+ :param user_name: Id of the user to delete
+ :return: 200 on successful delete, 404 if not found
+ """
+ # Get the person requested
+ user = User.query.filter(User.user_name == user_name).one_or_none()
+
+ # Did we find a person?
+ if user is not None:
+ db.session.delete(user)
+ db.session.commit()
+ return make_response(
+ "User {user_name} deleted".format(user_name=user_name), 200
+ )
+
+ # Otherwise, nope, didn't find that person
+ else:
+ abort(
+ 404,
+ "User not found for Id: {user_name}".format(user_name=user_name),
+ )
diff --git a/assets/DeepGauge.jpg b/assets/DeepGauge.jpg
new file mode 100644
index 0000000..ffc06b9
Binary files /dev/null and b/assets/DeepGauge.jpg differ
diff --git a/assets/DeepGauge.xml b/assets/DeepGauge.xml
new file mode 100644
index 0000000..16f0e39
--- /dev/null
+++ b/assets/DeepGauge.xml
@@ -0,0 +1 @@
+
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
\ No newline at end of file
diff --git a/aws/dashboard/index.html b/aws/dashboard/index.html
new file mode 100644
index 0000000..0c920bf
--- /dev/null
+++ b/aws/dashboard/index.html
@@ -0,0 +1,11 @@
+
+
+
+
+
+
+
+
+
+
+
diff --git a/aws/lambdas/optimizedImageClassification/camera.py b/aws/lambdas/optimizedImageClassification/camera.py
new file mode 100644
index 0000000..3ec8de0
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/camera.py
@@ -0,0 +1,39 @@
+#
+# Copyright 2010-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# This class is a camera that uses picamera to take a photo and DLC compiled
+# Resnet-50 model to perform image classification, identifying the objects
+# shown in the photo.
+#
+
+import StringIO
+import picamera
+import time
+
+class Camera(object):
+ r"""
+ Camera that captures an image for performing inference
+ with DLC compiled model.
+ """
+
+ def capture_image(self):
+ r"""
+ Capture image with PiCamera.
+ """
+ camera = picamera.PiCamera()
+ imageData = StringIO.StringIO()
+
+ try:
+ camera.resolution = (224, 224)
+ print("Taking a photo from your camera...")
+ camera.start_preview()
+ time.sleep(2)
+ camera.capture(imageData, format = "jpeg", resize = (224, 224))
+ camera.stop_preview()
+
+ imageData.seek(0)
+ return imageData
+ finally:
+ camera.close()
+
+ raise RuntimeError("There is problem to use your camera.")
diff --git a/aws/lambdas/optimizedImageClassification/greengrasssdk/IoTDataPlane.py b/aws/lambdas/optimizedImageClassification/greengrasssdk/IoTDataPlane.py
new file mode 100644
index 0000000..055e6ee
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/greengrasssdk/IoTDataPlane.py
@@ -0,0 +1,154 @@
+#
+# Copyright 2010-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+
+import base64
+import json
+import logging
+
+from greengrasssdk import Lambda
+from greengrass_common.env_vars import SHADOW_FUNCTION_ARN, ROUTER_FUNCTION_ARN, MY_FUNCTION_ARN
+
+# Log messages in the SDK are part of customer's log because they're helpful for debugging
+# customer's lambdas. Since we configured the root logger to log to customer's log and set the
+# propagate flag of this logger to True. The log messages submitted from this logger will be
+# sent to the customer's local Cloudwatch handler.
+customer_logger = logging.getLogger(__name__)
+customer_logger.propagate = True
+
+
+class ShadowError(Exception):
+ pass
+
+
+class Client:
+ def __init__(self):
+ self.lambda_client = Lambda.Client()
+
+ def get_thing_shadow(self, **kwargs):
+ r"""
+ Call shadow lambda to obtain current shadow state.
+
+ :Keyword Arguments:
+ * *thingName* (``string``) --
+ [REQUIRED]
+ The name of the thing.
+
+ :returns: (``dict``) --
+ The output from the GetThingShadow operation
+ * *payload* (``bytes``) --
+ The state information, in JSON format.
+ """
+ thing_name = self._get_required_parameter('thingName', **kwargs)
+ payload = b''
+
+ return self._shadow_op('get', thing_name, payload)
+
+ def update_thing_shadow(self, **kwargs):
+ r"""
+ Updates the thing shadow for the specified thing.
+
+ :Keyword Arguments:
+ * *thingName* (``string``) --
+ [REQUIRED]
+ The name of the thing.
+ * *payload* (``bytes or seekable file-like object``) --
+ [REQUIRED]
+ The state information, in JSON format.
+
+ :returns: (``dict``) --
+ The output from the UpdateThingShadow operation
+ * *payload* (``bytes``) --
+ The state information, in JSON format.
+ """
+ thing_name = self._get_required_parameter('thingName', **kwargs)
+ payload = self._get_required_parameter('payload', **kwargs)
+
+ return self._shadow_op('update', thing_name, payload)
+
+ def delete_thing_shadow(self, **kwargs):
+ r"""
+ Deletes the thing shadow for the specified thing.
+
+ :Keyword Arguments:
+ * *thingName* (``string``) --
+ [REQUIRED]
+ The name of the thing.
+
+ :returns: (``dict``) --
+ The output from the DeleteThingShadow operation
+ * *payload* (``bytes``) --
+ The state information, in JSON format.
+ """
+ thing_name = self._get_required_parameter('thingName', **kwargs)
+ payload = b''
+
+ return self._shadow_op('delete', thing_name, payload)
+
+ def publish(self, **kwargs):
+ r"""
+ Publishes state information.
+
+ :Keyword Arguments:
+ * *topic* (``string``) --
+ [REQUIRED]
+ The name of the MQTT topic.
+ * *payload* (``bytes or seekable file-like object``) --
+ The state information, in JSON format.
+
+ :returns: None
+ """
+
+ topic = self._get_required_parameter('topic', **kwargs)
+
+ # payload is an optional parameter
+ payload = kwargs.get('payload', b'')
+
+ function_arn = ROUTER_FUNCTION_ARN
+ client_context = {
+ 'custom': {
+ 'source': MY_FUNCTION_ARN,
+ 'subject': topic
+ }
+ }
+
+ customer_logger.debug('Publishing message on topic "{}" with Payload "{}"'.format(topic, payload))
+ self.lambda_client._invoke_internal(
+ function_arn,
+ payload,
+ base64.b64encode(json.dumps(client_context).encode()),
+ 'Event'
+ )
+
+ def _get_required_parameter(self, parameter_name, **kwargs):
+ if parameter_name not in kwargs:
+ raise ValueError('Parameter "{parameter_name}" is a required parameter but was not provided.'.format(
+ parameter_name=parameter_name
+ ))
+ return kwargs[parameter_name]
+
+ def _shadow_op(self, op, thing_name, payload):
+ topic = '$aws/things/{thing_name}/shadow/{op}'.format(thing_name=thing_name, op=op)
+ function_arn = SHADOW_FUNCTION_ARN
+ client_context = {
+ 'custom': {
+ 'subject': topic
+ }
+ }
+
+ customer_logger.debug('Calling shadow service on topic "{}" with payload "{}"'.format(topic, payload))
+ response = self.lambda_client._invoke_internal(
+ function_arn,
+ payload,
+ base64.b64encode(json.dumps(client_context).encode())
+ )
+
+ payload = response['Payload'].read()
+ if response:
+ response_payload_map = json.loads(payload.decode('utf-8'))
+ if 'code' in response_payload_map and 'message' in response_payload_map:
+ raise ShadowError('Request for shadow state returned error code {} with message "{}"'.format(
+ response_payload_map['code'], response_payload_map['message']
+ ))
+
+ return {'payload': payload}
diff --git a/aws/lambdas/optimizedImageClassification/greengrasssdk/Lambda.py b/aws/lambdas/optimizedImageClassification/greengrasssdk/Lambda.py
new file mode 100644
index 0000000..7272fff
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/greengrasssdk/Lambda.py
@@ -0,0 +1,135 @@
+#
+# Copyright 2010-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+
+import logging
+import re
+
+from io import BytesIO
+
+from greengrass_common.function_arn_fields import FunctionArnFields
+from greengrass_ipc_python_sdk.ipc_client import IPCClient, IPCException
+from greengrasssdk.utils.testing import mock
+
+# Log messages in the SDK are part of customer's log because they're helpful for debugging
+# customer's lambdas. Since we configured the root logger to log to customer's log and set the
+# propagate flag of this logger to True. The log messages submitted from this logger will be
+# sent to the customer's local Cloudwatch handler.
+customer_logger = logging.getLogger(__name__)
+customer_logger.propagate = True
+
+valid_base64_regex = '^([A-Za-z0-9+/]{4})*([A-Za-z0-9+/]{4}|[A-Za-z0-9+/]{3}=|[A-Za-z0-9+/]{2}==)$'
+
+
+class InvocationException(Exception):
+ pass
+
+
+class Client:
+ def __init__(self, endpoint='localhost', port=8000):
+ """
+ :param endpoint: Endpoint used to connect to IPC.
+ :type endpoint: str
+
+ :param port: Port number used to connect to the :code:`endpoint`.
+ :type port: int
+ """
+ self.ipc = IPCClient(endpoint=endpoint, port=port)
+
+ def invoke(self, **kwargs):
+
+ # FunctionName is a required parameter
+ if 'FunctionName' not in kwargs:
+ raise ValueError(
+ '"FunctionName" argument of Lambda.Client.invoke is a required argument but was not provided.'
+ )
+
+ arn_fields = FunctionArnFields(kwargs['FunctionName'])
+ arn_qualifier = arn_fields.qualifier
+
+ # A Function qualifier can be provided as part of the ARN in FunctionName, or it can be provided here. The
+ # behavior of the cloud is to throw an exception if both are specified but not equal
+ extraneous_qualifier = kwargs.get('Qualifier', '')
+
+ if extraneous_qualifier and arn_qualifier and arn_qualifier != extraneous_qualifier:
+ raise ValueError('The derived qualifier from the function name does not match the specified qualifier.')
+
+ final_qualifier = arn_qualifier if arn_qualifier else extraneous_qualifier
+
+ function_arn = FunctionArnFields.build_arn_string(
+ arn_fields.region, arn_fields.account_id, arn_fields.name, final_qualifier
+ )
+
+ # ClientContext must be base64 if given, but is an option parameter
+ try:
+ client_context = kwargs.get('ClientContext', b'').decode()
+ except AttributeError as e:
+ customer_logger.exception(e)
+ raise ValueError(
+ '"ClientContext" argument must be a byte string or support a decode method which returns a string'
+ )
+
+ if client_context:
+ if not re.match(valid_base64_regex, client_context):
+ raise ValueError('"ClientContext" argument of Lambda.Client.invoke must be base64 encoded.')
+
+ # Payload is an optional parameter
+ payload = kwargs.get('Payload', b'')
+ invocation_type = kwargs.get('InvocationType', 'RequestResponse')
+ customer_logger.debug('Invoking local lambda "{}" with payload "{}" and client context "{}"'.format(
+ function_arn, payload, client_context))
+
+ # Post the work to IPC and return the result of that work
+ return self._invoke_internal(function_arn, payload, client_context, invocation_type)
+
+ @mock
+ def _invoke_internal(self, function_arn, payload, client_context, invocation_type="RequestResponse"):
+ """
+ This private method is seperate from the main, public invoke method so that other code within this SDK can
+ give this Lambda client a raw payload/client context to invoke with, rather than having it built for them.
+ This lets you include custom ExtensionMap_ values like subject which are needed for our internal pinned Lambdas.
+ """
+ customer_logger.debug('Invoking Lambda function "{}" with Greengrass Message "{}"'.format(function_arn, payload))
+
+ try:
+ invocation_id = self.ipc.post_work(function_arn, payload, client_context, invocation_type)
+
+ if invocation_type == "Event":
+ # TODO: Properly return errors based on BOTO response
+ # https://boto3.readthedocs.io/en/latest/reference/services/lambda.html#Lambda.Client.invoke
+ return {'Payload': b'', 'FunctionError': ''}
+
+ work_result_output = self.ipc.get_work_result(function_arn, invocation_id)
+ if not work_result_output.func_err:
+ output_payload = StreamingBody(work_result_output.payload)
+ else:
+ output_payload = work_result_output.payload
+ invoke_output = {
+ 'Payload': output_payload,
+ 'FunctionError': work_result_output.func_err,
+ }
+ return invoke_output
+ except IPCException as e:
+ customer_logger.exception(e)
+ raise InvocationException('Failed to invoke function due to ' + str(e))
+
+
+class StreamingBody(object):
+ """Wrapper class for http response payload
+
+ This provides a consistent interface to AWS Lambda Python SDK
+ """
+ def __init__(self, payload):
+ self._raw_stream = BytesIO(payload)
+ self._amount_read = 0
+
+ def read(self, amt=None):
+ """Read at most amt bytes from the stream.
+ If the amt argument is omitted, read all data.
+ """
+ chunk = self._raw_stream.read(amt)
+ self._amount_read += len(chunk)
+ return chunk
+
+ def close(self):
+ self._raw_stream.close()
diff --git a/aws/lambdas/optimizedImageClassification/greengrasssdk/__init__.py b/aws/lambdas/optimizedImageClassification/greengrasssdk/__init__.py
new file mode 100644
index 0000000..c934592
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/greengrasssdk/__init__.py
@@ -0,0 +1,7 @@
+#
+# Copyright 2010-2016 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+
+from .client import client
+from .Lambda import StreamingBody
+INTERFACE_VERSION = '1.0'
diff --git a/aws/lambdas/optimizedImageClassification/greengrasssdk/client.py b/aws/lambdas/optimizedImageClassification/greengrasssdk/client.py
new file mode 100644
index 0000000..b881062
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/greengrasssdk/client.py
@@ -0,0 +1,14 @@
+#
+# Copyright 2010-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+
+
+def client(client_type, *args):
+ if client_type == 'lambda':
+ from .Lambda import Client
+ elif client_type == 'iot-data':
+ from .IoTDataPlane import Client
+ else:
+ raise Exception('Client type {} is not recognized.'.format(repr(client_type)))
+
+ return Client(*args)
diff --git a/aws/lambdas/optimizedImageClassification/greengrasssdk/utils/__init__.py b/aws/lambdas/optimizedImageClassification/greengrasssdk/utils/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/aws/lambdas/optimizedImageClassification/greengrasssdk/utils/testing.py b/aws/lambdas/optimizedImageClassification/greengrasssdk/utils/testing.py
new file mode 100644
index 0000000..2b334b2
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/greengrasssdk/utils/testing.py
@@ -0,0 +1,35 @@
+#
+# Copyright 2010-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+
+import json
+from functools import wraps
+from greengrass_common.env_vars import MY_FUNCTION_ARN
+
+
+def mock(func):
+ """
+ mock decorates _invoke_internal by checking if MY_FUNCTION_ARN is present
+ if MY_FUNCTION_ARN is present, the actual _invoke_internal is invoked
+ otherwise, the mock _invoke_internal is invoked
+ """
+ @wraps(func)
+ def mock_invoke_internal(self, function_arn, payload, client_context, invocation_type="RequestResponse"):
+ if MY_FUNCTION_ARN is None:
+ if invocation_type == 'RequestResponse':
+ return {
+ 'Payload': json.dumps({
+ 'TestKey': 'TestValue'
+ }),
+ 'FunctionError': ''
+ }
+ elif invocation_type == 'Event':
+ return {
+ 'Payload': b'',
+ 'FunctionError': ''
+ }
+ else:
+ raise Exception('Unsupported invocation type {}'.format(invocation_type))
+ else:
+ return func(self, function_arn, payload, client_context, invocation_type)
+ return mock_invoke_internal
diff --git a/aws/lambdas/optimizedImageClassification/inference.py b/aws/lambdas/optimizedImageClassification/inference.py
new file mode 100644
index 0000000..1bd06ca
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/inference.py
@@ -0,0 +1,112 @@
+#
+# Copyright 2010-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Greengrass lambda function to perform Image Classification with example model
+# Resnet-50 that was compiled by DLC.
+#
+#
+import logging
+import os
+import json
+
+from dlr import DLRModel
+from PIL import Image
+import numpy as np
+
+import greengrasssdk
+import camera
+import utils
+
+import boto3
+
+kinesis = boto3.client('kinesis')
+
+# Create MQTT client
+mqtt_client = greengrasssdk.client('iot-data')
+
+# Initialize logger
+customer_logger = logging.getLogger(__name__)
+
+# Initialize example Resnet-50 model
+model_resource_path = os.environ.get('MODEL_PATH', '/ml_model')
+input_shape = {'data': [1, 3, 224, 224]}
+output_shape = [1, 1000]
+dlr_model = DLRModel(model_resource_path, input_shape, output_shape, 'cpu')
+
+# Read synset file
+#synset_path = os.path.join(model_resource_path, 'synset.txt')
+#with open(synset_path, 'r') as f:
+# synset = eval(f.read())
+
+
+def predict(image_data):
+ r"""
+ Predict image with DLR. The result will be published
+ to MQTT topic 'deepgauge_model/predictions'.
+
+ :param image: numpy array of the Image inference with.
+ """
+ flattened_data = image_data.astype(np.float32).flatten()
+
+ prediction_scores = dlr_model.run({'data' : flattened_data}).squeeze()
+ max_score_id = np.argmax(prediction_scores)
+ max_score = np.max(prediction_scores)
+
+ result = json.dumps({"id": max_score_id, "score": max_score})
+
+ # Prepare result
+ #predicted_class = synset[max_score_id]
+ #result = 'Inference result: probability {}.'.format(max_score)
+
+ # Send result
+ send_mqtt_message(result)
+ kinesis.put_record(StreamName="DeepGauge",
+ Data=result,
+ PartitionKey="singleshardkey")
+
+
+def predict_from_cam():
+ r"""
+ Predict with the photo taken from your pi camera.
+ """
+ #send_mqtt_message("Taking a photo...")
+ my_camera = camera.Camera()
+ image = Image.open(my_camera.capture_image())
+ image_data = utils.transform_image(image)
+
+ #send_mqtt_message("Start predicting...")
+ predict(image_data)
+
+
+def predict_from_image(filename):
+ image = Image.open(filename)
+ image_data = utils.transform_image(image)
+
+ #send_mqtt_message("Start predicting...")
+ predict(image_data)
+
+
+def send_mqtt_message(message):
+ r"""
+ Publish message to the MQTT topic:
+ 'deepgauge_model/predictions'.
+
+ :param message: message to publish
+ """
+ mqtt_client.publish(topic='deepgauge_model/predictions',
+ payload=message)
+
+
+# The lambda to be invoked in Greengrass
+def handler(event, context):
+ filename = event.get('filename')
+ try:
+ if (filename == None):
+ predict_from_cam()
+ else:
+ predict_from_image(filename)
+
+ except Exception as e:
+ customer_logger.exception(e)
+ send_mqtt_message(
+ 'Exception occurred during prediction. Please check logs for troubleshooting: /greengrass/ggc/var/log.')
diff --git a/aws/lambdas/optimizedImageClassification/utils/__init__.py b/aws/lambdas/optimizedImageClassification/utils/__init__.py
new file mode 100644
index 0000000..3761257
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/utils/__init__.py
@@ -0,0 +1,6 @@
+#
+# Copyright 2010-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+#
+
+from image_util import transform_image
diff --git a/aws/lambdas/optimizedImageClassification/utils/image_util.py b/aws/lambdas/optimizedImageClassification/utils/image_util.py
new file mode 100644
index 0000000..466dca3
--- /dev/null
+++ b/aws/lambdas/optimizedImageClassification/utils/image_util.py
@@ -0,0 +1,16 @@
+#
+# Copyright 2010-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Image Utilities.
+#
+import numpy as np
+
+def transform_image(image):
+ r"""
+ Transform image for dlr model example.
+ """
+ image = np.array(image) - np.array([123., 117., 104.])
+ image /= np.array([58.395, 57.12, 57.375])
+ image = image.transpose((2, 0, 1))
+ image = image[np.newaxis, :]
+ return image
diff --git a/cloud-functions/README.md b/cloud-functions/README.md
new file mode 100644
index 0000000..5a8ee8f
--- /dev/null
+++ b/cloud-functions/README.md
@@ -0,0 +1,228 @@
+# Cloud Functions
+## Background Cloud Function
+Writing, deploying, and triggering a Background Cloud Function with a Cloud Storage trigger.
+
+**Objectives**
+- Write and deploy a Background Cloud Function.
+- Trigger the function by uploading a file to Cloud Storage.
+
+Update and install gcloud components:
+```
+gcloud components update &&
+gcloud components install beta
+```
+
+### Preparing the application
+1. Create a Cloud Storage bucket to upload a test file, where YOUR_TRIGGER_BUCKET_NAME is a globally unique bucket name:
+```
+gsutil mb gs://YOUR_TRIGGER_BUCKET_NAME
+gsutil mb gs://ocideepgauge-images
+```
+
+### Deploying and triggering the function
+
+
+Currently, Cloud Storage functions are based on [Pub/Sub notifications from Cloud Storage](https://cloud.google.com/storage/docs/pubsub-notifications) and support similar event types:
+
+- [finalize](https://cloud.google.com/functions/docs/tutorials/storage#object_finalize)
+
+- [delete](https://cloud.google.com/functions/docs/tutorials/storage#object_delete)
+
+- [archive](https://cloud.google.com/functions/docs/tutorials/storage#object_archive)
+
+- [metadata update](https://cloud.google.com/functions/docs/tutorials/storage#object_metadata_update)
+
+The following sections describe how to deploy and trigger a function for each of these event types.
+
+### Object Finalize
+
+Object finalize events trigger when a "write" of a [Cloud Storage Object](https://cloud.google.com/storage/docs/json_api/v1/objects#resource) is successfully finalized. In particular, this means that creating a new object or overwriting an existing object triggers this event. Archive and metadata update operations are ignored by this trigger.
+
+#### Object Finalize: deploying the function
+
+Take a look at the sample function, which handles Cloud Storage events:
+```
+def hello_gcs_generic(data, context):
+ """Background Cloud Function to be triggered by Cloud Storage.
+ This generic function logs relevant data when a file is changed.
+
+ Args:
+ data (dict): The Cloud Functions event payload.
+ context (google.cloud.functions.Context): Metadata of triggering event.
+ Returns:
+ None; the output is written to Stackdriver Logging
+ """
+
+ print('Event ID: {}'.format(context.event_id))
+ print('Event type: {}'.format(context.event_type))
+ print('Bucket: {}'.format(data['bucket']))
+ print('File: {}'.format(data['name']))
+ print('Metageneration: {}'.format(data['metageneration']))
+ print('Created: {}'.format(data['timeCreated']))
+ print('Updated: {}'.format(data['updated']))
+```
+Cloud Functions looks for your code in a file named `main.py`.
+
+To deploy the function, run the following command in the directory where the sample code is located:
+
+```
+gcloud functions deploy hello_gcs_generic --runtime python37 --trigger-resource YOUR_TRIGGER_BUCKET_NAME --trigger-event google.storage.object.finalize
+```
+Deep Gauge
+```
+gcloud functions deploy predict_gauge --source=. --runtime python37 --trigger-resource ocideepgauge-images --trigger-event google.storage.object.metadataUpdate
+```
+
+#### Object Finalize: triggering the function
+
+To trigger the function:
+
+1. Create an empty `gcf-test.txt` file in the directory where the sample code is located.
+
+2. Upload the file to Cloud Storage in order to trigger the function:
+```
+ gsutil cp gcf-test.txt gs://ocideepgauge-images
+ gsutil cp daisy.jpg gs://ocideepgauge-images
+```
+
+
+3. Check the logs to make sure the executions have completed:
+```
+gcloud functions logs read --limit 50
+```
+
+### Object Delete
+
+Object delete events are most useful for [non-versioning buckets](https://cloud.google.com/storage/docs/object-versioning). They are triggered when an old version of an object is deleted. In addition, they are triggered when an object is overwritten. Object delete triggers can also be used with [versioning buckets](https://cloud.google.com/storage/docs/object-versioning), triggering when a version of an object is permanently deleted.
+
+#### Object Delete: deploying the function
+
+Using the same sample code as in the finalize example, deploy the function with object delete as the trigger event. Run the following command in the directory where the sample code is located:
+
+```
+gcloud functions deploy hello_gcs_generic --runtime python37 --trigger-resource YOUR_TRIGGER_BUCKET_NAME --trigger-event google.storage.object.delete
+```
+
+```
+gcloud functions deploy predict_gauge --runtime python37 --trigger-resource ocideepgauge-images --trigger-event google.storage.object.delete
+```
+
+where `*YOUR_TRIGGER_BUCKET_NAME*` is the name of the Cloud Storage bucket that triggers the function.
+
+#### Object Delete: triggering the function
+
+To trigger the function:
+
+1. Create an empty `gcf-test.txt` file in the directory where the sample code is located.
+
+2. Make sure that your bucket is non-versioning:
+
+ gsutil versioning set off gs://*YOUR_TRIGGER_BUCKET_NAME*
+
+3. Upload the file to Cloud Storage:
+
+ gsutil cp gcf-test.txt gs://*YOUR_TRIGGER_BUCKET_NAME*
+
+ where `*YOUR_TRIGGER_BUCKET_NAME*` is the name of your Cloud Storage bucket where you will upload a test file. At this point the function should not execute yet.
+
+4. Delete the file to trigger the function:
+
+ gsutil rm gs://*YOUR_TRIGGER_BUCKET_NAME*/gcf-test.txt
+
+5. Check the logs to make sure the executions have completed:
+
+ `gcloud functions logs read --limit 50\
+ `
+
+Note that the function may take some time to finish executing.
+
+# PubSub
+
+## Create a topic and a subscription
+
+Once you create a topic, you can subscribe or publish to it.
+
+Use the [gcloud pubsub topics create](https://cloud.google.com/sdk/gcloud/reference/pubsub/topics/create) command to create a topic:
+```
+gcloud pubsub topics create my-topic
+```
+Use the [gcloud pubsub subscriptions create](https://cloud.google.com/sdk/gcloud/reference/pubsub/subscriptions/create) command to create a subscription. Only messages published to the topic after the subscription is created are available to subscriber applications.
+```
+gcloud pubsub subscriptions create my-sub --topic my-topic
+gcloud pubsub subscriptions create gauge-prediction --topic gauge-prediction
+```
+# BigQuery
+
+## Create BigQuery Dataset and Table
+
+i)Creating a dataset
+```
+from google.cloud import bigquery
+client = bigquery.Client()
+dataset_id = 'my_dataset'
+dataset_ref = client.dataset(dataset_id)
+dataset = bigquery.Dataset(dataset_ref)
+dataset.location = 'US'
+dataset = client.create_dataset(dataset) # API request
+```
+ii) Creating Schema for flowers ML Engine BigQuery
+```
+SCHEMA = [
+ bigquery.SchemaField('KEY', 'INTEGER', mode='REQUIRED'),
+ bigquery.SchemaField('PREDICTION', 'INTEGER', mode='REQUIRED'),
+ bigquery.SchemaField('SCORE1','FLOAT', mode='REQUIRED'),
+ bigquery.SchemaField('SCORE2','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE3','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE4','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE5','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE6','FLOAT',mode='REQUIRED'),
+ ]
+```
+iii) Creating a table based on the sample schema
+```
+schema = [
+ bigquery.SchemaField('full_name', 'STRING', mode='REQUIRED'),
+ bigquery.SchemaField('age', 'INTEGER', mode='REQUIRED'),
+]
+table_ref = dataset_ref.table('my_table')
+table = bigquery.Table(table_ref, schema=schema)
+table = client.create_table(table) # API request
+
+assert table.table_id == 'my_table'
+```
+## Insert rows in BigQuery Table
+You can load data:
+
+From Cloud Storage
+1. From other Google services, such as Google Ad Manager and Google Ads
+2. From a readable data source (such as your local machine)
+3. By inserting individual records using streaming inserts
+4. Using DML statements to perform bulk inserts
+5. Using a Google BigQuery IO transform in a Cloud Dataflow pipeline to write data to BigQuery
+
+Note: For the DeepGauge we use streaming inserts.
+
+### Streaming Data into BigQuery
+Instead of using a job to load data into BigQuery, you can choose to stream your data into BigQuery one record at a time by using the tabledata().insertAll() method. This approach enables querying data without the delay of running a load job.
+```
+rows_to_insert = [
+ (u'Phred Phlyntstone', 32),
+ (u'Wylma Phlyntstone', 29),
+]
+errors = client.insert_rows(table, rows_to_insert) # API request
+
+assert errors == []
+```
+The added table and data can be views at BigQuery WebUI or using BigQuery commands at terminal.
+1. WebUI to view the BigQuery datasets and tables for the project
+```
+https://console.cloud.google.com/bigquery?project=ocideepgauge&authuser=1&p=ocideepgauge&d=flowers_dataset&t=flowers_table&page=table
+
+SELECT SCORE1
+FROM `ocideepgauge.flowers_dataset.flowers_table`
+LIMIT 1000
+```
+2. Command line
+```
+bq ls --format=pretty ocideepgauge:flowers_dataset
+```
diff --git a/cloud-functions/background/main.py b/cloud-functions/background/main.py
new file mode 100644
index 0000000..d65ba92
--- /dev/null
+++ b/cloud-functions/background/main.py
@@ -0,0 +1,63 @@
+import base64, json, datetime
+
+# Imports the Google Cloud client library
+# from google.cloud import bigquery
+from google.cloud import pubsub_v1
+from google.cloud import storage
+from googleapiclient import discovery
+
+
+# [START functions_predict_gauge]
+def predict_gauge(data, context):
+ """Background Cloud Function to be triggered by Cloud Storage.
+ This generic function logs relevant data when a file is changed.
+ Args:
+ data (dict): The Cloud Functions event payload.
+ context (google.cloud.functions.Context): Metadata of triggering event.
+ Returns:
+ None; the output is written to Stackdriver Logging
+ """
+
+ # Get the file from the storage bucket
+ client = storage.Client()
+ bucket_id = 'ocideepgauge-images'
+ bucket = client.get_bucket(bucket_id)
+ blob = bucket.blob(data['name'])
+ my_blob = bucket.get_blob(data['name'])
+ img = base64.b64encode(blob.download_as_string())
+
+ instance = {"bytes": {"b64": img.decode("utf8")}}
+
+ # Compose request to ML Engine
+ project = 'ocideepgauge'
+ model = 'dg'
+ service = discovery.build('ml', 'v1', cache_discovery=False)
+ name = 'projects/{}/models/{}'.format(project, model)
+
+ # Create a request to call projects.models.predict.
+ response = service.projects().predict(
+ name=name,
+ body={'instances': [instance]}
+ ).execute()
+
+ # Compose request to PUB/SUB
+ topic_name = "gauge-prediction"
+
+ publisher = pubsub_v1.PublisherClient()
+ topic_path = publisher.topic_path(project, topic_name)
+
+ # return the image of the device
+ thumbnail = 'https://storage.googleapis.com/{0}/{1}'.format(bucket_id, data['name'])
+
+ # Data must be a bytestring
+ predictions = json.dumps(response['predictions'])
+ bytestring = predictions.encode('utf-8')
+ device_id = my_blob.metadata['device_id']
+
+
+ # Add two attributes, origin and username, to the message
+ publisher.publish(topic_path,bytestring,image=thumbnail,device=device_id)
+
+ return response
+
+# [END functions_predict_gauge]
diff --git a/cloud-functions/background/main_original.py b/cloud-functions/background/main_original.py
new file mode 100644
index 0000000..8c099b3
--- /dev/null
+++ b/cloud-functions/background/main_original.py
@@ -0,0 +1,114 @@
+import base64, json
+from google.cloud import storage
+from googleapiclient import discovery
+from google.cloud import pubsub_v1
+# Imports the Google Cloud client library
+from google.cloud import bigquery
+import datetime
+
+def flowers_table_insert_rows(client, datarow):
+ SCHEMA = [
+ bigquery.SchemaField('DATETIME','DATETIME',mode='REQUIRED'),
+ bigquery.SchemaField('KEY','INTEGER',mode='REQUIRED'),
+ bigquery.SchemaField('PREDICTION','INTEGER',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE1','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE2','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE3','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE4','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE5','FLOAT',mode='REQUIRED'),
+ bigquery.SchemaField('SCORE6','FLOAT',mode='REQUIRED')
+ ]
+
+ #my_bigquery.dataset(dataset_name).table(table_name).exists() # returns boolean
+
+ """Insert / fetch table data."""
+ dataset_id = 'flowers_dataset_final'
+ table_id = 'flowers_table_final'
+ dataset = bigquery.Dataset(client.dataset(dataset_id))
+ try:
+ dataset = client.create_dataset(dataset)
+ except Exception as err:
+ print("dataset already exists")
+ dataset.location = 'US'
+ table = bigquery.Table(dataset.table(table_id), schema=SCHEMA)
+ try:
+ table = client.create_table(table)
+ except Exception as err:
+ print("table already exists")
+ rows_to_insert = datarow
+ errors = client.insert_rows(table, rows_to_insert) # API request
+ assert errors == []
+ # [END bigquery_table_insert_rows]
+
+
+# [START functions_predict_gauge]
+def predict_gauge(data, context):
+ """Background Cloud Function to be triggered by Cloud Storage.
+ This generic function logs relevant data when a file is changed.
+ Args:
+ data (dict): The Cloud Functions event payload.
+ context (google.cloud.functions.Context): Metadata of triggering event.
+ Returns:
+ None; the output is written to Stackdriver Logging
+ """
+
+ # Get the file from the storage bucket
+ client = storage.Client()
+ bucket_id = 'ocideepgauge-images'
+ bucket = client.get_bucket(bucket_id)
+ blob = bucket.blob(data['name'])
+ img = base64.b64encode(blob.download_as_string())
+
+ instance = {"key":"0", "image_bytes": {"b64": img.decode("utf8")}}
+
+ #
+ # Compose request to ML Engine
+ #
+ project = 'ocideepgauge'
+ model = 'flowers'
+ service = discovery.build('ml', 'v1', cache_discovery=False)
+ name = 'projects/{}/models/{}'.format(project, model)
+
+ # Create a request to call projects.models.predict.
+ response = service.projects().predict(
+ name=name,
+ body={'instances': [instance]}
+ ).execute()
+
+ #
+ # Compose request to PUB/SUB
+ #
+ topic_name = "flower-prediction"
+
+ publisher = pubsub_v1.PublisherClient()
+ topic_path = publisher.topic_path(project, topic_name)
+
+ # Data must be a bytestring
+ predictions = json.dumps(response['predictions'])
+ bytestring = predictions.encode('utf-8')
+
+ # Add two attributes, origin and username, to the message
+ publisher.publish(topic_path, bytestring, origin='flower-sample', username='gcp')
+
+ print('Published messages with custom attributes.')
+ # daisy - 0, dandelion - 1, roses - 2, sunflowers - 3, tulips - 4
+ #print(response['predictions']
+ dt=datetime.datetime.now()
+ #Compose request to BigQuery
+ predict=(response['predictions'][0]['prediction'])
+ key=(response['predictions'][0]['key'])
+ score1, score2, score3, score4, score5, score6=(response['predictions'][0]['scores'])
+ rows=[(dt, key, predict, score1, score2, score3, score4, score5, score6)]
+ client = bigquery.Client()
+ flowers_table_insert_rows(client,rows)
+ print(dt, key, predict, score1, score2, score3,score4,score5,score6)
+ #print(reponse['predictions'][2])
+ # Print General Information
+ #print('Event ID: {}'.format(context.event_id))
+ #print('Event type: {}'.format(context.event_type))
+ #print('Bucket: {}'.format(data['bucket']))
+ #print('File: {}'.format(data['name']))
+ #print('Metageneration: {}'.format(data['metageneration']))
+ #print('Created: {}'.format(data['timeCreated']))
+ #print('Updated: {}'.format(data['updated']))
+# [END functions_predict_gauge]
\ No newline at end of file
diff --git a/cloud-functions/background/requirements.txt b/cloud-functions/background/requirements.txt
new file mode 100644
index 0000000..2973593
--- /dev/null
+++ b/cloud-functions/background/requirements.txt
@@ -0,0 +1,5 @@
+# Function dependencies, for example:
+google-cloud-storage
+google-api-python-client
+google-cloud-pubsub
+google-cloud-bigquery
diff --git a/cloud-functions/opencv_background/main.py b/cloud-functions/opencv_background/main.py
new file mode 100644
index 0000000..99048a9
--- /dev/null
+++ b/cloud-functions/opencv_background/main.py
@@ -0,0 +1,61 @@
+import cv2
+import numpy as np
+from skimage import io
+from google.cloud import storage
+import tempfile
+
+"""Background Cloud Function to be triggered by Cloud Storage.
+ This function takes an image and detects a circle in it, replaces
+ the background with single color
+ Arg:
+ data: object that holds img
+ Returns:
+ None; the output is saved to a file location
+ """
+
+def image_circle_detection(data):
+ # Get the file from the storage bucket
+ client = storage.Client()
+ bucket_id = 'ocideepgauge-image-w-background'
+ bucket = client.get_bucket(bucket_id)
+ img = io.imread(data['mediaLink'])
+ if img is None: # Check if image exists
+ print('Error opening image!')
+ print("Fail")
+
+ gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Convert to gray
+ gray = cv2.medianBlur(gray, 5)
+
+ rows = gray.shape[0]
+ circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, rows / 4,
+ param1=200, param2=60,
+ minRadius=0, maxRadius=0) # Hough Circle function
+ mask = np.full((img.shape[0], img.shape[1]), 0, dtype=np.uint8) # Mask creation
+ circle_details = None
+ if circles is not None:
+ circles = np.uint16(np.around(circles))
+ for i in circles[0, :]:
+ cv2.circle(mask, (i[0], i[1]), i[2], (255, 255, 255), -1) # Circle on mask around gauge
+ circle_details = i
+ fg = cv2.bitwise_or(img, img, mask=mask) # Compares img to mask
+ mask = cv2.bitwise_not(mask)
+ background = np.full(img.shape, 255, dtype=np.uint8)
+ bk = cv2.bitwise_or(background, background, mask=mask)
+ bk[mask == 255] = (255, 255, 255) # Set color of mask background
+ final = cv2.bitwise_or(fg, bk)
+
+ cropped = final[circle_details[1] - circle_details[2]:circle_details[1] + circle_details[2],
+ circle_details[0] - circle_details[2]:circle_details[0] + circle_details[2]]
+ final_resized = cv2.resize(cropped, (1920, 1080)) # Set img size
+ newname = "mod-" + data['name']
+ with tempfile.NamedTemporaryFile() as temp:
+ # Extract name to the temp file
+ iName = "".join([str(temp.name), ".jpg"])
+ # Save image to temp file
+ cv2.imwrite(iName, final_resized)
+ # Storing the image temp file inside the bucket
+ blob = bucket.blob(newname)
+ blob.upload_from_filename(iName, content_type=data['contentType'])
+
+ else:
+ print("No Circles Found")
diff --git a/cloud-functions/opencv_background/main_local.py b/cloud-functions/opencv_background/main_local.py
new file mode 100644
index 0000000..b7e60ae
--- /dev/null
+++ b/cloud-functions/opencv_background/main_local.py
@@ -0,0 +1,73 @@
+import cv2
+import numpy as np
+""" {
+ insertId: "000000-d13b9266-1773-4b78-bab9-25ef8da0999b"
+
+labels: {
+ execution_id: "ru1d7zvnt2w9"
+ }
+ logName: "projects/ocideepgauge/logs/cloudfunctions.googleapis.com%2Fcloud-functions"
+ receiveTimestamp: "2018-12-04T16:48:46.200758883Z"
+
+resource: {
+
+labels: {
+ function_name: "remove_background"
+ project_id: "ocideepgauge"
+ region: "us-central1"
+ }
+ type: "cloud_function"
+ }
+ severity: "DEBUG"
+ textPayload: "Function execution started"
+ timestamp: "2018-12-04T16:48:39.727682831Z"
+ trace: "projects/ocideepgauge/traces/d54ae2da15f3e62990b565c40d9c6ccc"
+}"""
+
+def image_circle_detection(input_path, output_path):
+ img = cv2.imread(input_path) # Image source
+ if img is None: # Check if image exists
+ print('Error opening image!')
+ print("Fail")
+
+ gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Convert to gray
+ gray = cv2.medianBlur(gray, 5)
+
+ rows = gray.shape[0]
+ circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, rows / 4,
+ param1=200, param2=60,
+ minRadius=0, maxRadius=0) # Hough Circle function
+ mask = np.full((img.shape[0], img.shape[1]), 0, dtype=np.uint8) # Mask creation
+ circle_details = None
+ if circles is not None:
+ circles = np.uint16(np.around(circles))
+ for i in circles[0, :]:
+ cv2.circle(mask, (i[0], i[1]), i[2], (255, 255, 255), -1) # Circle on mask around gauge
+ circle_details = i
+ fg = cv2.bitwise_or(img, img, mask=mask) # Compares img to mask
+ mask = cv2.bitwise_not(mask)
+ background = np.full(img.shape, 255, dtype=np.uint8)
+ bk = cv2.bitwise_or(background, background, mask=mask)
+ bk[mask == 255] = (255, 255, 255) # Set color of mask background
+ final = cv2.bitwise_or(fg, bk)
+
+ cropped = final[circle_details[1] - circle_details[2]:circle_details[1] + circle_details[2],
+ circle_details[0] - circle_details[2]:circle_details[0] + circle_details[2]]
+ finalR = cv2.resize(cropped, (1920, 1080)) # Set img size
+ cv2.imshow("circle mask", finalR) # Show image (Future location to be a Google Storage bucket
+ cv2.imwrite(output_path, finalR)
+ else:
+ print("No Circles Found")
+
+ cv2.waitKey(0)
+ cv2.destroyAllWindows()
+
+
+def main():
+ image = '' # Place path to image here
+ path = '' # Place path to save new image to here
+ image_circle_detection(image, path)
+
+
+if __name__ == '__main__':
+ main()
diff --git a/cloud-functions/opencv_background/requirements.txt b/cloud-functions/opencv_background/requirements.txt
new file mode 100644
index 0000000..ef3a857
--- /dev/null
+++ b/cloud-functions/opencv_background/requirements.txt
@@ -0,0 +1,7 @@
+# Function dependencies, for example:
+# package>=version
+opencv-python==3.4.4.19
+numpy==1.15.4
+scikit-image==0.14.1
+google-cloud-storage
+google-api-python-client
\ No newline at end of file
diff --git a/cloud-functions/opencv_background/requirements_local.txt b/cloud-functions/opencv_background/requirements_local.txt
new file mode 100644
index 0000000..8a1c388
--- /dev/null
+++ b/cloud-functions/opencv_background/requirements_local.txt
@@ -0,0 +1,6 @@
+# Function dependencies
+opencv-python
+google-cloud-storage
+google-api-python-client
+google-cloud-pubsub
+google-cloud-bigquery
\ No newline at end of file
diff --git a/cloud-functions/opencv_background/video_detection_WIP.py b/cloud-functions/opencv_background/video_detection_WIP.py
new file mode 100644
index 0000000..1902d26
--- /dev/null
+++ b/cloud-functions/opencv_background/video_detection_WIP.py
@@ -0,0 +1,101 @@
+import cv2
+import numpy as np
+
+def dist_2_pts(x1, y1, x2, y2):
+ return np.sqrt((x2 - x1)**2 + (y2 - y1)**2)
+
+
+def live_video_detection():
+ cap = cv2.VideoCapture(0)
+ t1 = True
+ while(True):
+ ret, frame = cap.read()
+
+ gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+ gray = cv2.medianBlur(gray, 5)
+
+ rows = frame.shape[0]
+ circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, rows / 16,
+ param1=200, param2=100,
+ minRadius=0, maxRadius=0)
+
+ mask = np.full((gray.shape[0], gray.shape[1]), 0, dtype=np.uint8)
+
+ if circles is not None:
+ print("found circle")
+ circles = np.uint16(np.around(circles))
+ for i in circles[0, :]:
+ center = (i[0], i[1])
+ # circle center
+ cv2.circle(gray, center, 1, (0, 100, 100), 3)
+ # circle outline
+ radius = i[2]
+ cv2.circle(gray, center, radius, (255, 0, 255), 3)
+
+ """
+ if i[0] is not 0 or i[1] is not 0 or i[2] is not 0:
+ print("in")
+ cv2.imwrite('/home/gabe/Documents/test_gauge.png', gray)
+ t1 = False
+ break
+ else:
+ print("loc")
+ if t1 == False:
+ break
+ # find lines
+ minLineLength = 10
+ maxLineGap = 0
+ lines = cv2.HoughLinesP(image=gray, rho=3, theta=np.pi / 180, threshold=100, minLineLength=minLineLength,
+ maxLineGap=0) # rho is set to 3 to detect more lines, easier to get more then filter them out later4
+
+ if lines is not None:
+ print("Found line")
+ final_line_list = []
+ # print "radius: %s" %r
+
+ diff1LowerBound = 0.15 # diff1LowerBound and diff1UpperBound determine how close the line should be from the center
+ diff1UpperBound = 0.25
+ diff2LowerBound = 0.5 # diff2LowerBound and diff2UpperBound determine how close the other point of the line should be to the outside of the gauge
+ diff2UpperBound = 1.0
+ for j in range(0, len(lines)):
+ for x1, y1, x2, y2 in lines[j]:
+ diff1 = dist_2_pts(i[0], i[1], x1, y1) # x, y is center of circle
+ diff2 = dist_2_pts(i[0], i[1], x2, y2) # x, y is center of circle
+ # set diff1 to be the smaller (closest to the center) of the two), makes the math easier
+ if (diff1 > diff2):
+ temp = diff1
+ diff1 = diff2
+ diff2 = temp
+ # check if line is within an acceptable range
+ if (((diff1 < diff1UpperBound * i[2]) and (diff1 > diff1LowerBound * i[2]) and (
+ diff2 < diff2UpperBound * i[2])) and (diff2 > diff2LowerBound * i[2])):
+ line_length = dist_2_pts(x1, y1, x2, y2)
+ # add to final list
+ final_line_list.append([x1, y1, x2, y2])
+
+ # best line
+ x1 = final_line_list[0][0]
+ y1 = final_line_list[0][1]
+ x2 = final_line_list[0][2]
+ y2 = final_line_list[0][3]
+ cv2.line(gray, (x1, y1), (x2, y2), (255, 0, 0), 2)
+ """
+
+ else:
+ print("No Circles Found")
+ count = 0
+
+ # Display the resulting frame
+ cv2.imshow('frame',gray)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+ # When everything done, release the capture
+ cap.release()
+ cv2.destroyAllWindows()
+
+def main():
+ live_video_detection()
+
+if __name__=='__main__':
+ main()
\ No newline at end of file
diff --git a/copy_to_bucket.sh b/copy_to_bucket.sh
deleted file mode 100644
index a00e620..0000000
--- a/copy_to_bucket.sh
+++ /dev/null
@@ -1,2 +0,0 @@
-gsutil -m cp -r ./data/ImageEveryUnit/. gs://deep_gauge/data/
-gsutil -m cp -r ./trainer/. gs://deep_gauge
\ No newline at end of file
diff --git a/customEstimator.py b/customEstimator.py
deleted file mode 100644
index 1e35222..0000000
--- a/customEstimator.py
+++ /dev/null
@@ -1,6 +0,0 @@
-from modules.ensemble_modules.trainer_from_storage.task import main
-import tensorflow as tf
-
-if __name__ == '__main__':
- tf.logging.set_verbosity(tf.logging.INFO)
- tf.app.run(main)
\ No newline at end of file
diff --git a/dumps/best_models_info.pkl b/dumps/best_models_info.pkl
deleted file mode 100644
index 5182eb9..0000000
Binary files a/dumps/best_models_info.pkl and /dev/null differ
diff --git a/ens.sh b/ens.sh
deleted file mode 100644
index 0f51880..0000000
--- a/ens.sh
+++ /dev/null
@@ -1,16 +0,0 @@
-python customEstimator.py --dev=True --retrain_primary_models=False --hidden_units='[100, 200, 300, 500]' --verbosity=DEBUG
-
-
-#######
-gcloud ml-engine local train --module-name trainer_from_storage.task \
- --package-path /home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage \
- -- --primary_models_directory=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/primary_models \
- --ensemble_architecture_path=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/temporary_models \
- --path_to_images=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/data/ImageEveryUnit \
- --bin_path=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/dumps
-
-
-
-
-
-
diff --git a/gaugeReader.ipynb b/gaugeReader.ipynb
deleted file mode 100644
index 52632f4..0000000
--- a/gaugeReader.ipynb
+++ /dev/null
@@ -1,377 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Image Data Preparation:\n",
- "\n",
- "The data processing is implemented through the LoadImg module (modules/LoadImg.py). The images dataset is first split into train and validation datasets, and then the images size and color mode are adjusted (using keras.preprocessing package). The following code block shows how the train and validation datasets can be obtained via LoadImg module."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Using TensorFlow backend.\n"
- ]
- }
- ],
- "source": [
- "import matplotlib.pyplot as plt\n",
- "import numpy as np\n",
- "from modules import LoadImg\n",
- "%matplotlib inline"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "The image pre-processing is complete.\n"
- ]
- }
- ],
- "source": [
- "# The color_mode is either 'rgb' or 'grayscale' (default).\n",
- "X_train, X_validation, y_train, y_validation, cls_indices = LoadImg.Dataset.prep_datasets(\n",
- " ver_ratio=0.2, container_path='data/ImageEveryUnit',\n",
- " final_img_width=79, final_img_height=79,\n",
- " color_mode=\"grayscale\", random_state=1911)\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Data Exploration:"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Train and Validation Datasets\n",
- "After data preparation, there are 1315 images in the training dataset and 329 images in the validation dataset."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "There are 1315 images in the train dataset.\n",
- "There are 329 images in the validation dataset.\n",
- "The images shape is (79, 79, 3)\n"
- ]
- }
- ],
- "source": [
- "print('There are {} images in the train dataset.'.format(X_train.shape[0]))\n",
- "print('There are {} images in the validation dataset.'.format(X_validation.shape[0]))\n",
- "print('The images shape is {}'.format(X_train.shape[1:]))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "In this example, a width and height of 79 were chosen, so the images shape is (79, 79, 3). In the following code blocks, 12 images are randomly selected from train and validation datasets. "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "#### Training Data Samples:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "
"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig = plt.figure(figsize=(15,2.5))\n",
- "imgs_num = np.random.choice(range(len(X_train)), 6)\n",
- "\n",
- "for i, img_num in enumerate(imgs_num):\n",
- " ax = fig.add_subplot(1, 6, i + 1, xticks=[], yticks=[])\n",
- " ax.imshow(X_train[img_num, :, :, 0], cmap='gray')\n",
- " ax.set_title('category {}_train'.format(np.argmax(y_train[img_num])))\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "#### Validation Data Samples:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig = plt.figure(figsize=(15,2.5))\n",
- "imgs_num = np.random.choice(range(len(X_validation)), 6)\n",
- "\n",
- "for i, img_num in enumerate(imgs_num):\n",
- " ax = fig.add_subplot(1, 6, i + 1, xticks=[], yticks=[])\n",
- " ax.imshow(X_validation[img_num, :, :, 0], cmap='gray')\n",
- " ax.set_title('category {}_val'.format(np.argmax(y_validation[img_num])))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Ensembling:"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The objective of this work is to train multiple models (here, referred to as __primary models__) and eventually use them to construct an ensemble model (a two layer fully connected neural network) which can perform with higher validation accuracy than each individual primary models. To construct the ensemble model, first the primay models are trained and then the logits (i.e. the output of the last layer softmax activation functions) of all models are computed and stacked into a numpy array (1D tensor) which will be the input of the ensemble model, a two layer fully connected neural network. The ensemble model is a classifier that is to predict the same 31 categories. It is trained with the same training dataset and its performance is evaluated versus the same validation dataset as those used for the primary models."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Primary Models:"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "\n",
- "\n",
- "For each primary model, a Covolutional Neural Network (CNN) architechture is trained and used for predicting the gauge images categories. There are 30 categories that show the pressure level collected by the gauge with half of the pressure unit (here psi) increments and one NaN category (31 categories all together).\n",
- "\n",
- "The CNN model consists of three CNN and two Fully Connected (FC) layers (the layers are defined in the NewLayers module, _modules/NewLayers.py_, and are combined in the NeuralNet module, _modules/NeuralNet.py_). The activation function of all layers is Rectified Linear Unit (relu) except the last layer which is softmax.\n",
- "\n",
- "For training the primary models, the cross-entropy function and Adam algorithm are employed as the cost function and optimizer, respectively. The model performance is evaluated in each training iteration via the accuracy of the validation dataset and the model checkpoint is saved (in the _logs/models/main_ folder) whenever the accuracy is improved. The models that have high validation accuracy for each specific category are also saved (in folders with the same name as the category name like _logs/models/psi_\\__2_); these models can be later used as primary models.\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Custom Performance Metric:"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The validation dataset accuracy is used as the metric to evaluate the model performance during the model training and the model checkpoint is saved whenever it increases. In tie cases where the performance metric does not change over training iterations, if the median of the true label logits (of the validation dataset) increases, the saved checkpoint is overwritten by the latest model chackpoint.\n",
- "\n",
- "In addition to the model evaluation using the whole validation dataset accuracy, the model perfomance for each specific category is also evaluated using the following equation:\n",
- "\n",
- "_catPerf = (number of true predictions in validation dataset for that category)/(total number of validation samples for that category)_\n",
- "\n",
- "The model checkpoints are also saved whenever the _catPerf_ increases during training in folders corresponding to categories such as _logs/models/psi_\\__2_.\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Hyperparameter Tuning:"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "For the primary models hyperparameter tuning, first a model was trained using images with the same width/height ratio as the original images, which is one here. The hyperparameters of this model were manually tunned and the ones that resulted better performance (i.e. validation dataset accuracy) were used for the subsequent models.\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "WARNING:tensorflow:From /home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/OptimizeAndLog.py:236: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.\n",
- "Instructions for updating:\n",
- "\n",
- "Future major versions of TensorFlow will allow gradients to flow\n",
- "into the labels input on backprop by default.\n",
- "\n",
- "See @{tf.nn.softmax_cross_entropy_with_logits_v2}.\n",
- "\n",
- "epoch 0 ... \n",
- "train_acc: 0.0259 test_acc: 0.0517 best_logits_median: 0.0324\n",
- "\n",
- "epoch 1 ... \n",
- "train_acc: 0.0433 test_acc: 0.0486 best_logits_median: 0.0324\n",
- "\n",
- "epoch 2 ... \n",
- "train_acc: 0.0943 test_acc: 0.1125 best_logits_median: 0.0319\n",
- "\n",
- "epoch 3 ... \n",
- "train_acc: 0.0867 test_acc: 0.1003 best_logits_median: 0.0319\n",
- "\n",
- "epoch 4 ... \n",
- "train_acc: 0.0844 test_acc: 0.1003 best_logits_median: 0.0319\n",
- "\n",
- "epoch 5 ... \n",
- "train_acc: 0.0844 test_acc: 0.1003 best_logits_median: 0.0319\n",
- "\n",
- "epoch 6 ... \n",
- "train_acc: 0.0844 test_acc: 0.1003 best_logits_median: 0.0319\n",
- "\n",
- "epoch 7 ... \n",
- "train_acc: 0.0844 test_acc: 0.1003 best_logits_median: 0.0319\n",
- "\n",
- "epoch 8 ... \n",
- "train_acc: 0.0844 test_acc: 0.1003 best_logits_median: 0.0319\n",
- "\n",
- "epoch 9 ... \n",
- "train_acc: 0.0844 test_acc: 0.1003 best_logits_median: 0.0319\n",
- "\n",
- "epoch 10 ... \n"
- ]
- }
- ],
- "source": [
- "from modules import OptimizeAndLog\n",
- "\n",
- "##\n",
- "OptimizeAndLog.OptimizerLogger. \\\n",
- " train_and_save_logs_three_CNN(filter_size1=17, num_filters1=45, strides_1=[1, 7, 7, 1],\n",
- " use_pooling_1=True, pooling_ksize_1=[1, 4, 4, 1], pooling_strides_1=[1, 4, 4, 1],\n",
- " ##\n",
- " filter_size2=7, num_filters2=17, strides_2=[1, 5, 5, 1],\n",
- " use_pooling_2=True, pooling_ksize_2=[1, 3, 3, 1], pooling_strides_2=[1, 3, 3, 1],\n",
- " ##\n",
- " filter_size3=1, num_filters3=7, strides_3=[1, 1, 1, 1],\n",
- " use_pooling_3=False, pooling_ksize_3=None, pooling_strides_3=None,\n",
- " ##\n",
- " fc_size=86,\n",
- " num_iterations=100,\n",
- " learning_rate=5e-4, momentum=None,\n",
- " X_train=X_train, y_train=y_train,\n",
- " X_test=X_validation, y_test=y_validation,\n",
- " models_log_path='./logs/models/',\n",
- " cls_indices=cls_indices,\n",
- " keep_best_model = True,\n",
- " padding='SAME',\n",
- " device_name=\"/cpu:0\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Feature Engineering:"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "For each primary model, the width/height ratios of the images were changed and for each ratio a model was trained and its saved checkpoint was manually copy-pasted to the _logs/historical_\\__models_ for the final ensemble model."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "X_train_2, X_validation_2, y_train_2, y_validation_2, _ = LoadImg.Dataset.prep_datasets(\n",
- " ver_ratio=0.2, container_path='data/ImageEveryUnit',\n",
- " final_img_width=160, final_img_height=80,\n",
- " color_mode=\"grayscale\", random_state=1911)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "fig = plt.figure(figsize=(15,2.5))\n",
- "imgs_num = np.random.choice(range(len(X_train_2)), 6)\n",
- "\n",
- "for i, img_num in enumerate(imgs_num):\n",
- " ax = fig.add_subplot(1, 6, i + 1, xticks=[], yticks=[])\n",
- " ax.imshow(X_train_2[img_num, :, :, 0], cmap='gray')\n",
- " ax.set_title('category {}_train'.format(np.argmax(y_train_2[img_num])))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
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- "language": "python",
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diff --git a/logs/models/psi-NAN/checkpoint b/logs/models/psi-NAN/checkpoint
deleted file mode 100644
index 72cf729..0000000
--- a/logs/models/psi-NAN/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "best_model_psi-NAN"
diff --git a/logs/models/psi-NAN/hyper_params_psi-NAN.json b/logs/models/psi-NAN/hyper_params_psi-NAN.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi-NAN/hyper_params_psi-NAN.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
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diff --git a/logs/models/psi_0/checkpoint b/logs/models/psi_0/checkpoint
deleted file mode 100644
index 1edff7d..0000000
--- a/logs/models/psi_0/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_0"
diff --git a/logs/models/psi_0/hyper_params_psi_0.json b/logs/models/psi_0/hyper_params_psi_0.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_0/hyper_params_psi_0.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_1/best_model_psi_1.data-00000-of-00001 b/logs/models/psi_1/best_model_psi_1.data-00000-of-00001
deleted file mode 100644
index 2126dfc..0000000
Binary files a/logs/models/psi_1/best_model_psi_1.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_1/best_model_psi_1.index b/logs/models/psi_1/best_model_psi_1.index
deleted file mode 100644
index 22ae3af..0000000
Binary files a/logs/models/psi_1/best_model_psi_1.index and /dev/null differ
diff --git a/logs/models/psi_1/best_model_psi_1.meta b/logs/models/psi_1/best_model_psi_1.meta
deleted file mode 100644
index 17c255e..0000000
Binary files a/logs/models/psi_1/best_model_psi_1.meta and /dev/null differ
diff --git a/logs/models/psi_1/checkpoint b/logs/models/psi_1/checkpoint
deleted file mode 100644
index 79f0dc5..0000000
--- a/logs/models/psi_1/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_1"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "best_model_psi_1"
diff --git a/logs/models/psi_1/hyper_params_psi_1.json b/logs/models/psi_1/hyper_params_psi_1.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_1/hyper_params_psi_1.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_10/best_model_psi_10.data-00000-of-00001 b/logs/models/psi_10/best_model_psi_10.data-00000-of-00001
deleted file mode 100644
index 94ed22a..0000000
Binary files a/logs/models/psi_10/best_model_psi_10.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_10/best_model_psi_10.index b/logs/models/psi_10/best_model_psi_10.index
deleted file mode 100644
index e7ed56f..0000000
Binary files a/logs/models/psi_10/best_model_psi_10.index and /dev/null differ
diff --git a/logs/models/psi_10/best_model_psi_10.meta b/logs/models/psi_10/best_model_psi_10.meta
deleted file mode 100644
index 5685fbb..0000000
Binary files a/logs/models/psi_10/best_model_psi_10.meta and /dev/null differ
diff --git a/logs/models/psi_10/checkpoint b/logs/models/psi_10/checkpoint
deleted file mode 100644
index 88c4e82..0000000
--- a/logs/models/psi_10/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_10"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "best_model_psi_10"
diff --git a/logs/models/psi_10/hyper_params_psi_10.json b/logs/models/psi_10/hyper_params_psi_10.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_10/hyper_params_psi_10.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_10_5/best_model_psi_10_5.data-00000-of-00001 b/logs/models/psi_10_5/best_model_psi_10_5.data-00000-of-00001
deleted file mode 100644
index eec951d..0000000
Binary files a/logs/models/psi_10_5/best_model_psi_10_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_10_5/best_model_psi_10_5.index b/logs/models/psi_10_5/best_model_psi_10_5.index
deleted file mode 100644
index 45f38b4..0000000
Binary files a/logs/models/psi_10_5/best_model_psi_10_5.index and /dev/null differ
diff --git a/logs/models/psi_10_5/best_model_psi_10_5.meta b/logs/models/psi_10_5/best_model_psi_10_5.meta
deleted file mode 100644
index c73cd54..0000000
Binary files a/logs/models/psi_10_5/best_model_psi_10_5.meta and /dev/null differ
diff --git a/logs/models/psi_10_5/checkpoint b/logs/models/psi_10_5/checkpoint
deleted file mode 100644
index 85dec4b..0000000
--- a/logs/models/psi_10_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "best_model_psi_10_5"
diff --git a/logs/models/psi_10_5/hyper_params_psi_10_5.json b/logs/models/psi_10_5/hyper_params_psi_10_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_10_5/hyper_params_psi_10_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_11/best_model_psi_11.data-00000-of-00001 b/logs/models/psi_11/best_model_psi_11.data-00000-of-00001
deleted file mode 100644
index c5f7319..0000000
Binary files a/logs/models/psi_11/best_model_psi_11.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_11/best_model_psi_11.index b/logs/models/psi_11/best_model_psi_11.index
deleted file mode 100644
index 92ac305..0000000
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diff --git a/logs/models/psi_11/best_model_psi_11.meta b/logs/models/psi_11/best_model_psi_11.meta
deleted file mode 100644
index 61abfd8..0000000
Binary files a/logs/models/psi_11/best_model_psi_11.meta and /dev/null differ
diff --git a/logs/models/psi_11/checkpoint b/logs/models/psi_11/checkpoint
deleted file mode 100644
index 36e178e..0000000
--- a/logs/models/psi_11/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_11"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "best_model_psi_11"
diff --git a/logs/models/psi_11/hyper_params_psi_11.json b/logs/models/psi_11/hyper_params_psi_11.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_11/hyper_params_psi_11.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_11_5/best_model_psi_11_5.data-00000-of-00001 b/logs/models/psi_11_5/best_model_psi_11_5.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
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diff --git a/logs/models/psi_11_5/best_model_psi_11_5.index b/logs/models/psi_11_5/best_model_psi_11_5.index
deleted file mode 100644
index 46fc378..0000000
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diff --git a/logs/models/psi_11_5/best_model_psi_11_5.meta b/logs/models/psi_11_5/best_model_psi_11_5.meta
deleted file mode 100644
index 71a351a..0000000
Binary files a/logs/models/psi_11_5/best_model_psi_11_5.meta and /dev/null differ
diff --git a/logs/models/psi_11_5/checkpoint b/logs/models/psi_11_5/checkpoint
deleted file mode 100644
index 79c6410..0000000
--- a/logs/models/psi_11_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "best_model_psi_11_5"
diff --git a/logs/models/psi_11_5/hyper_params_psi_11_5.json b/logs/models/psi_11_5/hyper_params_psi_11_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_11_5/hyper_params_psi_11_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_12/best_model_psi_12.data-00000-of-00001 b/logs/models/psi_12/best_model_psi_12.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_12/best_model_psi_12.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_12/best_model_psi_12.index b/logs/models/psi_12/best_model_psi_12.index
deleted file mode 100644
index 46fc378..0000000
Binary files a/logs/models/psi_12/best_model_psi_12.index and /dev/null differ
diff --git a/logs/models/psi_12/best_model_psi_12.meta b/logs/models/psi_12/best_model_psi_12.meta
deleted file mode 100644
index b03af56..0000000
Binary files a/logs/models/psi_12/best_model_psi_12.meta and /dev/null differ
diff --git a/logs/models/psi_12/checkpoint b/logs/models/psi_12/checkpoint
deleted file mode 100644
index 6d299b2..0000000
--- a/logs/models/psi_12/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_12"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "best_model_psi_12"
diff --git a/logs/models/psi_12/hyper_params_psi_12.json b/logs/models/psi_12/hyper_params_psi_12.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_12/hyper_params_psi_12.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_12_5/best_model_psi_12_5.data-00000-of-00001 b/logs/models/psi_12_5/best_model_psi_12_5.data-00000-of-00001
deleted file mode 100644
index 807a69c..0000000
Binary files a/logs/models/psi_12_5/best_model_psi_12_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_12_5/best_model_psi_12_5.index b/logs/models/psi_12_5/best_model_psi_12_5.index
deleted file mode 100644
index 07f4bda..0000000
Binary files a/logs/models/psi_12_5/best_model_psi_12_5.index and /dev/null differ
diff --git a/logs/models/psi_12_5/best_model_psi_12_5.meta b/logs/models/psi_12_5/best_model_psi_12_5.meta
deleted file mode 100644
index 2e474b2..0000000
Binary files a/logs/models/psi_12_5/best_model_psi_12_5.meta and /dev/null differ
diff --git a/logs/models/psi_12_5/checkpoint b/logs/models/psi_12_5/checkpoint
deleted file mode 100644
index aaf73f2..0000000
--- a/logs/models/psi_12_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_12_5"
diff --git a/logs/models/psi_12_5/hyper_params_psi_12_5.json b/logs/models/psi_12_5/hyper_params_psi_12_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_12_5/hyper_params_psi_12_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_13/best_model_psi_13.data-00000-of-00001 b/logs/models/psi_13/best_model_psi_13.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_13/best_model_psi_13.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_13/best_model_psi_13.index b/logs/models/psi_13/best_model_psi_13.index
deleted file mode 100644
index 46fc378..0000000
Binary files a/logs/models/psi_13/best_model_psi_13.index and /dev/null differ
diff --git a/logs/models/psi_13/best_model_psi_13.meta b/logs/models/psi_13/best_model_psi_13.meta
deleted file mode 100644
index bb89c43..0000000
Binary files a/logs/models/psi_13/best_model_psi_13.meta and /dev/null differ
diff --git a/logs/models/psi_13/checkpoint b/logs/models/psi_13/checkpoint
deleted file mode 100644
index 55ed2a0..0000000
--- a/logs/models/psi_13/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_13"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "best_model_psi_13"
diff --git a/logs/models/psi_13/hyper_params_psi_13.json b/logs/models/psi_13/hyper_params_psi_13.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_13/hyper_params_psi_13.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_13_5/best_model_psi_13_5.data-00000-of-00001 b/logs/models/psi_13_5/best_model_psi_13_5.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_13_5/best_model_psi_13_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_13_5/best_model_psi_13_5.index b/logs/models/psi_13_5/best_model_psi_13_5.index
deleted file mode 100644
index 46fc378..0000000
Binary files a/logs/models/psi_13_5/best_model_psi_13_5.index and /dev/null differ
diff --git a/logs/models/psi_13_5/best_model_psi_13_5.meta b/logs/models/psi_13_5/best_model_psi_13_5.meta
deleted file mode 100644
index 156e2fe..0000000
Binary files a/logs/models/psi_13_5/best_model_psi_13_5.meta and /dev/null differ
diff --git a/logs/models/psi_13_5/checkpoint b/logs/models/psi_13_5/checkpoint
deleted file mode 100644
index 77cddd7..0000000
--- a/logs/models/psi_13_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "best_model_psi_13_5"
diff --git a/logs/models/psi_13_5/hyper_params_psi_13_5.json b/logs/models/psi_13_5/hyper_params_psi_13_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_13_5/hyper_params_psi_13_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_14/best_model_psi_14.data-00000-of-00001 b/logs/models/psi_14/best_model_psi_14.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
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diff --git a/logs/models/psi_14/best_model_psi_14.index b/logs/models/psi_14/best_model_psi_14.index
deleted file mode 100644
index 46fc378..0000000
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diff --git a/logs/models/psi_14/best_model_psi_14.meta b/logs/models/psi_14/best_model_psi_14.meta
deleted file mode 100644
index e8e01d1..0000000
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diff --git a/logs/models/psi_14/checkpoint b/logs/models/psi_14/checkpoint
deleted file mode 100644
index e1f89b8..0000000
--- a/logs/models/psi_14/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "best_model_psi_14"
diff --git a/logs/models/psi_14/hyper_params_psi_14.json b/logs/models/psi_14/hyper_params_psi_14.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_14/hyper_params_psi_14.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_14_5/best_model_psi_14_5.data-00000-of-00001 b/logs/models/psi_14_5/best_model_psi_14_5.data-00000-of-00001
deleted file mode 100644
index c5f7319..0000000
Binary files a/logs/models/psi_14_5/best_model_psi_14_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_14_5/best_model_psi_14_5.index b/logs/models/psi_14_5/best_model_psi_14_5.index
deleted file mode 100644
index 92ac305..0000000
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diff --git a/logs/models/psi_14_5/best_model_psi_14_5.meta b/logs/models/psi_14_5/best_model_psi_14_5.meta
deleted file mode 100644
index abfb54d..0000000
Binary files a/logs/models/psi_14_5/best_model_psi_14_5.meta and /dev/null differ
diff --git a/logs/models/psi_14_5/checkpoint b/logs/models/psi_14_5/checkpoint
deleted file mode 100644
index efe01c3..0000000
--- a/logs/models/psi_14_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "best_model_psi_14_5"
diff --git a/logs/models/psi_14_5/hyper_params_psi_14_5.json b/logs/models/psi_14_5/hyper_params_psi_14_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_14_5/hyper_params_psi_14_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_15/best_model_psi_15.data-00000-of-00001 b/logs/models/psi_15/best_model_psi_15.data-00000-of-00001
deleted file mode 100644
index c5f7319..0000000
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diff --git a/logs/models/psi_15/best_model_psi_15.index b/logs/models/psi_15/best_model_psi_15.index
deleted file mode 100644
index 92ac305..0000000
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diff --git a/logs/models/psi_15/best_model_psi_15.meta b/logs/models/psi_15/best_model_psi_15.meta
deleted file mode 100644
index 0c1dfb6..0000000
Binary files a/logs/models/psi_15/best_model_psi_15.meta and /dev/null differ
diff --git a/logs/models/psi_15/checkpoint b/logs/models/psi_15/checkpoint
deleted file mode 100644
index 7a3b829..0000000
--- a/logs/models/psi_15/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "best_model_psi_15"
diff --git a/logs/models/psi_15/hyper_params_psi_15.json b/logs/models/psi_15/hyper_params_psi_15.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_15/hyper_params_psi_15.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_1_5/best_model_psi_1_5.data-00000-of-00001 b/logs/models/psi_1_5/best_model_psi_1_5.data-00000-of-00001
deleted file mode 100644
index 9c1d70f..0000000
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diff --git a/logs/models/psi_1_5/best_model_psi_1_5.index b/logs/models/psi_1_5/best_model_psi_1_5.index
deleted file mode 100644
index eca0f59..0000000
Binary files a/logs/models/psi_1_5/best_model_psi_1_5.index and /dev/null differ
diff --git a/logs/models/psi_1_5/best_model_psi_1_5.meta b/logs/models/psi_1_5/best_model_psi_1_5.meta
deleted file mode 100644
index 9670103..0000000
Binary files a/logs/models/psi_1_5/best_model_psi_1_5.meta and /dev/null differ
diff --git a/logs/models/psi_1_5/checkpoint b/logs/models/psi_1_5/checkpoint
deleted file mode 100644
index 8c39492..0000000
--- a/logs/models/psi_1_5/checkpoint
+++ /dev/null
@@ -1,16 +0,0 @@
-model_checkpoint_path: "best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "best_model_psi_1_5"
diff --git a/logs/models/psi_1_5/hyper_params_psi_1_5.json b/logs/models/psi_1_5/hyper_params_psi_1_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_1_5/hyper_params_psi_1_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_2/best_model_psi_2.data-00000-of-00001 b/logs/models/psi_2/best_model_psi_2.data-00000-of-00001
deleted file mode 100644
index 6c38e4e..0000000
Binary files a/logs/models/psi_2/best_model_psi_2.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_2/best_model_psi_2.index b/logs/models/psi_2/best_model_psi_2.index
deleted file mode 100644
index da707b5..0000000
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diff --git a/logs/models/psi_2/best_model_psi_2.meta b/logs/models/psi_2/best_model_psi_2.meta
deleted file mode 100644
index d6050d4..0000000
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diff --git a/logs/models/psi_2/checkpoint b/logs/models/psi_2/checkpoint
deleted file mode 100644
index 5f4ec62..0000000
--- a/logs/models/psi_2/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_2"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "best_model_psi_2"
diff --git a/logs/models/psi_2/hyper_params_psi_2.json b/logs/models/psi_2/hyper_params_psi_2.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_2/hyper_params_psi_2.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_2_5/best_model_psi_2_5.data-00000-of-00001 b/logs/models/psi_2_5/best_model_psi_2_5.data-00000-of-00001
deleted file mode 100644
index debcdc9..0000000
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diff --git a/logs/models/psi_2_5/best_model_psi_2_5.index b/logs/models/psi_2_5/best_model_psi_2_5.index
deleted file mode 100644
index bf883de..0000000
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diff --git a/logs/models/psi_2_5/best_model_psi_2_5.meta b/logs/models/psi_2_5/best_model_psi_2_5.meta
deleted file mode 100644
index d4bdf6b..0000000
Binary files a/logs/models/psi_2_5/best_model_psi_2_5.meta and /dev/null differ
diff --git a/logs/models/psi_2_5/checkpoint b/logs/models/psi_2_5/checkpoint
deleted file mode 100644
index be80a7b..0000000
--- a/logs/models/psi_2_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "best_model_psi_2_5"
diff --git a/logs/models/psi_2_5/hyper_params_psi_2_5.json b/logs/models/psi_2_5/hyper_params_psi_2_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_2_5/hyper_params_psi_2_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_3/best_model_psi_3.data-00000-of-00001 b/logs/models/psi_3/best_model_psi_3.data-00000-of-00001
deleted file mode 100644
index 347357e..0000000
Binary files a/logs/models/psi_3/best_model_psi_3.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_3/best_model_psi_3.index b/logs/models/psi_3/best_model_psi_3.index
deleted file mode 100644
index 155e072..0000000
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diff --git a/logs/models/psi_3/best_model_psi_3.meta b/logs/models/psi_3/best_model_psi_3.meta
deleted file mode 100644
index 989bd4a..0000000
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diff --git a/logs/models/psi_3/checkpoint b/logs/models/psi_3/checkpoint
deleted file mode 100644
index 8b7b6ab..0000000
--- a/logs/models/psi_3/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_3"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "best_model_psi_3"
diff --git a/logs/models/psi_3/hyper_params_psi_3.json b/logs/models/psi_3/hyper_params_psi_3.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_3/hyper_params_psi_3.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_3_5/best_model_psi_3_5.data-00000-of-00001 b/logs/models/psi_3_5/best_model_psi_3_5.data-00000-of-00001
deleted file mode 100644
index 94ed22a..0000000
Binary files a/logs/models/psi_3_5/best_model_psi_3_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_3_5/best_model_psi_3_5.index b/logs/models/psi_3_5/best_model_psi_3_5.index
deleted file mode 100644
index e7ed56f..0000000
Binary files a/logs/models/psi_3_5/best_model_psi_3_5.index and /dev/null differ
diff --git a/logs/models/psi_3_5/best_model_psi_3_5.meta b/logs/models/psi_3_5/best_model_psi_3_5.meta
deleted file mode 100644
index 46bd44a..0000000
Binary files a/logs/models/psi_3_5/best_model_psi_3_5.meta and /dev/null differ
diff --git a/logs/models/psi_3_5/checkpoint b/logs/models/psi_3_5/checkpoint
deleted file mode 100644
index e63f29a..0000000
--- a/logs/models/psi_3_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "best_model_psi_3_5"
diff --git a/logs/models/psi_3_5/hyper_params_psi_3_5.json b/logs/models/psi_3_5/hyper_params_psi_3_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_3_5/hyper_params_psi_3_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_4/best_model_psi_4.data-00000-of-00001 b/logs/models/psi_4/best_model_psi_4.data-00000-of-00001
deleted file mode 100644
index 1320279..0000000
Binary files a/logs/models/psi_4/best_model_psi_4.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_4/best_model_psi_4.index b/logs/models/psi_4/best_model_psi_4.index
deleted file mode 100644
index f24952d..0000000
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diff --git a/logs/models/psi_4/best_model_psi_4.meta b/logs/models/psi_4/best_model_psi_4.meta
deleted file mode 100644
index 0e93b88..0000000
Binary files a/logs/models/psi_4/best_model_psi_4.meta and /dev/null differ
diff --git a/logs/models/psi_4/checkpoint b/logs/models/psi_4/checkpoint
deleted file mode 100644
index 02c97fb..0000000
--- a/logs/models/psi_4/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "best_model_psi_4"
diff --git a/logs/models/psi_4/hyper_params_psi_4.json b/logs/models/psi_4/hyper_params_psi_4.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_4/hyper_params_psi_4.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_4_5/best_model_psi_4_5.data-00000-of-00001 b/logs/models/psi_4_5/best_model_psi_4_5.data-00000-of-00001
deleted file mode 100644
index 807a69c..0000000
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diff --git a/logs/models/psi_4_5/best_model_psi_4_5.index b/logs/models/psi_4_5/best_model_psi_4_5.index
deleted file mode 100644
index 07f4bda..0000000
Binary files a/logs/models/psi_4_5/best_model_psi_4_5.index and /dev/null differ
diff --git a/logs/models/psi_4_5/best_model_psi_4_5.meta b/logs/models/psi_4_5/best_model_psi_4_5.meta
deleted file mode 100644
index 08f0668..0000000
Binary files a/logs/models/psi_4_5/best_model_psi_4_5.meta and /dev/null differ
diff --git a/logs/models/psi_4_5/checkpoint b/logs/models/psi_4_5/checkpoint
deleted file mode 100644
index 02ac17f..0000000
--- a/logs/models/psi_4_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "best_model_psi_4_5"
diff --git a/logs/models/psi_4_5/hyper_params_psi_4_5.json b/logs/models/psi_4_5/hyper_params_psi_4_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_4_5/hyper_params_psi_4_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_5/best_model_psi_5.data-00000-of-00001 b/logs/models/psi_5/best_model_psi_5.data-00000-of-00001
deleted file mode 100644
index 2642dc4..0000000
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diff --git a/logs/models/psi_5/best_model_psi_5.index b/logs/models/psi_5/best_model_psi_5.index
deleted file mode 100644
index 3309ded..0000000
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diff --git a/logs/models/psi_5/best_model_psi_5.meta b/logs/models/psi_5/best_model_psi_5.meta
deleted file mode 100644
index 1edc74a..0000000
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diff --git a/logs/models/psi_5/checkpoint b/logs/models/psi_5/checkpoint
deleted file mode 100644
index e85086e..0000000
--- a/logs/models/psi_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "best_model_psi_5"
diff --git a/logs/models/psi_5/hyper_params_psi_5.json b/logs/models/psi_5/hyper_params_psi_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_5/hyper_params_psi_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_5_5/best_model_psi_5_5.data-00000-of-00001 b/logs/models/psi_5_5/best_model_psi_5_5.data-00000-of-00001
deleted file mode 100644
index 347357e..0000000
Binary files a/logs/models/psi_5_5/best_model_psi_5_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_5_5/best_model_psi_5_5.index b/logs/models/psi_5_5/best_model_psi_5_5.index
deleted file mode 100644
index 155e072..0000000
Binary files a/logs/models/psi_5_5/best_model_psi_5_5.index and /dev/null differ
diff --git a/logs/models/psi_5_5/best_model_psi_5_5.meta b/logs/models/psi_5_5/best_model_psi_5_5.meta
deleted file mode 100644
index 39da836..0000000
Binary files a/logs/models/psi_5_5/best_model_psi_5_5.meta and /dev/null differ
diff --git a/logs/models/psi_5_5/checkpoint b/logs/models/psi_5_5/checkpoint
deleted file mode 100644
index 680db61..0000000
--- a/logs/models/psi_5_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_5_5"
diff --git a/logs/models/psi_5_5/hyper_params_psi_5_5.json b/logs/models/psi_5_5/hyper_params_psi_5_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_5_5/hyper_params_psi_5_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_6/best_model_psi_6.data-00000-of-00001 b/logs/models/psi_6/best_model_psi_6.data-00000-of-00001
deleted file mode 100644
index 5a67e0e..0000000
Binary files a/logs/models/psi_6/best_model_psi_6.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_6/best_model_psi_6.index b/logs/models/psi_6/best_model_psi_6.index
deleted file mode 100644
index d2a312e..0000000
Binary files a/logs/models/psi_6/best_model_psi_6.index and /dev/null differ
diff --git a/logs/models/psi_6/best_model_psi_6.meta b/logs/models/psi_6/best_model_psi_6.meta
deleted file mode 100644
index c355e8a..0000000
Binary files a/logs/models/psi_6/best_model_psi_6.meta and /dev/null differ
diff --git a/logs/models/psi_6/checkpoint b/logs/models/psi_6/checkpoint
deleted file mode 100644
index 9c8aa1f..0000000
--- a/logs/models/psi_6/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_6"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_6"
diff --git a/logs/models/psi_6/hyper_params_psi_6.json b/logs/models/psi_6/hyper_params_psi_6.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_6/hyper_params_psi_6.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_6_5/best_model_psi_6_5.data-00000-of-00001 b/logs/models/psi_6_5/best_model_psi_6_5.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_6_5/best_model_psi_6_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_6_5/best_model_psi_6_5.index b/logs/models/psi_6_5/best_model_psi_6_5.index
deleted file mode 100644
index 46fc378..0000000
Binary files a/logs/models/psi_6_5/best_model_psi_6_5.index and /dev/null differ
diff --git a/logs/models/psi_6_5/best_model_psi_6_5.meta b/logs/models/psi_6_5/best_model_psi_6_5.meta
deleted file mode 100644
index 6828b03..0000000
Binary files a/logs/models/psi_6_5/best_model_psi_6_5.meta and /dev/null differ
diff --git a/logs/models/psi_6_5/checkpoint b/logs/models/psi_6_5/checkpoint
deleted file mode 100644
index 10a8ec4..0000000
--- a/logs/models/psi_6_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "best_model_psi_6_5"
diff --git a/logs/models/psi_6_5/hyper_params_psi_6_5.json b/logs/models/psi_6_5/hyper_params_psi_6_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_6_5/hyper_params_psi_6_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_7/best_model_psi_7.data-00000-of-00001 b/logs/models/psi_7/best_model_psi_7.data-00000-of-00001
deleted file mode 100644
index 347357e..0000000
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diff --git a/logs/models/psi_7/best_model_psi_7.index b/logs/models/psi_7/best_model_psi_7.index
deleted file mode 100644
index 155e072..0000000
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diff --git a/logs/models/psi_7/best_model_psi_7.meta b/logs/models/psi_7/best_model_psi_7.meta
deleted file mode 100644
index 361c47f..0000000
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diff --git a/logs/models/psi_7/checkpoint b/logs/models/psi_7/checkpoint
deleted file mode 100644
index 8c2ef92..0000000
--- a/logs/models/psi_7/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_7"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "best_model_psi_7"
diff --git a/logs/models/psi_7/hyper_params_psi_7.json b/logs/models/psi_7/hyper_params_psi_7.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_7/hyper_params_psi_7.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_7_5/best_model_psi_7_5.data-00000-of-00001 b/logs/models/psi_7_5/best_model_psi_7_5.data-00000-of-00001
deleted file mode 100644
index c5af541..0000000
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diff --git a/logs/models/psi_7_5/best_model_psi_7_5.index b/logs/models/psi_7_5/best_model_psi_7_5.index
deleted file mode 100644
index 791e3bc..0000000
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diff --git a/logs/models/psi_7_5/best_model_psi_7_5.meta b/logs/models/psi_7_5/best_model_psi_7_5.meta
deleted file mode 100644
index f8f68e1..0000000
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diff --git a/logs/models/psi_7_5/checkpoint b/logs/models/psi_7_5/checkpoint
deleted file mode 100644
index 206d0c7..0000000
--- a/logs/models/psi_7_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "best_model_psi_7_5"
diff --git a/logs/models/psi_7_5/hyper_params_psi_7_5.json b/logs/models/psi_7_5/hyper_params_psi_7_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_7_5/hyper_params_psi_7_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_8/best_model_psi_8.data-00000-of-00001 b/logs/models/psi_8/best_model_psi_8.data-00000-of-00001
deleted file mode 100644
index acd84c8..0000000
Binary files a/logs/models/psi_8/best_model_psi_8.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_8/best_model_psi_8.index b/logs/models/psi_8/best_model_psi_8.index
deleted file mode 100644
index 1f6e7ba..0000000
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diff --git a/logs/models/psi_8/best_model_psi_8.meta b/logs/models/psi_8/best_model_psi_8.meta
deleted file mode 100644
index 98e645d..0000000
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diff --git a/logs/models/psi_8/checkpoint b/logs/models/psi_8/checkpoint
deleted file mode 100644
index 3f2a75e..0000000
--- a/logs/models/psi_8/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_8"
diff --git a/logs/models/psi_8/hyper_params_psi_8.json b/logs/models/psi_8/hyper_params_psi_8.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_8/hyper_params_psi_8.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_8_5/best_model_psi_8_5.data-00000-of-00001 b/logs/models/psi_8_5/best_model_psi_8_5.data-00000-of-00001
deleted file mode 100644
index 9385859..0000000
Binary files a/logs/models/psi_8_5/best_model_psi_8_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_8_5/best_model_psi_8_5.index b/logs/models/psi_8_5/best_model_psi_8_5.index
deleted file mode 100644
index 2ec02ea..0000000
Binary files a/logs/models/psi_8_5/best_model_psi_8_5.index and /dev/null differ
diff --git a/logs/models/psi_8_5/best_model_psi_8_5.meta b/logs/models/psi_8_5/best_model_psi_8_5.meta
deleted file mode 100644
index 7b6e760..0000000
Binary files a/logs/models/psi_8_5/best_model_psi_8_5.meta and /dev/null differ
diff --git a/logs/models/psi_8_5/checkpoint b/logs/models/psi_8_5/checkpoint
deleted file mode 100644
index 8104558..0000000
--- a/logs/models/psi_8_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "best_model_psi_8_5"
diff --git a/logs/models/psi_8_5/hyper_params_psi_8_5.json b/logs/models/psi_8_5/hyper_params_psi_8_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_8_5/hyper_params_psi_8_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_9/best_model_psi_9.data-00000-of-00001 b/logs/models/psi_9/best_model_psi_9.data-00000-of-00001
deleted file mode 100644
index dd05062..0000000
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diff --git a/logs/models/psi_9/best_model_psi_9.index b/logs/models/psi_9/best_model_psi_9.index
deleted file mode 100644
index dee3901..0000000
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diff --git a/logs/models/psi_9/best_model_psi_9.meta b/logs/models/psi_9/best_model_psi_9.meta
deleted file mode 100644
index 82c1331..0000000
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diff --git a/logs/models/psi_9/checkpoint b/logs/models/psi_9/checkpoint
deleted file mode 100644
index b18da7b..0000000
--- a/logs/models/psi_9/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_9"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "best_model_psi_9"
diff --git a/logs/models/psi_9/hyper_params_psi_9.json b/logs/models/psi_9/hyper_params_psi_9.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_9/hyper_params_psi_9.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_9_5/best_model_psi_9_5.data-00000-of-00001 b/logs/models/psi_9_5/best_model_psi_9_5.data-00000-of-00001
deleted file mode 100644
index 6c38e4e..0000000
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diff --git a/logs/models/psi_9_5/best_model_psi_9_5.index b/logs/models/psi_9_5/best_model_psi_9_5.index
deleted file mode 100644
index da707b5..0000000
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diff --git a/logs/models/psi_9_5/best_model_psi_9_5.meta b/logs/models/psi_9_5/best_model_psi_9_5.meta
deleted file mode 100644
index 8009941..0000000
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diff --git a/logs/models/psi_9_5/checkpoint b/logs/models/psi_9_5/checkpoint
deleted file mode 100644
index 5a0292b..0000000
--- a/logs/models/psi_9_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "best_model_psi_9_5"
diff --git a/logs/models/psi_9_5/hyper_params_psi_9_5.json b/logs/models/psi_9_5/hyper_params_psi_9_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_9_5/hyper_params_psi_9_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi-NAN/best_model_psi-NAN.data-00000-of-00001 b/logs/models_ensemble/psi-NAN/best_model_psi-NAN.data-00000-of-00001
deleted file mode 100644
index 7ff134c..0000000
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diff --git a/logs/models_ensemble/psi-NAN/best_model_psi-NAN.index b/logs/models_ensemble/psi-NAN/best_model_psi-NAN.index
deleted file mode 100644
index 9049170..0000000
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diff --git a/logs/models_ensemble/psi-NAN/best_model_psi-NAN.meta b/logs/models_ensemble/psi-NAN/best_model_psi-NAN.meta
deleted file mode 100644
index 7d53d2f..0000000
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diff --git a/logs/models_ensemble/psi-NAN/checkpoint b/logs/models_ensemble/psi-NAN/checkpoint
deleted file mode 100644
index 9e183c6..0000000
--- a/logs/models_ensemble/psi-NAN/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "best_model_psi-NAN"
diff --git a/logs/models_ensemble/psi-NAN/hyper_params_psi-NAN.json b/logs/models_ensemble/psi-NAN/hyper_params_psi-NAN.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi-NAN/hyper_params_psi-NAN.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_0/best_model_psi_0.data-00000-of-00001 b/logs/models_ensemble/psi_0/best_model_psi_0.data-00000-of-00001
deleted file mode 100644
index 63fa39f..0000000
Binary files a/logs/models_ensemble/psi_0/best_model_psi_0.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_0/best_model_psi_0.index b/logs/models_ensemble/psi_0/best_model_psi_0.index
deleted file mode 100644
index 7940d43..0000000
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diff --git a/logs/models_ensemble/psi_0/best_model_psi_0.meta b/logs/models_ensemble/psi_0/best_model_psi_0.meta
deleted file mode 100644
index 19e7da3..0000000
Binary files a/logs/models_ensemble/psi_0/best_model_psi_0.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_0/checkpoint b/logs/models_ensemble/psi_0/checkpoint
deleted file mode 100644
index 9bd0ad9..0000000
--- a/logs/models_ensemble/psi_0/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_0"
diff --git a/logs/models_ensemble/psi_0/hyper_params_psi_0.json b/logs/models_ensemble/psi_0/hyper_params_psi_0.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_0/hyper_params_psi_0.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_1/best_model_psi_1.data-00000-of-00001 b/logs/models_ensemble/psi_1/best_model_psi_1.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
Binary files a/logs/models_ensemble/psi_1/best_model_psi_1.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_1/best_model_psi_1.index b/logs/models_ensemble/psi_1/best_model_psi_1.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_1/best_model_psi_1.meta b/logs/models_ensemble/psi_1/best_model_psi_1.meta
deleted file mode 100644
index 296c5be..0000000
Binary files a/logs/models_ensemble/psi_1/best_model_psi_1.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_1/checkpoint b/logs/models_ensemble/psi_1/checkpoint
deleted file mode 100644
index 26afb89..0000000
--- a/logs/models_ensemble/psi_1/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_1"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "best_model_psi_1"
diff --git a/logs/models_ensemble/psi_1/hyper_params_psi_1.json b/logs/models_ensemble/psi_1/hyper_params_psi_1.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_1/hyper_params_psi_1.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_10/best_model_psi_10.data-00000-of-00001 b/logs/models_ensemble/psi_10/best_model_psi_10.data-00000-of-00001
deleted file mode 100644
index 38a5ea0..0000000
Binary files a/logs/models_ensemble/psi_10/best_model_psi_10.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_10/best_model_psi_10.index b/logs/models_ensemble/psi_10/best_model_psi_10.index
deleted file mode 100644
index ebe0d59..0000000
Binary files a/logs/models_ensemble/psi_10/best_model_psi_10.index and /dev/null differ
diff --git a/logs/models_ensemble/psi_10/best_model_psi_10.meta b/logs/models_ensemble/psi_10/best_model_psi_10.meta
deleted file mode 100644
index cce597b..0000000
Binary files a/logs/models_ensemble/psi_10/best_model_psi_10.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_10/checkpoint b/logs/models_ensemble/psi_10/checkpoint
deleted file mode 100644
index 691f777..0000000
--- a/logs/models_ensemble/psi_10/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_10"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "best_model_psi_10"
diff --git a/logs/models_ensemble/psi_10/hyper_params_psi_10.json b/logs/models_ensemble/psi_10/hyper_params_psi_10.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_10/hyper_params_psi_10.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.data-00000-of-00001 b/logs/models_ensemble/psi_10_5/best_model_psi_10_5.data-00000-of-00001
deleted file mode 100644
index 9aaca8a..0000000
Binary files a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.index b/logs/models_ensemble/psi_10_5/best_model_psi_10_5.index
deleted file mode 100644
index c9f02b2..0000000
Binary files a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.index and /dev/null differ
diff --git a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.meta b/logs/models_ensemble/psi_10_5/best_model_psi_10_5.meta
deleted file mode 100644
index 4ab6bc0..0000000
Binary files a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_10_5/checkpoint b/logs/models_ensemble/psi_10_5/checkpoint
deleted file mode 100644
index c6b134c..0000000
--- a/logs/models_ensemble/psi_10_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "best_model_psi_10_5"
diff --git a/logs/models_ensemble/psi_10_5/hyper_params_psi_10_5.json b/logs/models_ensemble/psi_10_5/hyper_params_psi_10_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_10_5/hyper_params_psi_10_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_11/best_model_psi_11.data-00000-of-00001 b/logs/models_ensemble/psi_11/best_model_psi_11.data-00000-of-00001
deleted file mode 100644
index da14e33..0000000
Binary files a/logs/models_ensemble/psi_11/best_model_psi_11.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_11/best_model_psi_11.index b/logs/models_ensemble/psi_11/best_model_psi_11.index
deleted file mode 100644
index f6f69f4..0000000
Binary files a/logs/models_ensemble/psi_11/best_model_psi_11.index and /dev/null differ
diff --git a/logs/models_ensemble/psi_11/best_model_psi_11.meta b/logs/models_ensemble/psi_11/best_model_psi_11.meta
deleted file mode 100644
index d46e08d..0000000
Binary files a/logs/models_ensemble/psi_11/best_model_psi_11.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_11/checkpoint b/logs/models_ensemble/psi_11/checkpoint
deleted file mode 100644
index 16551a4..0000000
--- a/logs/models_ensemble/psi_11/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_11"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "best_model_psi_11"
diff --git a/logs/models_ensemble/psi_11/hyper_params_psi_11.json b/logs/models_ensemble/psi_11/hyper_params_psi_11.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_11/hyper_params_psi_11.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.data-00000-of-00001 b/logs/models_ensemble/psi_11_5/best_model_psi_11_5.data-00000-of-00001
deleted file mode 100644
index cc1158e..0000000
Binary files a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.index b/logs/models_ensemble/psi_11_5/best_model_psi_11_5.index
deleted file mode 100644
index 0b182e1..0000000
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diff --git a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.meta b/logs/models_ensemble/psi_11_5/best_model_psi_11_5.meta
deleted file mode 100644
index 05f7581..0000000
Binary files a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_11_5/checkpoint b/logs/models_ensemble/psi_11_5/checkpoint
deleted file mode 100644
index 862a11e..0000000
--- a/logs/models_ensemble/psi_11_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "best_model_psi_11_5"
diff --git a/logs/models_ensemble/psi_11_5/hyper_params_psi_11_5.json b/logs/models_ensemble/psi_11_5/hyper_params_psi_11_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_11_5/hyper_params_psi_11_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_12/best_model_psi_12.data-00000-of-00001 b/logs/models_ensemble/psi_12/best_model_psi_12.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
Binary files a/logs/models_ensemble/psi_12/best_model_psi_12.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_12/best_model_psi_12.index b/logs/models_ensemble/psi_12/best_model_psi_12.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_12/best_model_psi_12.meta b/logs/models_ensemble/psi_12/best_model_psi_12.meta
deleted file mode 100644
index d47d806..0000000
Binary files a/logs/models_ensemble/psi_12/best_model_psi_12.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_12/checkpoint b/logs/models_ensemble/psi_12/checkpoint
deleted file mode 100644
index 450959a..0000000
--- a/logs/models_ensemble/psi_12/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "best_model_psi_12"
diff --git a/logs/models_ensemble/psi_12/hyper_params_psi_12.json b/logs/models_ensemble/psi_12/hyper_params_psi_12.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_12/hyper_params_psi_12.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.data-00000-of-00001 b/logs/models_ensemble/psi_12_5/best_model_psi_12_5.data-00000-of-00001
deleted file mode 100644
index 246e06e..0000000
Binary files a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.index b/logs/models_ensemble/psi_12_5/best_model_psi_12_5.index
deleted file mode 100644
index 37f72aa..0000000
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diff --git a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.meta b/logs/models_ensemble/psi_12_5/best_model_psi_12_5.meta
deleted file mode 100644
index b387415..0000000
Binary files a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_12_5/checkpoint b/logs/models_ensemble/psi_12_5/checkpoint
deleted file mode 100644
index 85a4085..0000000
--- a/logs/models_ensemble/psi_12_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "best_model_psi_12_5"
diff --git a/logs/models_ensemble/psi_12_5/hyper_params_psi_12_5.json b/logs/models_ensemble/psi_12_5/hyper_params_psi_12_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_12_5/hyper_params_psi_12_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_13/best_model_psi_13.data-00000-of-00001 b/logs/models_ensemble/psi_13/best_model_psi_13.data-00000-of-00001
deleted file mode 100644
index 7dfc9d3..0000000
Binary files a/logs/models_ensemble/psi_13/best_model_psi_13.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_13/best_model_psi_13.index b/logs/models_ensemble/psi_13/best_model_psi_13.index
deleted file mode 100644
index 9f00019..0000000
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diff --git a/logs/models_ensemble/psi_13/best_model_psi_13.meta b/logs/models_ensemble/psi_13/best_model_psi_13.meta
deleted file mode 100644
index ed8575f..0000000
Binary files a/logs/models_ensemble/psi_13/best_model_psi_13.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_13/checkpoint b/logs/models_ensemble/psi_13/checkpoint
deleted file mode 100644
index 919c875..0000000
--- a/logs/models_ensemble/psi_13/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "best_model_psi_13"
diff --git a/logs/models_ensemble/psi_13/hyper_params_psi_13.json b/logs/models_ensemble/psi_13/hyper_params_psi_13.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_13/hyper_params_psi_13.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_13_5/best_model_psi_13_5.data-00000-of-00001 b/logs/models_ensemble/psi_13_5/best_model_psi_13_5.data-00000-of-00001
deleted file mode 100644
index 83d8909..0000000
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diff --git a/logs/models_ensemble/psi_13_5/best_model_psi_13_5.index b/logs/models_ensemble/psi_13_5/best_model_psi_13_5.index
deleted file mode 100644
index 8abdfe0..0000000
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diff --git a/logs/models_ensemble/psi_13_5/best_model_psi_13_5.meta b/logs/models_ensemble/psi_13_5/best_model_psi_13_5.meta
deleted file mode 100644
index 4b1d663..0000000
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diff --git a/logs/models_ensemble/psi_13_5/checkpoint b/logs/models_ensemble/psi_13_5/checkpoint
deleted file mode 100644
index 8c3882d..0000000
--- a/logs/models_ensemble/psi_13_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "best_model_psi_13_5"
diff --git a/logs/models_ensemble/psi_13_5/hyper_params_psi_13_5.json b/logs/models_ensemble/psi_13_5/hyper_params_psi_13_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_13_5/hyper_params_psi_13_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_14/best_model_psi_14.data-00000-of-00001 b/logs/models_ensemble/psi_14/best_model_psi_14.data-00000-of-00001
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index 3e11730..0000000
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diff --git a/logs/models_ensemble/psi_14/best_model_psi_14.index b/logs/models_ensemble/psi_14/best_model_psi_14.index
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index b51214b..0000000
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diff --git a/logs/models_ensemble/psi_14/best_model_psi_14.meta b/logs/models_ensemble/psi_14/best_model_psi_14.meta
deleted file mode 100644
index 678fcb4..0000000
Binary files a/logs/models_ensemble/psi_14/best_model_psi_14.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_14/checkpoint b/logs/models_ensemble/psi_14/checkpoint
deleted file mode 100644
index f8ba349..0000000
--- a/logs/models_ensemble/psi_14/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_14"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "best_model_psi_14"
diff --git a/logs/models_ensemble/psi_14/hyper_params_psi_14.json b/logs/models_ensemble/psi_14/hyper_params_psi_14.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_14/hyper_params_psi_14.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_14_5/best_model_psi_14_5.data-00000-of-00001 b/logs/models_ensemble/psi_14_5/best_model_psi_14_5.data-00000-of-00001
deleted file mode 100644
index 7ff134c..0000000
Binary files a/logs/models_ensemble/psi_14_5/best_model_psi_14_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_14_5/best_model_psi_14_5.index b/logs/models_ensemble/psi_14_5/best_model_psi_14_5.index
deleted file mode 100644
index 9049170..0000000
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diff --git a/logs/models_ensemble/psi_14_5/best_model_psi_14_5.meta b/logs/models_ensemble/psi_14_5/best_model_psi_14_5.meta
deleted file mode 100644
index ae377e3..0000000
Binary files a/logs/models_ensemble/psi_14_5/best_model_psi_14_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_14_5/checkpoint b/logs/models_ensemble/psi_14_5/checkpoint
deleted file mode 100644
index 111570d..0000000
--- a/logs/models_ensemble/psi_14_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "best_model_psi_14_5"
diff --git a/logs/models_ensemble/psi_14_5/hyper_params_psi_14_5.json b/logs/models_ensemble/psi_14_5/hyper_params_psi_14_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_14_5/hyper_params_psi_14_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_15/best_model_psi_15.data-00000-of-00001 b/logs/models_ensemble/psi_15/best_model_psi_15.data-00000-of-00001
deleted file mode 100644
index 7ff134c..0000000
Binary files a/logs/models_ensemble/psi_15/best_model_psi_15.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_15/best_model_psi_15.index b/logs/models_ensemble/psi_15/best_model_psi_15.index
deleted file mode 100644
index 9049170..0000000
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diff --git a/logs/models_ensemble/psi_15/best_model_psi_15.meta b/logs/models_ensemble/psi_15/best_model_psi_15.meta
deleted file mode 100644
index 9030f8d..0000000
Binary files a/logs/models_ensemble/psi_15/best_model_psi_15.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_15/checkpoint b/logs/models_ensemble/psi_15/checkpoint
deleted file mode 100644
index 5cc2467..0000000
--- a/logs/models_ensemble/psi_15/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_15"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "best_model_psi_15"
diff --git a/logs/models_ensemble/psi_15/hyper_params_psi_15.json b/logs/models_ensemble/psi_15/hyper_params_psi_15.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_15/hyper_params_psi_15.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.data-00000-of-00001 b/logs/models_ensemble/psi_1_5/best_model_psi_1_5.data-00000-of-00001
deleted file mode 100644
index 3e11730..0000000
Binary files a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.index b/logs/models_ensemble/psi_1_5/best_model_psi_1_5.index
deleted file mode 100644
index b51214b..0000000
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diff --git a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.meta b/logs/models_ensemble/psi_1_5/best_model_psi_1_5.meta
deleted file mode 100644
index 14f4a1f..0000000
Binary files a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_1_5/checkpoint b/logs/models_ensemble/psi_1_5/checkpoint
deleted file mode 100644
index 9420406..0000000
--- a/logs/models_ensemble/psi_1_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "best_model_psi_1_5"
diff --git a/logs/models_ensemble/psi_1_5/hyper_params_psi_1_5.json b/logs/models_ensemble/psi_1_5/hyper_params_psi_1_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_1_5/hyper_params_psi_1_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_2/best_model_psi_2.data-00000-of-00001 b/logs/models_ensemble/psi_2/best_model_psi_2.data-00000-of-00001
deleted file mode 100644
index 63fa39f..0000000
Binary files a/logs/models_ensemble/psi_2/best_model_psi_2.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_2/best_model_psi_2.index b/logs/models_ensemble/psi_2/best_model_psi_2.index
deleted file mode 100644
index 7940d43..0000000
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diff --git a/logs/models_ensemble/psi_2/best_model_psi_2.meta b/logs/models_ensemble/psi_2/best_model_psi_2.meta
deleted file mode 100644
index 1a5a083..0000000
Binary files a/logs/models_ensemble/psi_2/best_model_psi_2.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_2/checkpoint b/logs/models_ensemble/psi_2/checkpoint
deleted file mode 100644
index 764b42a..0000000
--- a/logs/models_ensemble/psi_2/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_2"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "best_model_psi_2"
diff --git a/logs/models_ensemble/psi_2/hyper_params_psi_2.json b/logs/models_ensemble/psi_2/hyper_params_psi_2.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_2/hyper_params_psi_2.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.data-00000-of-00001 b/logs/models_ensemble/psi_2_5/best_model_psi_2_5.data-00000-of-00001
deleted file mode 100644
index 7ff134c..0000000
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diff --git a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.index b/logs/models_ensemble/psi_2_5/best_model_psi_2_5.index
deleted file mode 100644
index 9049170..0000000
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diff --git a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.meta b/logs/models_ensemble/psi_2_5/best_model_psi_2_5.meta
deleted file mode 100644
index 9f031d6..0000000
Binary files a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_2_5/checkpoint b/logs/models_ensemble/psi_2_5/checkpoint
deleted file mode 100644
index a66b641..0000000
--- a/logs/models_ensemble/psi_2_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "best_model_psi_2_5"
diff --git a/logs/models_ensemble/psi_2_5/hyper_params_psi_2_5.json b/logs/models_ensemble/psi_2_5/hyper_params_psi_2_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_2_5/hyper_params_psi_2_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_3/best_model_psi_3.data-00000-of-00001 b/logs/models_ensemble/psi_3/best_model_psi_3.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
Binary files a/logs/models_ensemble/psi_3/best_model_psi_3.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_3/best_model_psi_3.index b/logs/models_ensemble/psi_3/best_model_psi_3.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_3/best_model_psi_3.meta b/logs/models_ensemble/psi_3/best_model_psi_3.meta
deleted file mode 100644
index cce7400..0000000
Binary files a/logs/models_ensemble/psi_3/best_model_psi_3.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_3/checkpoint b/logs/models_ensemble/psi_3/checkpoint
deleted file mode 100644
index 8ba06e2..0000000
--- a/logs/models_ensemble/psi_3/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_3"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "best_model_psi_3"
diff --git a/logs/models_ensemble/psi_3/hyper_params_psi_3.json b/logs/models_ensemble/psi_3/hyper_params_psi_3.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_3/hyper_params_psi_3.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_3_5/best_model_psi_3_5.data-00000-of-00001 b/logs/models_ensemble/psi_3_5/best_model_psi_3_5.data-00000-of-00001
deleted file mode 100644
index 6657699..0000000
Binary files a/logs/models_ensemble/psi_3_5/best_model_psi_3_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_3_5/best_model_psi_3_5.index b/logs/models_ensemble/psi_3_5/best_model_psi_3_5.index
deleted file mode 100644
index cf077e3..0000000
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diff --git a/logs/models_ensemble/psi_3_5/best_model_psi_3_5.meta b/logs/models_ensemble/psi_3_5/best_model_psi_3_5.meta
deleted file mode 100644
index 968dec4..0000000
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diff --git a/logs/models_ensemble/psi_3_5/checkpoint b/logs/models_ensemble/psi_3_5/checkpoint
deleted file mode 100644
index aa461ba..0000000
--- a/logs/models_ensemble/psi_3_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "best_model_psi_3_5"
diff --git a/logs/models_ensemble/psi_3_5/hyper_params_psi_3_5.json b/logs/models_ensemble/psi_3_5/hyper_params_psi_3_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_3_5/hyper_params_psi_3_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_4/best_model_psi_4.data-00000-of-00001 b/logs/models_ensemble/psi_4/best_model_psi_4.data-00000-of-00001
deleted file mode 100644
index 9aaca8a..0000000
Binary files a/logs/models_ensemble/psi_4/best_model_psi_4.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_4/best_model_psi_4.index b/logs/models_ensemble/psi_4/best_model_psi_4.index
deleted file mode 100644
index c9f02b2..0000000
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diff --git a/logs/models_ensemble/psi_4/best_model_psi_4.meta b/logs/models_ensemble/psi_4/best_model_psi_4.meta
deleted file mode 100644
index 144a689..0000000
Binary files a/logs/models_ensemble/psi_4/best_model_psi_4.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_4/checkpoint b/logs/models_ensemble/psi_4/checkpoint
deleted file mode 100644
index f93e6c1..0000000
--- a/logs/models_ensemble/psi_4/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_4"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "best_model_psi_4"
diff --git a/logs/models_ensemble/psi_4/hyper_params_psi_4.json b/logs/models_ensemble/psi_4/hyper_params_psi_4.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_4/hyper_params_psi_4.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.data-00000-of-00001 b/logs/models_ensemble/psi_4_5/best_model_psi_4_5.data-00000-of-00001
deleted file mode 100644
index ad56b60..0000000
Binary files a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.index b/logs/models_ensemble/psi_4_5/best_model_psi_4_5.index
deleted file mode 100644
index ef49308..0000000
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diff --git a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.meta b/logs/models_ensemble/psi_4_5/best_model_psi_4_5.meta
deleted file mode 100644
index 5f3cc19..0000000
Binary files a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_4_5/checkpoint b/logs/models_ensemble/psi_4_5/checkpoint
deleted file mode 100644
index 0232826..0000000
--- a/logs/models_ensemble/psi_4_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "best_model_psi_4_5"
diff --git a/logs/models_ensemble/psi_4_5/hyper_params_psi_4_5.json b/logs/models_ensemble/psi_4_5/hyper_params_psi_4_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_4_5/hyper_params_psi_4_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_5/best_model_psi_5.data-00000-of-00001 b/logs/models_ensemble/psi_5/best_model_psi_5.data-00000-of-00001
deleted file mode 100644
index 3e11730..0000000
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diff --git a/logs/models_ensemble/psi_5/best_model_psi_5.index b/logs/models_ensemble/psi_5/best_model_psi_5.index
deleted file mode 100644
index b51214b..0000000
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diff --git a/logs/models_ensemble/psi_5/best_model_psi_5.meta b/logs/models_ensemble/psi_5/best_model_psi_5.meta
deleted file mode 100644
index 3383595..0000000
Binary files a/logs/models_ensemble/psi_5/best_model_psi_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_5/checkpoint b/logs/models_ensemble/psi_5/checkpoint
deleted file mode 100644
index 3ddf378..0000000
--- a/logs/models_ensemble/psi_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "best_model_psi_5"
diff --git a/logs/models_ensemble/psi_5/hyper_params_psi_5.json b/logs/models_ensemble/psi_5/hyper_params_psi_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_5/hyper_params_psi_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_5_5/best_model_psi_5_5.data-00000-of-00001 b/logs/models_ensemble/psi_5_5/best_model_psi_5_5.data-00000-of-00001
deleted file mode 100644
index 40afdab..0000000
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diff --git a/logs/models_ensemble/psi_5_5/best_model_psi_5_5.index b/logs/models_ensemble/psi_5_5/best_model_psi_5_5.index
deleted file mode 100644
index 1771939..0000000
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diff --git a/logs/models_ensemble/psi_5_5/best_model_psi_5_5.meta b/logs/models_ensemble/psi_5_5/best_model_psi_5_5.meta
deleted file mode 100644
index 514e6f0..0000000
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diff --git a/logs/models_ensemble/psi_5_5/checkpoint b/logs/models_ensemble/psi_5_5/checkpoint
deleted file mode 100644
index 2775a1e..0000000
--- a/logs/models_ensemble/psi_5_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_5_5"
diff --git a/logs/models_ensemble/psi_5_5/hyper_params_psi_5_5.json b/logs/models_ensemble/psi_5_5/hyper_params_psi_5_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_5_5/hyper_params_psi_5_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_6/best_model_psi_6.data-00000-of-00001 b/logs/models_ensemble/psi_6/best_model_psi_6.data-00000-of-00001
deleted file mode 100644
index 78b4595..0000000
Binary files a/logs/models_ensemble/psi_6/best_model_psi_6.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_6/best_model_psi_6.index b/logs/models_ensemble/psi_6/best_model_psi_6.index
deleted file mode 100644
index d245728..0000000
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diff --git a/logs/models_ensemble/psi_6/best_model_psi_6.meta b/logs/models_ensemble/psi_6/best_model_psi_6.meta
deleted file mode 100644
index 690057d..0000000
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diff --git a/logs/models_ensemble/psi_6/checkpoint b/logs/models_ensemble/psi_6/checkpoint
deleted file mode 100644
index 6903078..0000000
--- a/logs/models_ensemble/psi_6/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_6"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "best_model_psi_6"
diff --git a/logs/models_ensemble/psi_6/hyper_params_psi_6.json b/logs/models_ensemble/psi_6/hyper_params_psi_6.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_6/hyper_params_psi_6.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_6_5/best_model_psi_6_5.data-00000-of-00001 b/logs/models_ensemble/psi_6_5/best_model_psi_6_5.data-00000-of-00001
deleted file mode 100644
index fb49107..0000000
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diff --git a/logs/models_ensemble/psi_6_5/best_model_psi_6_5.index b/logs/models_ensemble/psi_6_5/best_model_psi_6_5.index
deleted file mode 100644
index cdd8368..0000000
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diff --git a/logs/models_ensemble/psi_6_5/best_model_psi_6_5.meta b/logs/models_ensemble/psi_6_5/best_model_psi_6_5.meta
deleted file mode 100644
index a97137b..0000000
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diff --git a/logs/models_ensemble/psi_6_5/checkpoint b/logs/models_ensemble/psi_6_5/checkpoint
deleted file mode 100644
index eedcfee..0000000
--- a/logs/models_ensemble/psi_6_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_6_5"
diff --git a/logs/models_ensemble/psi_6_5/hyper_params_psi_6_5.json b/logs/models_ensemble/psi_6_5/hyper_params_psi_6_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_6_5/hyper_params_psi_6_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_7/best_model_psi_7.data-00000-of-00001 b/logs/models_ensemble/psi_7/best_model_psi_7.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
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diff --git a/logs/models_ensemble/psi_7/best_model_psi_7.index b/logs/models_ensemble/psi_7/best_model_psi_7.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_7/best_model_psi_7.meta b/logs/models_ensemble/psi_7/best_model_psi_7.meta
deleted file mode 100644
index c700e61..0000000
Binary files a/logs/models_ensemble/psi_7/best_model_psi_7.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_7/checkpoint b/logs/models_ensemble/psi_7/checkpoint
deleted file mode 100644
index 21eb900..0000000
--- a/logs/models_ensemble/psi_7/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_7"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_7"
diff --git a/logs/models_ensemble/psi_7/hyper_params_psi_7.json b/logs/models_ensemble/psi_7/hyper_params_psi_7.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_7/hyper_params_psi_7.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_7_5/best_model_psi_7_5.data-00000-of-00001 b/logs/models_ensemble/psi_7_5/best_model_psi_7_5.data-00000-of-00001
deleted file mode 100644
index da14e33..0000000
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diff --git a/logs/models_ensemble/psi_7_5/best_model_psi_7_5.index b/logs/models_ensemble/psi_7_5/best_model_psi_7_5.index
deleted file mode 100644
index f6f69f4..0000000
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diff --git a/logs/models_ensemble/psi_7_5/best_model_psi_7_5.meta b/logs/models_ensemble/psi_7_5/best_model_psi_7_5.meta
deleted file mode 100644
index eca8975..0000000
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diff --git a/logs/models_ensemble/psi_7_5/checkpoint b/logs/models_ensemble/psi_7_5/checkpoint
deleted file mode 100644
index b237b83..0000000
--- a/logs/models_ensemble/psi_7_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "best_model_psi_7_5"
diff --git a/logs/models_ensemble/psi_7_5/hyper_params_psi_7_5.json b/logs/models_ensemble/psi_7_5/hyper_params_psi_7_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_7_5/hyper_params_psi_7_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_8/best_model_psi_8.data-00000-of-00001 b/logs/models_ensemble/psi_8/best_model_psi_8.data-00000-of-00001
deleted file mode 100644
index 02e6414..0000000
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diff --git a/logs/models_ensemble/psi_8/best_model_psi_8.index b/logs/models_ensemble/psi_8/best_model_psi_8.index
deleted file mode 100644
index 8a36ce3..0000000
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diff --git a/logs/models_ensemble/psi_8/best_model_psi_8.meta b/logs/models_ensemble/psi_8/best_model_psi_8.meta
deleted file mode 100644
index 4ed963f..0000000
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diff --git a/logs/models_ensemble/psi_8/checkpoint b/logs/models_ensemble/psi_8/checkpoint
deleted file mode 100644
index 0cddb16..0000000
--- a/logs/models_ensemble/psi_8/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "best_model_psi_8"
diff --git a/logs/models_ensemble/psi_8/hyper_params_psi_8.json b/logs/models_ensemble/psi_8/hyper_params_psi_8.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_8/hyper_params_psi_8.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_8_5/best_model_psi_8_5.data-00000-of-00001 b/logs/models_ensemble/psi_8_5/best_model_psi_8_5.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
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diff --git a/logs/models_ensemble/psi_8_5/best_model_psi_8_5.index b/logs/models_ensemble/psi_8_5/best_model_psi_8_5.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_8_5/best_model_psi_8_5.meta b/logs/models_ensemble/psi_8_5/best_model_psi_8_5.meta
deleted file mode 100644
index 19273fe..0000000
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diff --git a/logs/models_ensemble/psi_8_5/checkpoint b/logs/models_ensemble/psi_8_5/checkpoint
deleted file mode 100644
index d4984e8..0000000
--- a/logs/models_ensemble/psi_8_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_8_5"
diff --git a/logs/models_ensemble/psi_8_5/hyper_params_psi_8_5.json b/logs/models_ensemble/psi_8_5/hyper_params_psi_8_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_8_5/hyper_params_psi_8_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_9/best_model_psi_9.data-00000-of-00001 b/logs/models_ensemble/psi_9/best_model_psi_9.data-00000-of-00001
deleted file mode 100644
index a9bcb18..0000000
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diff --git a/logs/models_ensemble/psi_9/best_model_psi_9.index b/logs/models_ensemble/psi_9/best_model_psi_9.index
deleted file mode 100644
index fbbda4f..0000000
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diff --git a/logs/models_ensemble/psi_9/best_model_psi_9.meta b/logs/models_ensemble/psi_9/best_model_psi_9.meta
deleted file mode 100644
index 9aca64e..0000000
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diff --git a/logs/models_ensemble/psi_9/checkpoint b/logs/models_ensemble/psi_9/checkpoint
deleted file mode 100644
index 27b5452..0000000
--- a/logs/models_ensemble/psi_9/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_9"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "best_model_psi_9"
diff --git a/logs/models_ensemble/psi_9/hyper_params_psi_9.json b/logs/models_ensemble/psi_9/hyper_params_psi_9.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_9/hyper_params_psi_9.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_9_5/best_model_psi_9_5.data-00000-of-00001 b/logs/models_ensemble/psi_9_5/best_model_psi_9_5.data-00000-of-00001
deleted file mode 100644
index f4b3f19..0000000
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diff --git a/logs/models_ensemble/psi_9_5/best_model_psi_9_5.index b/logs/models_ensemble/psi_9_5/best_model_psi_9_5.index
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index c637583..0000000
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diff --git a/logs/models_ensemble/psi_9_5/best_model_psi_9_5.meta b/logs/models_ensemble/psi_9_5/best_model_psi_9_5.meta
deleted file mode 100644
index 6f92ccb..0000000
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diff --git a/logs/models_ensemble/psi_9_5/checkpoint b/logs/models_ensemble/psi_9_5/checkpoint
deleted file mode 100644
index 199998e..0000000
--- a/logs/models_ensemble/psi_9_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "best_model_psi_9_5"
diff --git a/logs/models_ensemble/psi_9_5/hyper_params_psi_9_5.json b/logs/models_ensemble/psi_9_5/hyper_params_psi_9_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_9_5/hyper_params_psi_9_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/temporary_latest_streaming_image/1.jpeg b/logs/temporary_latest_streaming_image/1.jpeg
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diff --git a/logs/temporary_latest_streaming_image/2.png b/logs/temporary_latest_streaming_image/2.png
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diff --git a/logs/temporary_latest_streaming_image/3.png b/logs/temporary_latest_streaming_image/3.png
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index 5a82531..0000000
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diff --git a/logs/temporary_latest_streaming_image/3_needle.png b/logs/temporary_latest_streaming_image/3_needle.png
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index f2e6b9e..0000000
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diff --git a/logs/temporary_latest_streaming_image/latest_streaming_frame.jpg b/logs/temporary_latest_streaming_image/latest_streaming_frame.jpg
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diff --git a/logs/temporary_models/checkpoint b/logs/temporary_models/checkpoint
deleted file mode 100644
index c870bd8..0000000
--- a/logs/temporary_models/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "ensemble_architecture_main"
-all_model_checkpoint_paths: "ensemble_architecture_main"
diff --git a/logs/temporary_models/ensemble_architecture_main.data-00000-of-00001 b/logs/temporary_models/ensemble_architecture_main.data-00000-of-00001
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index 7cf0a96..0000000
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diff --git a/logs/temporary_models/ensemble_architecture_main.index b/logs/temporary_models/ensemble_architecture_main.index
deleted file mode 100644
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diff --git a/logs/temporary_models/ensemble_architecture_main.meta b/logs/temporary_models/ensemble_architecture_main.meta
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diff --git a/modules/LoadImg.py b/modules/LoadImg.py
deleted file mode 100644
index b7bd829..0000000
--- a/modules/LoadImg.py
+++ /dev/null
@@ -1,183 +0,0 @@
-from sklearn.datasets import load_files
-import numpy as np
-from sklearn.model_selection import train_test_split
-from keras.preprocessing import image
-import pandas as pd
-from MultiColProcessor import MultiColProcessor as mcp
-import pickle
-import json
-from collections import OrderedDict
-
-
-class Dataset(object):
- def __init__(self):
- self.category_mapper = {}
-
- @staticmethod
- def dump_pkl_MultiColProcessor(gauge_categories, bin_path):
- y_true_cat = pd.DataFrame(data=gauge_categories, columns=['y_true'], dtype='category')
- MultiColumnOneHotEncoder = mcp.MultiColomnOneHotEncoder()
- MultiColumnOneHotEncoder.fit(data=y_true_cat)
- with open(bin_path+'MultiColProcessor.pkl', 'wb') as pklFile:
- pickle.dump(MultiColumnOneHotEncoder, pklFile)
- return
-
- @staticmethod
- def dump_json_category_mapper(data, bin_path):
- ##
- category_mapper = OrderedDict()
- category_mapper_num_to_cat = OrderedDict()
- category_mapper_cat_to_num = OrderedDict()
- for i in range(len(data['target_names'])):
- category_mapper_num_to_cat[i] = data['target_names'][i]
- for i in range(len(data['target_names'])):
- category_mapper_cat_to_num[data['target_names'][i]] = i
-
- ##
- category_mapper['num_to_cat'] = category_mapper_num_to_cat
- category_mapper['cat_to_num'] = category_mapper_cat_to_num
- category_mapper['num_classes'] = len(data['target_names'])
-
- Dataset.category_mapper = category_mapper
-
- with open(bin_path+'category_mapper.json', 'w') as outfile:
- json.dump(category_mapper, outfile)
- return
-
- @staticmethod
- def load_dataset(path, bin_path):
- data = load_files(path, load_content=False)
-
- ## to save categories encoder
- Dataset.dump_json_category_mapper(data=data, bin_path=bin_path)
-
- ##
- guage_files = np.array(data['filenames'])
- gauge_categories = np.array(data['target'])
-
- ##
- Dataset.dump_pkl_MultiColProcessor(gauge_categories=gauge_categories, bin_path=bin_path)
-
- return guage_files, gauge_categories
-
- @staticmethod
- def split_data_files(ver_ratio, path, random_state, is_trial, bin_path):
- ##
- guage_files, gauge_categories = Dataset.load_dataset(path=path, bin_path=bin_path)
-
- if is_trial:
- guage_files = guage_files[:20]
- gauge_categories = gauge_categories[:20]
-
-
- #
- X_train_path_names, X_test_path_names, y_train, y_test = \
- train_test_split(guage_files,
- gauge_categories,
- test_size=ver_ratio,
- random_state=random_state)
- ##
- return X_train_path_names, X_test_path_names, y_train, y_test
-
- @staticmethod
- def path_to_tensor(img_path, img_size_x, img_size_y, color_mode):
- if img_size_x is None:
- img_size_x = 224
- if img_size_y is None:
- img_size_y = 224
- # loads RGB image as PIL.Image.Image type
- img = image.load_img(img_path, target_size=(img_size_y, img_size_x, color_mode))
- # convert PIL.Image.Image type to 3D tensor with shape (?, ?, ?)
- x = image.img_to_array(img)
- # convert 3D tensor to 4D tensor with shape (1, ?, ?, ?) and return 4D tensor
- return np.expand_dims(x, axis=0)
-
- @staticmethod
- def paths_to_tensor(imgs_path, img_size_x, img_size_y, color_mode):
- list_of_tensors = [Dataset.path_to_tensor(img_path, img_size_x, img_size_y, color_mode)
- for img_path in list(imgs_path)]
- return np.vstack(list_of_tensors)
-
- @staticmethod
- def find_cls_indices(train_y_data, test_y_data):
- ##
- num_classes = Dataset.category_mapper['num_classes']
-
- ##
- train_indices = OrderedDict()
- test_indices = OrderedDict()
- for cls in range(num_classes):
- label = Dataset.category_mapper['num_to_cat'][cls]
- train_indices[label] = train_y_data[:, cls] == True
- test_indices[label] = test_y_data[:, cls] == True
-
- ##
- cls_indices = OrderedDict()
- cls_indices['train_indices'] = train_indices
- cls_indices['test_indices'] = test_indices
-
- return cls_indices
-
- @classmethod
- def prep_datasets(cls, ver_ratio, container_path, final_img_width, final_img_height,
- color_mode='grayscale',
- random_state=19, is_trial=False, bin_path='dumps/'):
- ##
- X_train_path_names, X_test_path_names, y_train, y_test = \
- cls.split_data_files(ver_ratio=ver_ratio,
- path=container_path,
- random_state=random_state,
- is_trial=is_trial,
- bin_path=bin_path)
-
- X_train = cls.paths_to_tensor(imgs_path=X_train_path_names,
- img_size_x=final_img_width,
- img_size_y=final_img_height,
- color_mode=color_mode)
-
- X_test = cls.paths_to_tensor(imgs_path=X_test_path_names,
- img_size_x=final_img_width,
- img_size_y=final_img_height,
- color_mode=color_mode)
-
- ## OneHot encoding of y_train and y_test
- with open('dumps/MultiColProcessor.pkl', 'rb') as handle:
- MultiColumnOneHotEncoder = pickle.load(handle)
-
- y_train_cat = pd.DataFrame(data=y_train, columns=['y_true'], dtype='category')
- y_train = MultiColumnOneHotEncoder.transform(data=y_train_cat)
- y_test_cat = pd.DataFrame(data=y_test, columns=['y_true'], dtype='category')
- y_test = MultiColumnOneHotEncoder.transform(data=y_test_cat)
-
- ##
- cls_indices = cls.find_cls_indices(train_y_data=y_train.values, test_y_data=y_test.values)
-
- print("The image pre-processing is complete.")
-
- return X_train, X_test, y_train.values, y_test.values, cls_indices
-
- # @classmethod
- # def prep_datasets_for_ensemble(cls, ver_ratio, container_path, final_img_width, final_img_height,
- # color_mode='grayscale',
- # random_state=19, is_trial=False, bin_path='dump/'):
- # ##
- # X_train_path_names, X_test_path_names, y_train, y_test = \
- # cls.split_data_files(ver_ratio=ver_ratio,
- # path=container_path,
- # random_state=random_state,
- # is_trial=is_trial,
- # bin_path=bin_path)
- #
- # X_train = cls.paths_to_tensor(imgs_path=X_train_path_names,
- # img_size_x=final_img_width,
- # img_size_y=final_img_height,
- # color_mode=color_mode)
- #
- # X_test = cls.paths_to_tensor(imgs_path=X_test_path_names,
- # img_size_x=final_img_width,
- # img_size_y=final_img_height,
- # color_mode=color_mode)
- #
- # print("The image pre-processing for ensemble is complete.")
- #
- # return X_train, X_test, y_train, y_test
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diff --git a/modules/ensemble_modules/CustomEnsembleEstimator.py b/modules/ensemble_modules/CustomEnsembleEstimator.py
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--- a/modules/ensemble_modules/CustomEnsembleEstimator.py
+++ /dev/null
@@ -1,591 +0,0 @@
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import argparse
-import tensorflow as tf
-from modules import LoadImg
-import glob
-import os
-from tensorflow.python.framework import meta_graph
-import numpy as np
-
-from sklearn.datasets import load_files
-import numpy as np
-from sklearn.model_selection import train_test_split
-from keras.preprocessing import image
-import pandas as pd
-from MultiColProcessor import MultiColProcessor as mcp
-import pickle
-import json
-from collections import OrderedDict
-
-
-########################
-def create_parser():
- parser = argparse.ArgumentParser()
- parser.add_argument('--path_to_images', default='data/ImageEveryUnit',
- type=str,
- help='path to images (e.g. gs://...)')
- parser.add_argument('--primary_models_directory',
- default='./logs/primary_models/',
- type=str)
- parser.add_argument('--images_shape',
- default='[None, 224, 224, 3]',
- type=str)
- parser.add_argument('--hidden_units',
- default='[500, 100]',
- type=str)
- parser.add_argument('--learning_rate',
- default=3e-4,
- type=float)
- parser.add_argument('--retrain_primary_models',
- default='False',
- type=str)
- parser.add_argument('--batch_size',
- default=6,
- type=int)
- parser.add_argument('--train_epochs',
- default=1,
- type=int)
- parser.add_argument('--epochs_between_evals',
- default=1,
- type=int)
- parser.add_argument('--export_dir',
- default='./logs/exported_model',
- type=str)
- parser.add_argument('--ensemble_architecture_path',
- default='./logs/temporary_models/',
- type=str)
- parser.add_argument('--metric',
- default='accuracy',
- type=str)
- parser.add_argument('--bin_path',
- default='dumps/',
- type=str)
- parser.add_argument('--dev',
- default='False',
- type=str)
- parser.add_argument('--color_mode',
- default='grayscale',
- type=str)
- parser.add_argument('--random_state',
- default=1911,
- type=int)
- return parser
-
-
-parser = create_parser()
-
-
-class Dataset():
- def __init__(self):
- self.category_mapper = {}
-
- @staticmethod
- def dump_pkl_MultiColProcessor(gauge_categories, bin_path):
- y_true_cat = pd.DataFrame(data=gauge_categories, columns=['y_true'], dtype='category')
- MultiColumnOneHotEncoder = mcp.MultiColomnOneHotEncoder()
- MultiColumnOneHotEncoder.fit(data=y_true_cat)
- with open(bin_path + 'MultiColProcessor.pkl', 'wb') as pklFile:
- pickle.dump(MultiColumnOneHotEncoder, pklFile)
- return
-
- @staticmethod
- def dump_json_category_mapper(data, bin_path):
- ##
- category_mapper = OrderedDict()
- category_mapper_num_to_cat = OrderedDict()
- category_mapper_cat_to_num = OrderedDict()
- for i in range(len(data['target_names'])):
- category_mapper_num_to_cat[i] = data['target_names'][i]
- for i in range(len(data['target_names'])):
- category_mapper_cat_to_num[data['target_names'][i]] = i
-
- ##
- category_mapper['num_to_cat'] = category_mapper_num_to_cat
- category_mapper['cat_to_num'] = category_mapper_cat_to_num
- category_mapper['num_classes'] = len(data['target_names'])
-
- Dataset.category_mapper = category_mapper
-
- with open(bin_path + 'category_mapper.json', 'w') as outfile:
- json.dump(category_mapper, outfile)
- return
-
- @staticmethod
- def load_dataset(path, bin_path):
- data = load_files(path, load_content=False)
-
- ## to save categories encoder
- Dataset.dump_json_category_mapper(data=data, bin_path=bin_path)
-
- ##
- guage_files = np.array(data['filenames'])
- gauge_categories = np.array(data['target'])
-
- ##
- Dataset.dump_pkl_MultiColProcessor(gauge_categories=gauge_categories, bin_path=bin_path)
-
- return guage_files, gauge_categories
-
- @staticmethod
- def split_data_files(ver_ratio, path, random_state, is_trial, bin_path):
- ##
- guage_files, gauge_categories = Dataset.load_dataset(path=path, bin_path=bin_path)
-
- if is_trial == True:
- guage_files = guage_files[:20]
- gauge_categories = gauge_categories[:20]
-
- #
- X_train_path_names, X_test_path_names, y_train, y_test = \
- train_test_split(guage_files,
- gauge_categories,
- test_size=ver_ratio,
- random_state=random_state)
- ##
- return X_train_path_names, X_test_path_names, y_train, y_test
-
- @staticmethod
- def path_to_tensor(img_path, img_size_x, img_size_y, color_mode):
- if img_size_x is None:
- img_size_x = 224
- if img_size_y is None:
- img_size_y = 224
- # loads RGB image as PIL.Image.Image type
- img = image.load_img(img_path, target_size=(img_size_y, img_size_x, color_mode))
- # convert PIL.Image.Image type to 3D tensor with shape (?, ?, ?)
- x = image.img_to_array(img)
- # convert 3D tensor to 4D tensor with shape (1, ?, ?, ?) and return 4D tensor
- return np.expand_dims(x, axis=0)
-
- @staticmethod
- def paths_to_tensor(imgs_path, img_size_x, img_size_y, color_mode):
- list_of_tensors = [Dataset.path_to_tensor(img_path, img_size_x, img_size_y, color_mode)
- for img_path in list(imgs_path)]
- return np.vstack(list_of_tensors)
-
- @staticmethod
- def find_cls_indices(train_y_data, test_y_data):
- ##
- num_classes = Dataset.category_mapper['num_classes']
-
- ##
- train_indices = OrderedDict()
- test_indices = OrderedDict()
- for cls in range(num_classes):
- label = Dataset.category_mapper['num_to_cat'][cls]
- train_indices[label] = train_y_data[:, cls] == True
- test_indices[label] = test_y_data[:, cls] == True
-
- ##
- cls_indices = OrderedDict()
- cls_indices['train_indices'] = train_indices
- cls_indices['test_indices'] = test_indices
-
- return cls_indices
-
- @classmethod
- def prep_datasets(cls, ver_ratio, container_path, final_img_width, final_img_height,
- color_mode='grayscale',
- random_state=19, is_trial=None, bin_path='dumps/'):
- ##
- X_train_path_names, X_test_path_names, y_train, y_test = \
- cls.split_data_files(ver_ratio=ver_ratio,
- path=container_path,
- random_state=random_state,
- is_trial=is_trial,
- bin_path=bin_path)
-
- X_train = cls.paths_to_tensor(imgs_path=X_train_path_names,
- img_size_x=final_img_width,
- img_size_y=final_img_height,
- color_mode=color_mode)
-
- X_test = cls.paths_to_tensor(imgs_path=X_test_path_names,
- img_size_x=final_img_width,
- img_size_y=final_img_height,
- color_mode=color_mode)
-
- ## OneHot encoding of y_train and y_test
- with open('dumps/MultiColProcessor.pkl', 'rb') as handle:
- MultiColumnOneHotEncoder = pickle.load(handle)
-
- y_train_cat = pd.DataFrame(data=y_train, columns=['y_true'], dtype='category')
- y_train = MultiColumnOneHotEncoder.transform(data=y_train_cat)
- y_test_cat = pd.DataFrame(data=y_test, columns=['y_true'], dtype='category')
- y_test = MultiColumnOneHotEncoder.transform(data=y_test_cat)
-
- ##
- cls_indices = cls.find_cls_indices(train_y_data=y_train.values, test_y_data=y_test.values)
-
- print("The image pre-processing is complete.")
-
- return X_train, X_test, y_train.values, y_test.values, cls_indices
-
-
-def input_fn_train(raw_imgs, labels, batch_size, epochs_between_evals):
- # Convert the inputs to a Dataset.
- dataset = tf.data.Dataset.from_tensor_slices(({'X': raw_imgs}, labels))
- # Shuffle, repeat, and batch the examples.
- dataset = dataset.cache().shuffle(100000).repeat(epochs_between_evals).batch(batch_size)
- # Return the read end of the pipeline.
- return dataset # dataset #dataset.make_one_shot_iterator().get_next()
-
-
-def input_fn_eval(raw_imgs, labels):
- dataset = tf.data.Dataset.from_tensor_slices(({'X': raw_imgs}, labels))
- dataset = dataset.batch(raw_imgs.shape[0])
- return dataset.make_one_shot_iterator().get_next()
-
-
-def create_ensemble_architecture(hidden_units=None,
- n_output=None,
- primary_models_directory=None,
- images_shape=None,
- save_path=None):
- class Ensemble():
- @staticmethod
- def __build_pipeline(model_name_scope=None,
- pipeline_params=None,
- raw_imgs_placeholder=None):
- graph_model = tf.Graph()
- with graph_model.as_default():
- ##################################
- with tf.Session(graph=graph_model) as sess:
- saver = tf.train.import_meta_graph(pipeline_params["checkpoint_file_path"],
- clear_devices=True,
- import_scope='CNN_model')
- saver.restore(tf.get_default_session(),
- tf.train.latest_checkpoint(pipeline_params["checkpoint_path"]))
-
- X_image_tf = graph_model.get_tensor_by_name("CNN_model/X_image_tf:0")
- logits_tf = graph_model.get_tensor_by_name("CNN_model/logits_tf:0")
- # logits_tf_sg = tf.stop_gradient(logits_tf)
- ####################################
-
- graph_pipeline = tf.Graph()
- with graph_pipeline.as_default():
- ##################################
- X_raw = tf.placeholder(tf.float32, shape=[None, None, None, None], name="X_raw")
- meta_graph.import_scoped_meta_graph(pipeline_params["checkpoint_file_path"],
- clear_devices=True,
- import_scope='img_size_info')
-
- X_image_tf = graph_pipeline.get_tensor_by_name("img_size_info/X_image_tf:0")
-
- resized_imgs = tf.identity(tf.image.resize_images(X_raw, (X_image_tf.get_shape().as_list()[1],
- X_image_tf.get_shape().as_list()[2])),
- name='resized_imgs')
- ####################################
-
- graph = tf.get_default_graph()
-
- raw_imgs = raw_imgs_placeholder
-
- meta_graph_1 = tf.train.export_meta_graph(graph=graph_pipeline)
- meta_graph.import_scoped_meta_graph(meta_graph_1,
- input_map={"X_raw": raw_imgs},
- import_scope=model_name_scope + '_img_pipeline')
-
- out_1 = graph.get_tensor_by_name(model_name_scope + '_img_pipeline' + '/resized_imgs:0')
-
- meta_graph_2 = tf.train.export_meta_graph(graph=graph_model)
- meta_graph.import_scoped_meta_graph(meta_graph_2,
- input_map={"CNN_model/X_image_tf": out_1},
- import_scope=model_name_scope + '_CNN')
-
- out_2 = graph.get_tensor_by_name(model_name_scope + '_CNN' + '/CNN_model/logits_tf:0')
-
- return out_2
-
- @staticmethod
- def _combine_all_channel(models_directory=None, images_shape=None):
- graph_parent = tf.Graph()
- with graph_parent.as_default():
- raw_imgs = tf.placeholder(tf.float32, shape=[None, None, None, None], name='raw_imgs')
- for i, model in enumerate(os.listdir(models_directory)):
- checkpoint_path = glob.glob(os.path.join(models_directory, model))[0]
- checkpoint_file_path = glob.glob(os.path.join(checkpoint_path, '*.meta'))[0]
- params = {"checkpoint_path": checkpoint_path,
- "checkpoint_file_path": checkpoint_file_path}
-
- logits_out = Ensemble.__build_pipeline(
- model_name_scope='M_' + model,
- pipeline_params=params,
- raw_imgs_placeholder=raw_imgs)
-
- try:
- final_logits = tf.concat([final_logits, logits_out], 1)
- except:
- final_logits = logits_out
-
- final_logits_named = tf.identity(final_logits, name='final_logits')
-
- graph = tf.get_default_graph()
-
- raw_imgs_in_main_graph = tf.placeholder(tf.float32, shape=images_shape, name='raw_imgs')
-
- meta_graph_3 = tf.train.export_meta_graph(graph=graph_parent)
- meta_graph.import_scoped_meta_graph(meta_graph_3,
- input_map={"raw_imgs": raw_imgs_in_main_graph},
- import_scope='graph_parent')
-
- # raw_imgs_name = [n.name for n in tf.get_default_graph().as_graph_def().node if 'raw_imgs' in n.name][0]
- # raw_imgs_tf = graph.get_tensor_by_name(raw_imgs_name + ':0')
-
- logits_name = [n.name for n in tf.get_default_graph().as_graph_def().node if 'final_logit' in n.name][0]
- logits_concat = graph.get_tensor_by_name(logits_name + ':0')
-
- return raw_imgs_in_main_graph, logits_concat
-
- @classmethod
- def build_finalGraph_and_return_final_tensors(cls,
- hidden_units=None,
- n_output=None,
- primary_models_directory=None,
- images_shape=None):
- def _new_weights(shape):
- with tf.name_scope('weights_ensemble'):
- weights = tf.Variable(tf.truncated_normal(shape, stddev=0.05))
- return weights
-
- def _new_biases(length):
- with tf.name_scope('biases_ensemble'):
- biases = tf.Variable(tf.constant(0.05, shape=[length]))
- return biases
-
- def new_fc_layer(inp,
- num_inputs,
- num_outputs,
- use_relu=True,
- use_drop_out=True,
- name_scope=''):
- with tf.name_scope(name_scope):
- weights = _new_weights(shape=[num_inputs, num_outputs])
- biases = _new_biases(length=num_outputs)
-
- layer = tf.matmul(inp, weights) + biases
-
- if use_drop_out:
- layer = tf.layers.dropout(layer, rate=0.05, training=use_drop_out)
-
- if use_relu:
- layer = tf.nn.relu(layer)
-
- return layer
-
- ##
- raw_imgs, concatenated_features = cls._combine_all_channel(
- models_directory=primary_models_directory, images_shape=images_shape)
- ##
- params_fc = {'hidden_units': hidden_units.copy(),
- 'n_output': n_output}
- ##
- graph_fc = tf.Graph()
- with graph_fc.as_default():
- X_tf = tf.placeholder(tf.float32, shape=[None, concatenated_features.get_shape().as_list()[1]],
- name='X_tf')
-
- #########################
- layer = None
- for n_layer, n_nodes in enumerate(params_fc['hidden_units']):
- if n_layer == 0:
- layer = new_fc_layer(X_tf,
- num_inputs=X_tf.get_shape().as_list()[1],
- num_outputs=n_nodes,
- name_scope='layer_' + str(n_layer + 1))
- else:
- layer = new_fc_layer(layer,
- num_inputs=layer.get_shape().as_list()[1],
- num_outputs=n_nodes,
- name_scope='layer_' + str(n_layer + 1))
-
- logits = new_fc_layer(layer,
- num_inputs=layer.get_shape().as_list()[1],
- num_outputs=params_fc['n_output'],
- use_relu=False,
- use_drop_out=False,
- name_scope='output_layer')
-
- logits_fc = tf.identity(logits, name='logits_tf')
-
- ##
- graph = tf.get_default_graph()
-
- meta_graph_3 = tf.train.export_meta_graph(graph=graph_fc)
- meta_graph.import_scoped_meta_graph(meta_graph_3,
- input_map={"X_tf": concatenated_features},
- import_scope='')
-
- logits_fc = graph.get_tensor_by_name('logits_tf:0')
- return raw_imgs, logits_fc
-
- ## to create the ensemble architecture from the primary models
- tf.reset_default_graph()
- ##
- _, _ = Ensemble.build_finalGraph_and_return_final_tensors(
- hidden_units=hidden_units,
- n_output=n_output,
- primary_models_directory=primary_models_directory,
- images_shape=images_shape)
- saver = tf.train.Saver(max_to_keep=1)
- with tf.Session() as sess:
- sess.run(tf.global_variables_initializer())
- saver.save(sess, os.path.join(save_path, 'ensemble_architecture_' + 'main'))
- tf.reset_default_graph()
- return
-
-
-def ensemble_model(features, labels, mode, params):
- ######### dev
- # params = {'primary_models_directory': './logs/primary_models/',
- # 'writer_path': './trial/writer',
- # 'save_model_path': './trial/best_model_main',
- # 'number_of_categories': labels.shape[1],
- # 'images_shape': [None, 224, 224, 3],
- # 'hidden_units': [500, 100],
- # 'n_output': labels.shape[1],
- # 'epochs': 10,
- # 'learning_rate': 3e-4}
-
- #########
-
- graph_ensemble = tf.Graph()
- with tf.Session(graph=graph_ensemble) as sess:
- meta_graph_path = glob.glob(os.path.join(params["ensemble_architecture_path"], '*.meta'))[0]
- loader = tf.train.import_meta_graph(meta_graph_path, clear_devices=True)
- loader.restore(sess, tf.train.latest_checkpoint(params["ensemble_architecture_path"]))
-
- graph = tf.get_default_graph()
-
- meta_graph_0 = tf.train.export_meta_graph(graph=graph_ensemble)
- meta_graph.import_scoped_meta_graph(meta_graph_0,
- input_map={"raw_imgs": features['X']},
- import_scope='main_graph')
-
- logits = graph.get_tensor_by_name('main_graph/logits_tf:0')
-
- predicted_classes = tf.argmax(logits, 1)
-
- if mode == tf.estimator.ModeKeys.PREDICT:
- predictions = {
- 'class_ids': predicted_classes[:, tf.newaxis],
- 'probabilities': tf.nn.softmax(logits),
- 'logits': logits,
- }
- return tf.estimator.EstimatorSpec(mode, predictions=predictions)
-
- cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(labels=labels,
- logits=logits,
- name='cross_entropy')
- loss = tf.reduce_mean(cross_entropy, name='cost_fc')
-
- accuracy = tf.metrics.accuracy(labels=tf.argmax(labels, 1),
- predictions=predicted_classes,
- name='acc_op')
-
- metrics = {'accuracy': accuracy}
- tf.summary.scalar('accuracy', accuracy[1])
-
- if mode == tf.estimator.ModeKeys.EVAL:
- return tf.estimator.EstimatorSpec(
- mode, loss=loss, eval_metric_ops=metrics)
-
- assert mode == tf.estimator.ModeKeys.TRAIN
-
- if params['retrain_primary_models'] != True:
- trainable_variables = [v for v in tf.trainable_variables() if 'ensemble' in v.name]
- else:
- trainable_variables = [v for v in tf.trainable_variables()]
-
- ###### trial
- print('there are {} DDDDDDDDDDDD'.format(len(trainable_variables)))
- ######
-
- optimizer = tf.train.AdamOptimizer(learning_rate=params['learning_rate'], name='adam_fc')
- train_op = optimizer.minimize(loss, var_list=trainable_variables,
- global_step=tf.train.get_or_create_global_step())
- return tf.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op)
-
-
-def main(argv):
- args = parser.parse_args(argv[1:])
-
- ##
- images_shape = eval(args.images_shape)
- path_to_images = args.path_to_images
- color_mode = args.color_mode
- bin_path = args.bin_path
- is_trial = args.dev == 'True'
- primary_models_directory = args.primary_models_directory
- hidden_units = eval(args.hidden_units)
- ensemble_architecture_path = args.ensemble_architecture_path
- learning_rate = args.learning_rate
- retrain_primary_models = args.retrain_primary_models == 'True'
- train_epochs = args.train_epochs
- epochs_between_evals = args.epochs_between_evals
- batch_size = args.batch_size
- export_dir = args.export_dir
- metric = args.metric
- ##
-
- # Fetch the data
- print('loading image data ...')
- X_train, X_test, y_train, y_test, _ = Dataset.prep_datasets(
- ver_ratio=0.2, container_path=path_to_images,
- final_img_width=images_shape[2], final_img_height=images_shape[1],
- color_mode=color_mode, random_state=1911, bin_path=bin_path, is_trial=is_trial)
-
- create_ensemble_architecture(hidden_units=hidden_units,
- n_output=y_train.shape[1],
- primary_models_directory=primary_models_directory,
- images_shape=images_shape,
- save_path=ensemble_architecture_path)
-
- classifier = tf.estimator.Estimator(
- model_fn=ensemble_model,
- params={
- 'primary_models_directory': primary_models_directory,
- 'images_shape': images_shape,
- 'hidden_units': hidden_units,
- 'learning_rate': learning_rate,
- 'ensemble_architecture_path': ensemble_architecture_path,
- 'retrain_primary_models': retrain_primary_models
- })
-
- # Train and evaluate model.
- model_criteria = 0.0
- image = tf.placeholder(tf.float32, shape=images_shape, name='export_input_image')
- input_fn = tf.estimator.export.build_raw_serving_input_receiver_fn({'X': image})
- ##
- for i in range(train_epochs // epochs_between_evals):
- print('epoch {} .........'.format(i * epochs_between_evals + 1))
- classifier.train(
- input_fn=lambda: input_fn_train(
- raw_imgs=X_train, labels=y_train,
- batch_size=batch_size,
- epochs_between_evals=epochs_between_evals))
-
- eval_result = classifier.evaluate(
- input_fn=lambda: input_fn_eval(raw_imgs=X_test, labels=y_test))
- print('')
- print('')
- print('current validation dataset accuracy is: {}'.format(eval_result['accuracy']))
- print('current highest validation dataset accuracy is: {}'.format(model_criteria))
- if eval_result[metric] > model_criteria:
- model_criteria = eval_result[metric].copy()
- print('current highest validation dataset accuracy updated to: {}'.format(model_criteria))
- print('')
- print('')
- classifier.export_savedmodel(export_dir, input_fn, strip_default_attrs=True)
- print('model updated')
- continue
- print('')
- print('')
-
-
-if __name__ == '__main__':
- tf.logging.set_verbosity(tf.logging.INFO)
- tf.app.run(main)
diff --git a/modules/ensemble_modules/__pycache__/CustomEnsembleEstimator.cpython-36.pyc b/modules/ensemble_modules/__pycache__/CustomEnsembleEstimator.cpython-36.pyc
deleted file mode 100644
index 82ed5b5..0000000
Binary files a/modules/ensemble_modules/__pycache__/CustomEnsembleEstimator.cpython-36.pyc and /dev/null differ
diff --git a/modules/ensemble_modules/ensemble_build.py b/modules/ensemble_modules/ensemble_build.py
deleted file mode 100644
index d171124..0000000
--- a/modules/ensemble_modules/ensemble_build.py
+++ /dev/null
@@ -1,279 +0,0 @@
-import glob
-import os
-from tensorflow.python.framework import meta_graph
-import tensorflow as tf
-from modules import LoadImg
-import time
-import numpy as np
-
-X_train, X_test, y_train, y_test, cls_indices = LoadImg.Dataset.prep_datasets(
- ver_ratio=0.2, container_path='data/ImageEveryUnit',
- final_img_width=224, final_img_height=224,
- color_mode="grayscale", random_state=1911, is_trial=True)
-
-
-class Ensemble():
- @staticmethod
- def __build_pipeline(model_name_scope=None,
- pipeline_params=None,
- raw_imgs_placeholder=None):
- graph_model = tf.Graph()
- with graph_model.as_default():
- ##################################
- with tf.Session(graph=graph_model) as sess:
- saver = tf.train.import_meta_graph(pipeline_params["checkpoint_file_path"],
- clear_devices=True,
- import_scope='CNN_model')
- saver.restore(tf.get_default_session(),
- tf.train.latest_checkpoint(pipeline_params["checkpoint_path"]))
-
- X_image_tf = graph_model.get_tensor_by_name("CNN_model/X_image_tf:0")
- logits_tf = graph_model.get_tensor_by_name("CNN_model/logits_tf:0")
- # logits_tf_sg = tf.stop_gradient(logits_tf)
- ####################################
-
- graph_pipeline = tf.Graph()
- with graph_pipeline.as_default():
- ##################################
- X_raw = tf.placeholder(tf.float32, shape=[None, None, None, None], name="X_raw")
- meta_graph.import_scoped_meta_graph(pipeline_params["checkpoint_file_path"],
- clear_devices=True,
- import_scope='img_size_info')
-
- X_image_tf = graph_pipeline.get_tensor_by_name("img_size_info/X_image_tf:0")
-
- resized_imgs = tf.identity(tf.image.resize_images(X_raw, (X_image_tf.get_shape().as_list()[1],
- X_image_tf.get_shape().as_list()[2])),
- name='resized_imgs')
- ####################################
-
- graph = tf.get_default_graph()
-
- raw_imgs = raw_imgs_placeholder
-
- meta_graph_1 = tf.train.export_meta_graph(graph=graph_pipeline)
- meta_graph.import_scoped_meta_graph(meta_graph_1,
- input_map={"X_raw": raw_imgs},
- import_scope=model_name_scope + '_img_pipeline')
-
- out_1 = graph.get_tensor_by_name(model_name_scope + '_img_pipeline' + '/resized_imgs:0')
-
- meta_graph_2 = tf.train.export_meta_graph(graph=graph_model)
- meta_graph.import_scoped_meta_graph(meta_graph_2,
- input_map={"CNN_model/X_image_tf": out_1},
- import_scope=model_name_scope + '_CNN')
-
- out_2 = graph.get_tensor_by_name(model_name_scope + '_CNN' + '/CNN_model/logits_tf:0')
-
- return out_2
-
- @staticmethod
- def _combine_all_channel(models_directory=None, images_shape=None):
- graph_parent = tf.Graph()
- with graph_parent.as_default():
- raw_imgs = tf.placeholder(tf.float32, shape=[None, None, None, None], name='raw_imgs')
- for i, model in enumerate(os.listdir(models_directory)):
- checkpoint_path = glob.glob(os.path.join(models_directory, model))[0]
- checkpoint_file_path = glob.glob(os.path.join(checkpoint_path, '*.meta'))[0]
- params = {"checkpoint_path": checkpoint_path,
- "checkpoint_file_path": checkpoint_file_path}
-
- logits_out = Ensemble.__build_pipeline(
- model_name_scope='M_' + model,
- pipeline_params=params,
- raw_imgs_placeholder=raw_imgs)
-
- try:
- final_logits = tf.concat([final_logits, logits_out], 1)
- except:
- final_logits = logits_out
-
- final_logits_named = tf.identity(final_logits, name='final_logits')
-
- graph = tf.get_default_graph()
-
- raw_imgs_in_main_graph = tf.placeholder(tf.float32, shape=images_shape, name='raw_imgs')
-
- meta_graph_3 = tf.train.export_meta_graph(graph=graph_parent)
- meta_graph.import_scoped_meta_graph(meta_graph_3,
- input_map={"raw_imgs": raw_imgs_in_main_graph},
- import_scope='graph_parent')
-
- # raw_imgs_name = [n.name for n in tf.get_default_graph().as_graph_def().node if 'raw_imgs' in n.name][0]
- # raw_imgs_tf = graph.get_tensor_by_name(raw_imgs_name + ':0')
-
- logits_name = [n.name for n in tf.get_default_graph().as_graph_def().node if 'final_logit' in n.name][0]
- logits_concat = graph.get_tensor_by_name(logits_name + ':0')
-
- return raw_imgs_in_main_graph, logits_concat
-
- @classmethod
- def build_finalGraph_and_return_final_tensors(cls,
- hidden_units=None,
- n_output=None,
- primary_models_directory=None,
- images_shape=None):
- def _new_weights(shape):
- with tf.name_scope('weights_ensemble'):
- weights = tf.Variable(tf.truncated_normal(shape, stddev=0.05))
- return weights
-
- def _new_biases(length):
- with tf.name_scope('biases_ensemble'):
- biases = tf.Variable(tf.constant(0.05, shape=[length]))
- return biases
-
- def new_fc_layer(inp,
- num_inputs,
- num_outputs,
- use_relu=True,
- use_drop_out=True,
- name_scope=''):
- with tf.name_scope(name_scope):
- weights = _new_weights(shape=[num_inputs, num_outputs])
- biases = _new_biases(length=num_outputs)
-
- layer = tf.matmul(inp, weights) + biases
-
- if use_drop_out:
- layer = tf.layers.dropout(layer, rate=0.05, training=use_drop_out)
-
- if use_relu:
- layer = tf.nn.relu(layer)
-
- return layer
-
- ##
- raw_imgs, concatenated_features = cls._combine_all_channel(
- models_directory=primary_models_directory, images_shape=images_shape)
- ##
- params_fc = {'hidden_units': hidden_units.copy(),
- 'n_output': n_output}
- ##
- graph_fc = tf.Graph()
- with graph_fc.as_default():
- X_tf = tf.placeholder(tf.float32, shape=[None, concatenated_features.get_shape().as_list()[1]], name='X_tf')
-
- #########################
- layer = None
- for n_layer, n_nodes in enumerate(params_fc['hidden_units']):
- if n_layer == 0:
- layer = new_fc_layer(X_tf,
- num_inputs=X_tf.get_shape().as_list()[1],
- num_outputs=n_nodes,
- name_scope='layer_' + str(n_layer + 1))
- else:
- layer = new_fc_layer(layer,
- num_inputs=layer.get_shape().as_list()[1],
- num_outputs=n_nodes,
- name_scope='layer_' + str(n_layer + 1))
-
- logits = new_fc_layer(layer,
- num_inputs=layer.get_shape().as_list()[1],
- num_outputs=params_fc['n_output'],
- use_relu=False,
- use_drop_out=False,
- name_scope='output_layer')
-
- logits_fc = tf.identity(logits, name='logits_tf')
-
- ##
- graph = tf.get_default_graph()
-
- meta_graph_3 = tf.train.export_meta_graph(graph=graph_fc)
- meta_graph.import_scoped_meta_graph(meta_graph_3,
- input_map={"X_tf": concatenated_features},
- import_scope='')
-
- logits_fc = graph.get_tensor_by_name('logits_tf:0')
- return raw_imgs, logits_fc
-
-
-def build_model_and_train(primary_models_directory='./logs/primary_models/',
- writer_path='./trial/writer',
- save_model_path='./trial/best_model_main',
- images_shape=[None, 224, 224, 3],
- hidden_units=[500, 100],
- X_train=X_train, X_test=X_test,
- y_train=y_train, y_test=y_test,
- batch_size=4,
- epochs=10):
- raw_imgs, logits_fc = Ensemble.build_finalGraph_and_return_final_tensors(
- hidden_units=hidden_units,
- n_output=y_train.shape[1],
- primary_models_directory=primary_models_directory,
- images_shape=images_shape)
- tf.reset_default_graph()
- graph = tf.get_default_graph()
-
- ## y
- y_true_tf = tf.placeholder(tf.float64, shape=[None, y_train.shape[1]],
- name='y_true_tf')
-
- y_pred = tf.nn.softmax(logits_fc)
- y_pred_cls = tf.argmax(y_pred, axis=1)
- y_true_cls = tf.argmax(y_true_tf, axis=1)
- correct_prediction = tf.equal(y_pred_cls, y_true_cls)
- accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
-
- ## dataset
- dataset = tf.data.Dataset.from_tensor_slices((raw_imgs, y_true_tf))
- dataset = dataset.shuffle(buffer_size=100)
- dataset = dataset.batch(batch_size)
- dataset = dataset.repeat(epochs)
- iter = dataset.make_initializable_iterator()
- # iter = dataset.make_one_shot_iterator()
- get_batch = iter.get_next()
-
- ## cost
- cost = tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits_fc,
- labels=y_true_tf,
- name='cost_fc')
-
- trainable_variables = [v for v in tf.trainable_variables() if 'ensemble' in v.name]
- optimizer = tf.train.AdamOptimizer(learning_rate=3e-4, name='adam_fc'). \
- minimize(cost, var_list=trainable_variables)
- # variables_list = [n.name for n in tf.get_default_graph().as_graph_def().node if 'raw_imgs' in n.name]
-
- feed_dict_train = {raw_imgs: X_train,
- y_true_tf: y_train}
-
- feed_dict_test = {raw_imgs: X_test,
- y_true_tf: y_test}
-
- # Start-time used for printing time-usage below.
- start_time = time.time()
-
- with tf.Session(graph=graph) as session:
- # initialize weights and biases variables
- session.run(tf.global_variables_initializer())
- session.run(iter.initializer, feed_dict=feed_dict_train)
- writer = tf.summary.FileWriter(writer_path, session.graph)
-
- best_validation_accuracy=0
-
- for i in range(200):
- try:
- print('batch {} ... '.format(i))
- Xydata = session.run(get_batch)
- session.run(optimizer, feed_dict={raw_imgs: Xydata[0],
- y_true_tf: Xydata[1]})
- accuracy_train = session.run(accuracy, feed_dict=feed_dict_train)
- print('train_acc = {} ... '.format(accuracy_train))
- accuracy_validation = session.run(accuracy, feed_dict=feed_dict_test)
- print('validation_acc = {} ... '.format(accuracy_validation))
- if accuracy_validation > best_validation_accuracy:
- saver = tf.train.Saver(max_to_keep=1)
- saver.save(session, save_model_path)
- except:
- break
-
- writer.close()
-
- end_time = time.time()
-
- print("Training took {}.".format(end_time-start_time))
-
- return
-
-build_model_and_train()
\ No newline at end of file
diff --git a/modules/ensemble_modules/funcs_backup.py b/modules/ensemble_modules/funcs_backup.py
deleted file mode 100644
index e326837..0000000
--- a/modules/ensemble_modules/funcs_backup.py
+++ /dev/null
@@ -1,215 +0,0 @@
-import glob
-import os
-from tensorflow.python.framework import meta_graph
-import tensorflow as tf
-from modules import LoadImg
-import time
-import numpy as np
-
-
-def building_funcs():
- def __build_pipeline(model_name_scope=None,
- pipeline_params=None,
- raw_imgs_placeholder=None):
- graph_model = tf.Graph()
- with graph_model.as_default():
- ##################################
- with tf.Session(graph=graph_model) as sess:
- saver = tf.train.import_meta_graph(pipeline_params["checkpoint_file_path"],
- clear_devices=True,
- import_scope='CNN_model')
- saver.restore(tf.get_default_session(),
- tf.train.latest_checkpoint(pipeline_params["checkpoint_path"]))
-
- X_image_tf = graph_model.get_tensor_by_name("CNN_model/X_image_tf:0")
- logits_tf = graph_model.get_tensor_by_name("CNN_model/logits_tf:0")
- # logits_tf_sg = tf.stop_gradient(logits_tf)
- ####################################
-
- graph_pipeline = tf.Graph()
- with graph_pipeline.as_default():
- ##################################
- X_raw = tf.placeholder(tf.float32, shape=[None, None, None, None], name="X_raw")
- meta_graph.import_scoped_meta_graph(pipeline_params["checkpoint_file_path"],
- clear_devices=True,
- import_scope='img_size_info')
-
- X_image_tf = graph_pipeline.get_tensor_by_name("img_size_info/X_image_tf:0")
-
- resized_imgs = tf.identity(tf.image.resize_images(X_raw, (X_image_tf.get_shape().as_list()[1],
- X_image_tf.get_shape().as_list()[2])),
- name='resized_imgs')
- ####################################
-
- graph = tf.get_default_graph()
-
- raw_imgs = raw_imgs_placeholder
-
- meta_graph_1 = tf.train.export_meta_graph(graph=graph_pipeline)
- meta_graph.import_scoped_meta_graph(meta_graph_1,
- input_map={"X_raw": raw_imgs},
- import_scope=model_name_scope + '_img_pipeline')
-
- out_1 = graph.get_tensor_by_name(model_name_scope + '_img_pipeline' + '/resized_imgs:0')
-
- meta_graph_2 = tf.train.export_meta_graph(graph=graph_model)
- meta_graph.import_scoped_meta_graph(meta_graph_2,
- input_map={"CNN_model/X_image_tf": out_1},
- import_scope=model_name_scope + '_CNN')
-
- out_2 = graph.get_tensor_by_name(model_name_scope + '_CNN' + '/CNN_model/logits_tf:0')
-
- return out_2
-
- def _build_architecture(models_directory=None):
- graph_parent = tf.Graph()
- with graph_parent.as_default():
- raw_imgs = tf.placeholder(tf.float32, shape=[None, None, None, None], name='raw_imgs')
- for i, model in enumerate(os.listdir(models_directory)):
- checkpoint_path = glob.glob(os.path.join(models_directory, model))[0]
- checkpoint_file_path = glob.glob(os.path.join(checkpoint_path, '*.meta'))[0]
- params = {"checkpoint_path": checkpoint_path,
- "checkpoint_file_path": checkpoint_file_path}
-
- logits_out = __build_pipeline(
- model_name_scope='M_' + model,
- pipeline_params=params,
- raw_imgs_placeholder=raw_imgs)
-
- # logits_out = Integrated_Graph.__build_pipeline(
- # model_name_scope='M_' + model,
- # pipeline_params=params,
- # raw_imgs_placeholder=raw_imgs)
- try:
- final_logits = tf.concat([final_logits, logits_out], 1)
- except:
- final_logits = logits_out
-
- final_logits_named = tf.identity(final_logits, name='final_logits')
-
- graph = tf.get_default_graph()
-
- meta_graph_3 = tf.train.export_meta_graph(graph=graph_parent)
- meta_graph.import_scoped_meta_graph(meta_graph_3,
- import_scope='graph_parent')
-
- raw_imgs_name = [n.name for n in tf.get_default_graph().as_graph_def().node if 'raw_imgs' in n.name][0]
- raw_imgs_tf = graph.get_tensor_by_name(raw_imgs_name + ':0')
-
- logits_name = [n.name for n in tf.get_default_graph().as_graph_def().node if 'final_logit' in n.name][0]
- logits_concat = graph.get_tensor_by_name(logits_name + ':0')
-
- return raw_imgs_tf, logits_concat
-
- def build_finalGraph_and_return_final_tensors(hidden_units=None,
- y_data=None,
- primary_models_directory=None):
- def _new_weights(shape):
- with tf.name_scope('weights'):
- weights = tf.Variable(tf.truncated_normal(shape, stddev=0.05))
- return weights
-
- def _new_biases(length):
- with tf.name_scope('biases'):
- biases = tf.Variable(tf.constant(0.05, shape=[length]))
- return biases
-
- def new_fc_layer(inp,
- num_inputs,
- num_outputs,
- use_relu=True,
- use_drop_out=True,
- name_scope=''):
- with tf.name_scope(name_scope):
- weights = _new_weights(shape=[num_inputs, num_outputs])
- biases = _new_biases(length=num_outputs)
-
- layer = tf.matmul(inp, weights) + biases
-
- if use_drop_out:
- layer = tf.layers.dropout(layer, rate=0.05, training=use_drop_out)
-
- if use_relu:
- layer = tf.nn.relu(layer)
-
- return layer
-
- ##
- raw_imgs, concatenated_features = _build_architecture(
- models_directory=primary_models_directory)
- ##
- params_fc = {'hidden_units': hidden_units.copy(),
- 'y_data': y_data.copy()}
- ##
- graph_fc = tf.Graph()
- with graph_fc.as_default():
- X_tf = tf.placeholder(tf.float32, shape=[None, concatenated_features.get_shape().as_list()[1]], name='X_tf')
-
- #########################
- layer = None
- for n_layer, n_nodes in enumerate(params_fc['hidden_units']):
- if n_layer == 0:
- layer = new_fc_layer(X_tf,
- num_inputs=X_tf.get_shape().as_list()[1],
- num_outputs=n_nodes,
- name_scope='layer_' + str(n_layer + 1))
- else:
- layer = new_fc_layer(layer,
- num_inputs=layer.get_shape().as_list()[1],
- num_outputs=n_nodes,
- name_scope='layer_' + str(n_layer + 1))
-
- logits = new_fc_layer(layer,
- num_inputs=layer.get_shape().as_list()[1],
- num_outputs=params_fc['y_data'].shape[1],
- use_relu=False,
- use_drop_out=False,
- name_scope='output_layer')
-
- logits_fc = tf.identity(logits, name='logits_fc')
-
- ##
- graph = tf.get_default_graph()
-
- meta_graph_3 = tf.train.export_meta_graph(graph=graph_fc)
- meta_graph.import_scoped_meta_graph(meta_graph_3,
- input_map={"X_tf": concatenated_features},
- import_scope='DNN_fc')
-
- logits_fc = graph.get_tensor_by_name('DNN_fc/logits_fc:0')
- return raw_imgs, logits_fc
-
- return
-
-# raw_imgs, logits_fc = build_finalGraph_and_return_final_tensors(hidden_units=[500, 100],
-# y_data=y_train,
-# primary_models_directory='./logs/primary_models/')
-
-
-
-###########################
-##### prediction
-import tensorflow as tf
-from modules import LoadImg
-
-X_train, X_test, y_train, y_test, cls_indices = LoadImg.Dataset.prep_datasets(
- ver_ratio=0.2, container_path='data/ImageEveryUnit',
- final_img_width=224, final_img_height=224,
- color_mode="grayscale", random_state=1911, is_trial=True)
-
-with tf.Session() as session:
- writer = tf.summary.FileWriter('./trial/writer_prediction', session.graph)
- saver_3 = tf.train.import_meta_graph('./trial/best_model_main.meta',
- clear_devices=True)
- saver_3.restore(tf.get_default_session(),
- tf.train.latest_checkpoint('./trial'))
- graph_pred = tf.get_default_graph()
- raw_imgs = graph_pred.get_tensor_by_name("raw_imgs:0")
- final_logits = graph_pred.get_tensor_by_name("logits_tf:0")
-
- ##
- feed_dict_pred = {raw_imgs: X_train}
-
- ##
- logits = session.run(final_logits, feed_dict=feed_dict_pred)
- writer.close()
\ No newline at end of file
diff --git a/modules/ensemble_modules/logs/exported_model/1540929675/saved_model.pb b/modules/ensemble_modules/logs/exported_model/1540929675/saved_model.pb
deleted file mode 100644
index 3d8b2ce..0000000
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diff --git a/modules/ensemble_modules/obsolete_EnsenmbleData.py b/modules/ensemble_modules/obsolete_EnsenmbleData.py
deleted file mode 100644
index 6be4493..0000000
--- a/modules/ensemble_modules/obsolete_EnsenmbleData.py
+++ /dev/null
@@ -1,166 +0,0 @@
-from modules.prediction_modules import Prediction
-import os
-import tensorflow as tf
-import glob
-import numpy as np
-import pickle
-from modules import LoadImg
-import cv2
-from collections import OrderedDict
-
-
-def save_dictionary(data, path, file_name):
- if not os.path.exists(path):
- os.makedirs(path)
-
- with open(os.path.join(path, file_name), 'wb') as outfile:
- pickle.dump(data, outfile)
- return
-
-
-def find_required_datasets_dim(models_directory='./logs/primary_models/'):
- dims = []
- dims_dict = OrderedDict()
- models_info = OrderedDict()
- for i, m in enumerate(os.listdir(models_directory)):
- checkpoint_path = glob.glob(os.path.join(models_directory, m))[0]
-
- ##
- with tf.Session() as session:
- Prediction.Predict.restore_model(checkpoint_path=checkpoint_path, sess=session)
- graph = tf.get_default_graph()
- X_image_tf = graph.get_tensor_by_name("X_image_tf:0")
- image_shape = X_image_tf.get_shape().as_list()
- if image_shape[1:4] not in dims:
- dims.append(image_shape[1:4])
- models_info[m] = image_shape[1:4]
- tf.reset_default_graph()
- ##
- dims_dict['models_info'] = models_info
- dims_dict["ensemble_models_dims"] = dims
- # save_dictionary(data=dims_dict, path='./dumps', file_name='ensemble_models_dims.pkl')
- # with open('dumps/ensemble_models_dims.pkl', 'wb') as outfile:
- # pickle.dump(dims_dict, outfile)
- return dims_dict
-
-
-def prep_datasets(models_directory='./logs/primary_models/',
- data_path='data/ImageEveryUnit', ver_ratio=0.2):
- dims_dict = find_required_datasets_dim(models_directory=models_directory)
- # with open('dumps/ensemble_models_dims.pkl', 'rb') as pklFile:
- # dims_dict = pickle.load(pklFile)
-
- unique_dims = dims_dict['ensemble_models_dims']
-
- X_train, X_test, y_train, y_test, cls_indices = LoadImg.Dataset.prep_datasets(
- ver_ratio=ver_ratio, container_path=data_path,
- final_img_width=None, final_img_height=None,
- color_mode="grayscale", random_state=1911)
-
- data_dict = {}
- for dim in unique_dims:
- temp_dict = {}
-
- current_X_train = []
- for img_num in range(X_train.shape[0]):
- current_X_train.append(cv2.resize(X_train[img_num], dsize=(dim[0], dim[1])))
-
- current_X_test = []
- for img_num in range(X_test.shape[0]):
- current_X_test.append(cv2.resize(X_test[img_num], dsize=(dim[0], dim[1])))
-
- temp_dict['X_train'] = np.array(current_X_train)
- temp_dict['X_test'] = np.array(current_X_test)
- temp_dict['y_train'] = y_train
- temp_dict['y_test'] = y_test
- temp_dict['cls_indices'] = cls_indices
- data_dict[str(dim)] = temp_dict
- save_dictionary(data=data_dict, path='./data/ensembleDatasets',
- file_name='pre_ensembleData.pkl')
- return data_dict, dims_dict
-
-
-def prep_data_for_ensemble(models_directory='./logs/primary_models/',
- data_path='data/ImageEveryUnit',
- ver_ratio=0.2,
- save_folder='./data/ensembleDatasets',
- file_name='pre_ensembleData_final.pkl'):
- data_dict, dims_dict = prep_datasets(models_directory='./logs/primary_models/',
- data_path=data_path, ver_ratio=ver_ratio)
- # ##
- # with open('dumps/ensemble_models_dims.pkl', 'rb') as pklFile:
- # dims_dict = pickle.load(pklFile)
- #
- # with open(data_path, 'rb') as pklFile:
- # data_dict = pickle.load(pklFile)
-
- models_info = dims_dict['models_info']
-
- # logits_appended_train = np.array([])
- # logits_appended_test = np.array([])
-
- for model_folder, dims in models_info.items():
- tf.reset_default_graph()
- data = data_dict[str(dims)]
- X_train = data['X_train']
- X_test = data['X_test']
- y_train = data['y_train']
- y_test = data['y_test']
- cls_indices = data['cls_indices']
-
- checkpoint_path = os.path.join('./logs/primary_models/', model_folder)
- logits_pred_train, _, _ = Prediction. \
- Predict.predict_batch(checkpoint_path=checkpoint_path,
- X_pred=X_train,
- y_true=y_train,
- get_results_pandas=False)
- try:
- logits_appended_train = np.append(logits_appended_train, logits_pred_train, axis=1)
- except:
- logits_appended_train = logits_pred_train.copy()
-
- logits_pred_test, _, _ = Prediction. \
- Predict.predict_batch(checkpoint_path=checkpoint_path,
- X_pred=X_test,
- y_true=y_test,
- get_results_pandas=False)
- try:
- logits_appended_test = np.append(logits_appended_test, logits_pred_test, axis=1)
- except:
- logits_appended_test = logits_pred_test.copy()
-
- ##
- ensemble_data_dict = {}
- ensemble_data_dict['X_train'] = logits_appended_train
- ensemble_data_dict['y_train'] = y_train
- ensemble_data_dict['X_test'] = logits_appended_test
- ensemble_data_dict['y_test'] = y_test
- ensemble_data_dict['cls_indices'] = cls_indices
-
- save_dictionary(data=ensemble_data_dict, path=save_folder,
- file_name=file_name)
-
- return
-
-
-def do_all_data_prep_for_training():
- find_required_datasets_dim()
- print('The dims saved.')
- prep_datasets()
- print('The first data prep done.')
- prep_data_for_ensemble()
- print('The second data prep done.')
- return
-
-
-def load_ensemble_data(data_path='./data/ensembleDatasets/pre_ensembleData_final.pkl'):
- ##
- with open(data_path, 'rb') as pklFile:
- data_dict = pickle.load(pklFile)
- ##
- X_train = data_dict['X_train']
- X_test = data_dict['X_test']
- y_train = data_dict['y_train']
- y_test = data_dict['y_test']
- cls_indices = data_dict['cls_indices']
- return X_train, X_test, y_train, y_test, cls_indices
diff --git a/modules/ensemble_modules/trainer/CustomEnsembleEstimator.py b/modules/ensemble_modules/trainer/CustomEnsembleEstimator.py
deleted file mode 100644
index 2606b9f..0000000
--- a/modules/ensemble_modules/trainer/CustomEnsembleEstimator.py
+++ /dev/null
@@ -1,591 +0,0 @@
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import argparse
-import tensorflow as tf
-from modules import LoadImg
-import glob
-import os
-from tensorflow.python.framework import meta_graph
-import numpy as np
-
-from sklearn.datasets import load_files
-import numpy as np
-from sklearn.model_selection import train_test_split
-from keras.preprocessing import image
-import pandas as pd
-from MultiColProcessor import MultiColProcessor as mcp
-import pickle
-import json
-from collections import OrderedDict
-
-
-########################
-def create_parser():
- parser = argparse.ArgumentParser()
- parser.add_argument('--path_to_images', default='data/ImageEveryUnit',
- type=str,
- help='path to images (e.g. gs://...)')
- parser.add_argument('--primary_models_directory',
- default='./logs/primary_models/',
- type=str)
- parser.add_argument('--images_shape',
- default='[None, 224, 224, 3]',
- type=str)
- parser.add_argument('--hidden_units',
- default='[500, 100]',
- type=str)
- parser.add_argument('--learning_rate',
- default=3e4,
- type=float)
- parser.add_argument('--retrain_primary_models',
- default='False',
- type=str)
- parser.add_argument('--batch_size',
- default=6,
- type=int)
- parser.add_argument('--train_epochs',
- default=1,
- type=int)
- parser.add_argument('--epochs_between_evals',
- default=1,
- type=int)
- parser.add_argument('--export_dir',
- default='./logs/exported_model',
- type=str)
- parser.add_argument('--ensemble_architecture_path',
- default='./logs/temporary_models/',
- type=str)
- parser.add_argument('--metric',
- default='accuracy',
- type=str)
- parser.add_argument('--bin_path',
- default='dumps/',
- type=str)
- parser.add_argument('--dev',
- default='False',
- type=str)
- parser.add_argument('--color_mode',
- default='grayscale',
- type=str)
- parser.add_argument('--random_state',
- default=1911,
- type=int)
- return parser
-
-
-parser = create_parser()
-
-
-class Dataset():
- def __init__(self):
- self.category_mapper = {}
-
- @staticmethod
- def dump_pkl_MultiColProcessor(gauge_categories, bin_path):
- y_true_cat = pd.DataFrame(data=gauge_categories, columns=['y_true'], dtype='category')
- MultiColumnOneHotEncoder = mcp.MultiColomnOneHotEncoder()
- MultiColumnOneHotEncoder.fit(data=y_true_cat)
- with open(bin_path + 'MultiColProcessor.pkl', 'wb') as pklFile:
- pickle.dump(MultiColumnOneHotEncoder, pklFile)
- return
-
- @staticmethod
- def dump_json_category_mapper(data, bin_path):
- ##
- category_mapper = OrderedDict()
- category_mapper_num_to_cat = OrderedDict()
- category_mapper_cat_to_num = OrderedDict()
- for i in range(len(data['target_names'])):
- category_mapper_num_to_cat[i] = data['target_names'][i]
- for i in range(len(data['target_names'])):
- category_mapper_cat_to_num[data['target_names'][i]] = i
-
- ##
- category_mapper['num_to_cat'] = category_mapper_num_to_cat
- category_mapper['cat_to_num'] = category_mapper_cat_to_num
- category_mapper['num_classes'] = len(data['target_names'])
-
- Dataset.category_mapper = category_mapper
-
- with open(bin_path + 'category_mapper.json', 'w') as outfile:
- json.dump(category_mapper, outfile)
- return
-
- @staticmethod
- def load_dataset(path, bin_path):
- data = load_files(path, load_content=False)
-
- ## to save categories encoder
- Dataset.dump_json_category_mapper(data=data, bin_path=bin_path)
-
- ##
- guage_files = np.array(data['filenames'])
- gauge_categories = np.array(data['target'])
-
- ##
- Dataset.dump_pkl_MultiColProcessor(gauge_categories=gauge_categories, bin_path=bin_path)
-
- return guage_files, gauge_categories
-
- @staticmethod
- def split_data_files(ver_ratio, path, random_state, is_trial, bin_path):
- ##
- guage_files, gauge_categories = Dataset.load_dataset(path=path, bin_path=bin_path)
-
- if is_trial == True:
- guage_files = guage_files[:20]
- gauge_categories = gauge_categories[:20]
-
- #
- X_train_path_names, X_test_path_names, y_train, y_test = \
- train_test_split(guage_files,
- gauge_categories,
- test_size=ver_ratio,
- random_state=random_state)
- ##
- return X_train_path_names, X_test_path_names, y_train, y_test
-
- @staticmethod
- def path_to_tensor(img_path, img_size_x, img_size_y, color_mode):
- if img_size_x is None:
- img_size_x = 224
- if img_size_y is None:
- img_size_y = 224
- # loads RGB image as PIL.Image.Image type
- img = image.load_img(img_path, target_size=(img_size_y, img_size_x, color_mode))
- # convert PIL.Image.Image type to 3D tensor with shape (?, ?, ?)
- x = image.img_to_array(img)
- # convert 3D tensor to 4D tensor with shape (1, ?, ?, ?) and return 4D tensor
- return np.expand_dims(x, axis=0)
-
- @staticmethod
- def paths_to_tensor(imgs_path, img_size_x, img_size_y, color_mode):
- list_of_tensors = [Dataset.path_to_tensor(img_path, img_size_x, img_size_y, color_mode)
- for img_path in list(imgs_path)]
- return np.vstack(list_of_tensors)
-
- @staticmethod
- def find_cls_indices(train_y_data, test_y_data):
- ##
- num_classes = Dataset.category_mapper['num_classes']
-
- ##
- train_indices = OrderedDict()
- test_indices = OrderedDict()
- for cls in range(num_classes):
- label = Dataset.category_mapper['num_to_cat'][cls]
- train_indices[label] = train_y_data[:, cls] == True
- test_indices[label] = test_y_data[:, cls] == True
-
- ##
- cls_indices = OrderedDict()
- cls_indices['train_indices'] = train_indices
- cls_indices['test_indices'] = test_indices
-
- return cls_indices
-
- @classmethod
- def prep_datasets(cls, ver_ratio, container_path, final_img_width, final_img_height,
- color_mode='grayscale',
- random_state=19, is_trial=None, bin_path='dumps/'):
- ##
- X_train_path_names, X_test_path_names, y_train, y_test = \
- cls.split_data_files(ver_ratio=ver_ratio,
- path=container_path,
- random_state=random_state,
- is_trial=is_trial,
- bin_path=bin_path)
-
- X_train = cls.paths_to_tensor(imgs_path=X_train_path_names,
- img_size_x=final_img_width,
- img_size_y=final_img_height,
- color_mode=color_mode)
-
- X_test = cls.paths_to_tensor(imgs_path=X_test_path_names,
- img_size_x=final_img_width,
- img_size_y=final_img_height,
- color_mode=color_mode)
-
- ## OneHot encoding of y_train and y_test
- with open('dumps/MultiColProcessor.pkl', 'rb') as handle:
- MultiColumnOneHotEncoder = pickle.load(handle)
-
- y_train_cat = pd.DataFrame(data=y_train, columns=['y_true'], dtype='category')
- y_train = MultiColumnOneHotEncoder.transform(data=y_train_cat)
- y_test_cat = pd.DataFrame(data=y_test, columns=['y_true'], dtype='category')
- y_test = MultiColumnOneHotEncoder.transform(data=y_test_cat)
-
- ##
- cls_indices = cls.find_cls_indices(train_y_data=y_train.values, test_y_data=y_test.values)
-
- print("The image pre-processing is complete.")
-
- return X_train, X_test, y_train.values, y_test.values, cls_indices
-
-
-def input_fn_train(raw_imgs, labels, batch_size, epochs_between_evals):
- # Convert the inputs to a Dataset.
- dataset = tf.data.Dataset.from_tensor_slices(({'X': raw_imgs}, labels))
- # Shuffle, repeat, and batch the examples.
- dataset = dataset.cache().shuffle(100000).repeat(epochs_between_evals).batch(batch_size)
- # Return the read end of the pipeline.
- return dataset # dataset #dataset.make_one_shot_iterator().get_next()
-
-
-def input_fn_eval(raw_imgs, labels):
- dataset = tf.data.Dataset.from_tensor_slices(({'X': raw_imgs}, labels))
- dataset = dataset.batch(raw_imgs.shape[0])
- return dataset.make_one_shot_iterator().get_next()
-
-
-def create_ensemble_architecture(hidden_units=None,
- n_output=None,
- primary_models_directory=None,
- images_shape=None,
- save_path=None):
- class Ensemble():
- @staticmethod
- def __build_pipeline(model_name_scope=None,
- pipeline_params=None,
- raw_imgs_placeholder=None):
- graph_model = tf.Graph()
- with graph_model.as_default():
- ##################################
- with tf.Session(graph=graph_model) as sess:
- saver = tf.train.import_meta_graph(pipeline_params["checkpoint_file_path"],
- clear_devices=True,
- import_scope='CNN_model')
- saver.restore(tf.get_default_session(),
- tf.train.latest_checkpoint(pipeline_params["checkpoint_path"]))
-
- X_image_tf = graph_model.get_tensor_by_name("CNN_model/X_image_tf:0")
- logits_tf = graph_model.get_tensor_by_name("CNN_model/logits_tf:0")
- # logits_tf_sg = tf.stop_gradient(logits_tf)
- ####################################
-
- graph_pipeline = tf.Graph()
- with graph_pipeline.as_default():
- ##################################
- X_raw = tf.placeholder(tf.float32, shape=[None, None, None, None], name="X_raw")
- meta_graph.import_scoped_meta_graph(pipeline_params["checkpoint_file_path"],
- clear_devices=True,
- import_scope='img_size_info')
-
- X_image_tf = graph_pipeline.get_tensor_by_name("img_size_info/X_image_tf:0")
-
- resized_imgs = tf.identity(tf.image.resize_images(X_raw, (X_image_tf.get_shape().as_list()[1],
- X_image_tf.get_shape().as_list()[2])),
- name='resized_imgs')
- ####################################
-
- graph = tf.get_default_graph()
-
- raw_imgs = raw_imgs_placeholder
-
- meta_graph_1 = tf.train.export_meta_graph(graph=graph_pipeline)
- meta_graph.import_scoped_meta_graph(meta_graph_1,
- input_map={"X_raw": raw_imgs},
- import_scope=model_name_scope + '_img_pipeline')
-
- out_1 = graph.get_tensor_by_name(model_name_scope + '_img_pipeline' + '/resized_imgs:0')
-
- meta_graph_2 = tf.train.export_meta_graph(graph=graph_model)
- meta_graph.import_scoped_meta_graph(meta_graph_2,
- input_map={"CNN_model/X_image_tf": out_1},
- import_scope=model_name_scope + '_CNN')
-
- out_2 = graph.get_tensor_by_name(model_name_scope + '_CNN' + '/CNN_model/logits_tf:0')
-
- return out_2
-
- @staticmethod
- def _combine_all_channel(models_directory=None, images_shape=None):
- graph_parent = tf.Graph()
- with graph_parent.as_default():
- raw_imgs = tf.placeholder(tf.float32, shape=[None, None, None, None], name='raw_imgs')
- for i, model in enumerate(os.listdir(models_directory)):
- checkpoint_path = glob.glob(os.path.join(models_directory, model))[0]
- checkpoint_file_path = glob.glob(os.path.join(checkpoint_path, '*.meta'))[0]
- params = {"checkpoint_path": checkpoint_path,
- "checkpoint_file_path": checkpoint_file_path}
-
- logits_out = Ensemble.__build_pipeline(
- model_name_scope='M_' + model,
- pipeline_params=params,
- raw_imgs_placeholder=raw_imgs)
-
- try:
- final_logits = tf.concat([final_logits, logits_out], 1)
- except:
- final_logits = logits_out
-
- final_logits_named = tf.identity(final_logits, name='final_logits')
-
- graph = tf.get_default_graph()
-
- raw_imgs_in_main_graph = tf.placeholder(tf.float32, shape=images_shape, name='raw_imgs')
-
- meta_graph_3 = tf.train.export_meta_graph(graph=graph_parent)
- meta_graph.import_scoped_meta_graph(meta_graph_3,
- input_map={"raw_imgs": raw_imgs_in_main_graph},
- import_scope='graph_parent')
-
- # raw_imgs_name = [n.name for n in tf.get_default_graph().as_graph_def().node if 'raw_imgs' in n.name][0]
- # raw_imgs_tf = graph.get_tensor_by_name(raw_imgs_name + ':0')
-
- logits_name = [n.name for n in tf.get_default_graph().as_graph_def().node if 'final_logit' in n.name][0]
- logits_concat = graph.get_tensor_by_name(logits_name + ':0')
-
- return raw_imgs_in_main_graph, logits_concat
-
- @classmethod
- def build_finalGraph_and_return_final_tensors(cls,
- hidden_units=None,
- n_output=None,
- primary_models_directory=None,
- images_shape=None):
- def _new_weights(shape):
- with tf.name_scope('weights_ensemble'):
- weights = tf.Variable(tf.truncated_normal(shape, stddev=0.05))
- return weights
-
- def _new_biases(length):
- with tf.name_scope('biases_ensemble'):
- biases = tf.Variable(tf.constant(0.05, shape=[length]))
- return biases
-
- def new_fc_layer(inp,
- num_inputs,
- num_outputs,
- use_relu=True,
- use_drop_out=True,
- name_scope=''):
- with tf.name_scope(name_scope):
- weights = _new_weights(shape=[num_inputs, num_outputs])
- biases = _new_biases(length=num_outputs)
-
- layer = tf.matmul(inp, weights) + biases
-
- if use_drop_out:
- layer = tf.layers.dropout(layer, rate=0.05, training=use_drop_out)
-
- if use_relu:
- layer = tf.nn.relu(layer)
-
- return layer
-
- ##
- raw_imgs, concatenated_features = cls._combine_all_channel(
- models_directory=primary_models_directory, images_shape=images_shape)
- ##
- params_fc = {'hidden_units': hidden_units.copy(),
- 'n_output': n_output}
- ##
- graph_fc = tf.Graph()
- with graph_fc.as_default():
- X_tf = tf.placeholder(tf.float32, shape=[None, concatenated_features.get_shape().as_list()[1]],
- name='X_tf')
-
- #########################
- layer = None
- for n_layer, n_nodes in enumerate(params_fc['hidden_units']):
- if n_layer == 0:
- layer = new_fc_layer(X_tf,
- num_inputs=X_tf.get_shape().as_list()[1],
- num_outputs=n_nodes,
- name_scope='layer_' + str(n_layer + 1))
- else:
- layer = new_fc_layer(layer,
- num_inputs=layer.get_shape().as_list()[1],
- num_outputs=n_nodes,
- name_scope='layer_' + str(n_layer + 1))
-
- logits = new_fc_layer(layer,
- num_inputs=layer.get_shape().as_list()[1],
- num_outputs=params_fc['n_output'],
- use_relu=False,
- use_drop_out=False,
- name_scope='output_layer')
-
- logits_fc = tf.identity(logits, name='logits_tf')
-
- ##
- graph = tf.get_default_graph()
-
- meta_graph_3 = tf.train.export_meta_graph(graph=graph_fc)
- meta_graph.import_scoped_meta_graph(meta_graph_3,
- input_map={"X_tf": concatenated_features},
- import_scope='')
-
- logits_fc = graph.get_tensor_by_name('logits_tf:0')
- return raw_imgs, logits_fc
-
- ## to create the ensemble architecture from the primary models
- tf.reset_default_graph()
- ##
- _, _ = Ensemble.build_finalGraph_and_return_final_tensors(
- hidden_units=hidden_units,
- n_output=n_output,
- primary_models_directory=primary_models_directory,
- images_shape=images_shape)
- saver = tf.train.Saver(max_to_keep=1)
- with tf.Session() as sess:
- sess.run(tf.global_variables_initializer())
- saver.save(sess, os.path.join(save_path, 'ensemble_architecture_' + 'main'))
- tf.reset_default_graph()
- return
-
-
-def ensemble_model(features, labels, mode, params):
- ######### dev
- # params = {'primary_models_directory': './logs/primary_models/',
- # 'writer_path': './trial/writer',
- # 'save_model_path': './trial/best_model_main',
- # 'number_of_categories': labels.shape[1],
- # 'images_shape': [None, 224, 224, 3],
- # 'hidden_units': [500, 100],
- # 'n_output': labels.shape[1],
- # 'epochs': 10,
- # 'learning_rate': 3e-4}
-
- #########
-
- graph_ensemble = tf.Graph()
- with tf.Session(graph=graph_ensemble) as sess:
- meta_graph_path = glob.glob(os.path.join(params["ensemble_architecture_path"], '*.meta'))[0]
- loader = tf.train.import_meta_graph(meta_graph_path, clear_devices=True)
- loader.restore(sess, tf.train.latest_checkpoint(params["ensemble_architecture_path"]))
-
- graph = tf.get_default_graph()
-
- meta_graph_0 = tf.train.export_meta_graph(graph=graph_ensemble)
- meta_graph.import_scoped_meta_graph(meta_graph_0,
- input_map={"raw_imgs": features['X']},
- import_scope='main_graph')
-
- logits = graph.get_tensor_by_name('main_graph/logits_tf:0')
-
- predicted_classes = tf.argmax(logits, 1)
-
- if mode == tf.estimator.ModeKeys.PREDICT:
- predictions = {
- 'class_ids': predicted_classes[:, tf.newaxis],
- 'probabilities': tf.nn.softmax(logits),
- 'logits': logits,
- }
- return tf.estimator.EstimatorSpec(mode, predictions=predictions)
-
- cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(labels=labels,
- logits=logits,
- name='cross_entropy')
- loss = tf.reduce_mean(cross_entropy, name='cost_fc')
-
- accuracy = tf.metrics.accuracy(labels=tf.argmax(labels, 1),
- predictions=predicted_classes,
- name='acc_op')
-
- metrics = {'accuracy': accuracy}
- tf.summary.scalar('accuracy', accuracy[1])
-
- if mode == tf.estimator.ModeKeys.EVAL:
- return tf.estimator.EstimatorSpec(
- mode, loss=loss, eval_metric_ops=metrics)
-
- assert mode == tf.estimator.ModeKeys.TRAIN
-
- if params['retrain_primary_models'] != True:
- trainable_variables = [v for v in tf.trainable_variables() if 'ensemble' in v.name]
- else:
- trainable_variables = [v for v in tf.trainable_variables()]
-
- ###### trial
- print('there are {} DDDDDDDDDDDD'.format(len(trainable_variables)))
- ######
-
- optimizer = tf.train.AdamOptimizer(learning_rate=params['learning_rate'], name='adam_fc')
- train_op = optimizer.minimize(loss, var_list=trainable_variables,
- global_step=tf.train.get_or_create_global_step())
- return tf.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op)
-
-
-def main(argv):
- args = parser.parse_args(argv[1:])
-
- ##
- images_shape = eval(args.images_shape)
- path_to_images = args.path_to_images
- color_mode = args.color_mode
- bin_path = args.bin_path
- is_trial = args.dev == 'True'
- primary_models_directory = args.primary_models_directory
- hidden_units = eval(args.hidden_units)
- ensemble_architecture_path = args.ensemble_architecture_path
- learning_rate = args.learning_rate
- retrain_primary_models = args.retrain_primary_models == 'True'
- train_epochs = args.train_epochs
- epochs_between_evals = args.epochs_between_evals
- batch_size = args.batch_size
- export_dir = args.export_dir
- metric = args.metric
- ##
-
- # Fetch the data
- print('loading image data ...')
- X_train, X_test, y_train, y_test, _ = Dataset.prep_datasets(
- ver_ratio=0.2, container_path=path_to_images,
- final_img_width=images_shape[2], final_img_height=images_shape[1],
- color_mode=color_mode, random_state=1911, bin_path=bin_path, is_trial=is_trial)
-
- create_ensemble_architecture(hidden_units=hidden_units,
- n_output=y_train.shape[1],
- primary_models_directory=primary_models_directory,
- images_shape=images_shape,
- save_path=ensemble_architecture_path)
-
- classifier = tf.estimator.Estimator(
- model_fn=ensemble_model,
- params={
- 'primary_models_directory': primary_models_directory,
- 'images_shape': images_shape,
- 'hidden_units': hidden_units,
- 'learning_rate': learning_rate,
- 'ensemble_architecture_path': ensemble_architecture_path,
- 'retrain_primary_models': retrain_primary_models
- })
-
- # Train and evaluate model.
- model_criteria = 0.0
- image = tf.placeholder(tf.float32, shape=images_shape, name='export_input_image')
- input_fn = tf.estimator.export.build_raw_serving_input_receiver_fn({'X': image})
- ##
- for i in range(train_epochs // epochs_between_evals):
- print('epoch {} .........'.format(i * epochs_between_evals + 1))
- classifier.train(
- input_fn=lambda: input_fn_train(
- raw_imgs=X_train, labels=y_train,
- batch_size=batch_size,
- epochs_between_evals=epochs_between_evals))
-
- eval_result = classifier.evaluate(
- input_fn=lambda: input_fn_eval(raw_imgs=X_test, labels=y_test))
- print('')
- print('')
- print('current validation dataset accuracy is: {}'.format(eval_result['accuracy']))
- print('current highest validation dataset accuracy is: {}'.format(model_criteria))
- if eval_result[metric] > model_criteria:
- model_criteria = eval_result[metric].copy()
- print('current highest validation dataset accuracy updated to: {}'.format(model_criteria))
- print('')
- print('')
- classifier.export_savedmodel(export_dir, input_fn, strip_default_attrs=True)
- print('model updated')
- continue
- print('')
- print('')
-
-
-if __name__ == '__main__':
- tf.logging.set_verbosity(tf.logging.INFO)
- tf.app.run(main)
diff --git a/modules/ensemble_modules/trainer/LoadImg.py b/modules/ensemble_modules/trainer/LoadImg.py
deleted file mode 100644
index b7bd829..0000000
--- a/modules/ensemble_modules/trainer/LoadImg.py
+++ /dev/null
@@ -1,183 +0,0 @@
-from sklearn.datasets import load_files
-import numpy as np
-from sklearn.model_selection import train_test_split
-from keras.preprocessing import image
-import pandas as pd
-from MultiColProcessor import MultiColProcessor as mcp
-import pickle
-import json
-from collections import OrderedDict
-
-
-class Dataset(object):
- def __init__(self):
- self.category_mapper = {}
-
- @staticmethod
- def dump_pkl_MultiColProcessor(gauge_categories, bin_path):
- y_true_cat = pd.DataFrame(data=gauge_categories, columns=['y_true'], dtype='category')
- MultiColumnOneHotEncoder = mcp.MultiColomnOneHotEncoder()
- MultiColumnOneHotEncoder.fit(data=y_true_cat)
- with open(bin_path+'MultiColProcessor.pkl', 'wb') as pklFile:
- pickle.dump(MultiColumnOneHotEncoder, pklFile)
- return
-
- @staticmethod
- def dump_json_category_mapper(data, bin_path):
- ##
- category_mapper = OrderedDict()
- category_mapper_num_to_cat = OrderedDict()
- category_mapper_cat_to_num = OrderedDict()
- for i in range(len(data['target_names'])):
- category_mapper_num_to_cat[i] = data['target_names'][i]
- for i in range(len(data['target_names'])):
- category_mapper_cat_to_num[data['target_names'][i]] = i
-
- ##
- category_mapper['num_to_cat'] = category_mapper_num_to_cat
- category_mapper['cat_to_num'] = category_mapper_cat_to_num
- category_mapper['num_classes'] = len(data['target_names'])
-
- Dataset.category_mapper = category_mapper
-
- with open(bin_path+'category_mapper.json', 'w') as outfile:
- json.dump(category_mapper, outfile)
- return
-
- @staticmethod
- def load_dataset(path, bin_path):
- data = load_files(path, load_content=False)
-
- ## to save categories encoder
- Dataset.dump_json_category_mapper(data=data, bin_path=bin_path)
-
- ##
- guage_files = np.array(data['filenames'])
- gauge_categories = np.array(data['target'])
-
- ##
- Dataset.dump_pkl_MultiColProcessor(gauge_categories=gauge_categories, bin_path=bin_path)
-
- return guage_files, gauge_categories
-
- @staticmethod
- def split_data_files(ver_ratio, path, random_state, is_trial, bin_path):
- ##
- guage_files, gauge_categories = Dataset.load_dataset(path=path, bin_path=bin_path)
-
- if is_trial:
- guage_files = guage_files[:20]
- gauge_categories = gauge_categories[:20]
-
-
- #
- X_train_path_names, X_test_path_names, y_train, y_test = \
- train_test_split(guage_files,
- gauge_categories,
- test_size=ver_ratio,
- random_state=random_state)
- ##
- return X_train_path_names, X_test_path_names, y_train, y_test
-
- @staticmethod
- def path_to_tensor(img_path, img_size_x, img_size_y, color_mode):
- if img_size_x is None:
- img_size_x = 224
- if img_size_y is None:
- img_size_y = 224
- # loads RGB image as PIL.Image.Image type
- img = image.load_img(img_path, target_size=(img_size_y, img_size_x, color_mode))
- # convert PIL.Image.Image type to 3D tensor with shape (?, ?, ?)
- x = image.img_to_array(img)
- # convert 3D tensor to 4D tensor with shape (1, ?, ?, ?) and return 4D tensor
- return np.expand_dims(x, axis=0)
-
- @staticmethod
- def paths_to_tensor(imgs_path, img_size_x, img_size_y, color_mode):
- list_of_tensors = [Dataset.path_to_tensor(img_path, img_size_x, img_size_y, color_mode)
- for img_path in list(imgs_path)]
- return np.vstack(list_of_tensors)
-
- @staticmethod
- def find_cls_indices(train_y_data, test_y_data):
- ##
- num_classes = Dataset.category_mapper['num_classes']
-
- ##
- train_indices = OrderedDict()
- test_indices = OrderedDict()
- for cls in range(num_classes):
- label = Dataset.category_mapper['num_to_cat'][cls]
- train_indices[label] = train_y_data[:, cls] == True
- test_indices[label] = test_y_data[:, cls] == True
-
- ##
- cls_indices = OrderedDict()
- cls_indices['train_indices'] = train_indices
- cls_indices['test_indices'] = test_indices
-
- return cls_indices
-
- @classmethod
- def prep_datasets(cls, ver_ratio, container_path, final_img_width, final_img_height,
- color_mode='grayscale',
- random_state=19, is_trial=False, bin_path='dumps/'):
- ##
- X_train_path_names, X_test_path_names, y_train, y_test = \
- cls.split_data_files(ver_ratio=ver_ratio,
- path=container_path,
- random_state=random_state,
- is_trial=is_trial,
- bin_path=bin_path)
-
- X_train = cls.paths_to_tensor(imgs_path=X_train_path_names,
- img_size_x=final_img_width,
- img_size_y=final_img_height,
- color_mode=color_mode)
-
- X_test = cls.paths_to_tensor(imgs_path=X_test_path_names,
- img_size_x=final_img_width,
- img_size_y=final_img_height,
- color_mode=color_mode)
-
- ## OneHot encoding of y_train and y_test
- with open('dumps/MultiColProcessor.pkl', 'rb') as handle:
- MultiColumnOneHotEncoder = pickle.load(handle)
-
- y_train_cat = pd.DataFrame(data=y_train, columns=['y_true'], dtype='category')
- y_train = MultiColumnOneHotEncoder.transform(data=y_train_cat)
- y_test_cat = pd.DataFrame(data=y_test, columns=['y_true'], dtype='category')
- y_test = MultiColumnOneHotEncoder.transform(data=y_test_cat)
-
- ##
- cls_indices = cls.find_cls_indices(train_y_data=y_train.values, test_y_data=y_test.values)
-
- print("The image pre-processing is complete.")
-
- return X_train, X_test, y_train.values, y_test.values, cls_indices
-
- # @classmethod
- # def prep_datasets_for_ensemble(cls, ver_ratio, container_path, final_img_width, final_img_height,
- # color_mode='grayscale',
- # random_state=19, is_trial=False, bin_path='dump/'):
- # ##
- # X_train_path_names, X_test_path_names, y_train, y_test = \
- # cls.split_data_files(ver_ratio=ver_ratio,
- # path=container_path,
- # random_state=random_state,
- # is_trial=is_trial,
- # bin_path=bin_path)
- #
- # X_train = cls.paths_to_tensor(imgs_path=X_train_path_names,
- # img_size_x=final_img_width,
- # img_size_y=final_img_height,
- # color_mode=color_mode)
- #
- # X_test = cls.paths_to_tensor(imgs_path=X_test_path_names,
- # img_size_x=final_img_width,
- # img_size_y=final_img_height,
- # color_mode=color_mode)
- #
- # print("The image pre-processing for ensemble is complete.")
- #
- # return X_train, X_test, y_train, y_test
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diff --git a/modules/ensemble_modules/trainer_from_storage/input.py b/modules/ensemble_modules/trainer_from_storage/input.py
deleted file mode 100644
index 749ea52..0000000
--- a/modules/ensemble_modules/trainer_from_storage/input.py
+++ /dev/null
@@ -1,166 +0,0 @@
-from sklearn.datasets import load_files
-import numpy as np
-from sklearn.model_selection import train_test_split
-import pandas as pd
-from MultiColProcessor import MultiColProcessor as mcp
-import pickle
-import json
-from collections import OrderedDict
-import tensorflow as tf
-import multiprocessing
-
-
-class Dataset():
- @staticmethod
- def dump_pkl_MultiColProcessor(gauge_categories, bin_path):
- y_true_cat = pd.DataFrame(data=gauge_categories, columns=['y_true'], dtype='category')
- MultiColumnOneHotEncoder = mcp.MultiColomnOneHotEncoder()
- MultiColumnOneHotEncoder.fit(data=y_true_cat)
- with open(bin_path + 'MultiColProcessor.pkl', 'wb') as pklFile:
- pickle.dump(MultiColumnOneHotEncoder, pklFile)
- return
-
- @staticmethod
- def dump_json_category_mapper(data, bin_path):
- ##
- category_mapper = OrderedDict()
- category_mapper_num_to_cat = OrderedDict()
- category_mapper_cat_to_num = OrderedDict()
- for i in range(len(data['target_names'])):
- category_mapper_num_to_cat[i] = data['target_names'][i]
- for i in range(len(data['target_names'])):
- category_mapper_cat_to_num[data['target_names'][i]] = i
-
- ##
- category_mapper['num_to_cat'] = category_mapper_num_to_cat
- category_mapper['cat_to_num'] = category_mapper_cat_to_num
- category_mapper['num_classes'] = len(data['target_names'])
-
- Dataset.category_mapper = category_mapper
-
- with open(bin_path + 'category_mapper.json', 'w') as outfile:
- json.dump(category_mapper, outfile)
- return
-
- @staticmethod
- def load_dataset(path, bin_path):
- data = load_files(path, load_content=False)
-
- ## to save categories encoder
- Dataset.dump_json_category_mapper(data=data, bin_path=bin_path)
-
- ##
- guage_files = np.array(data['filenames'])
- gauge_categories = np.array(data['target'])
-
- ##
- Dataset.dump_pkl_MultiColProcessor(gauge_categories=gauge_categories, bin_path=bin_path)
-
- return guage_files, gauge_categories
-
- @staticmethod
- def split_data_files(ver_ratio, path, random_state, is_trial, bin_path):
- ##
- guage_files, gauge_categories = Dataset.load_dataset(path=path, bin_path=bin_path)
-
- if is_trial:
- guage_files = guage_files[:20]
- gauge_categories = gauge_categories[:20]
-
- #
- X_train_path_names, X_test_path_names, y_train, y_test = \
- train_test_split(guage_files,
- gauge_categories,
- test_size=ver_ratio,
- random_state=random_state)
- ##
- return X_train_path_names, X_test_path_names, y_train, y_test
-
- @staticmethod
- def parse_function(filename, label):
- image_string = tf.read_file(filename)
- image = tf.image.decode_jpeg(image_string, channels=3)
- image = tf.expand_dims(image, 0)
- image = tf.image.resize_bilinear(image, [224, 224])
- image = tf.squeeze(image, 0)
- image = tf.image.convert_image_dtype(image, tf.float32)
- return {'X': image}, label
-
- @classmethod
- def prep_train_input_function(cls, ver_ratio, container_path,
- prefetch_buffer_size,
- color_mode='grayscale',
- epochs_between_evals=None,
- random_state=19,
- is_trial=False,
- bin_path=None,
- multi_threading=True,
- train_batch_size=None):
- X_train_path_names, _, y_train, _ = \
- cls.split_data_files(ver_ratio=ver_ratio,
- path=container_path,
- random_state=random_state,
- is_trial=is_trial,
- bin_path=bin_path)
- ##
- ## OneHot encoding of y_train and y_test
- with open(bin_path + '/MultiColProcessor.pkl', 'rb') as handle:
- MultiColumnOneHotEncoder = pickle.load(handle)
-
- y_train_cat = pd.DataFrame(data=y_train, columns=['y_true'], dtype='category')
- y_train = MultiColumnOneHotEncoder.transform(data=y_train_cat)
- y_train = y_train.values
- ##
- num_threads = multiprocessing.cpu_count() if multi_threading else 1
-
- X_train_path_names_tf = tf.constant(X_train_path_names)
- y_train_tf = tf.constant(y_train)
-
- dataset_train = tf.data.Dataset.from_tensor_slices((X_train_path_names_tf, y_train_tf))
-
- ##
- dataset_train = dataset_train.apply(
- tf.contrib.data.map_and_batch(
- map_func=cls.parse_function,
- batch_size=train_batch_size,
- num_parallel_batches=num_threads))
-
- dataset_train = dataset_train.\
- cache().shuffle(len(X_train_path_names) + 10).repeat(epochs_between_evals)#.batch(batch_size)
- #
- dataset_train = dataset_train.prefetch(buffer_size=prefetch_buffer_size)
-
- return dataset_train
-
- @classmethod
- def prep_eval_input_function(cls, ver_ratio, container_path,
- random_state=19,
- is_trial=False,
- bin_path=None,
- multi_threading=True):
- _, X_test_path_names, _, y_test = \
- cls.split_data_files(ver_ratio=ver_ratio,
- path=container_path,
- random_state=random_state,
- is_trial=is_trial,
- bin_path=bin_path)
- ##
- with open(bin_path + '/MultiColProcessor.pkl', 'rb') as handle:
- MultiColumnOneHotEncoder = pickle.load(handle)
-
- y_test_cat = pd.DataFrame(data=y_test, columns=['y_true'], dtype='category')
- y_test = MultiColumnOneHotEncoder.transform(data=y_test_cat)
- y_test = y_test.values
- ##
- X_test_path_names_tf = tf.constant(X_test_path_names)
- y_test_tf = tf.constant(y_test)
-
- num_threads = multiprocessing.cpu_count() if multi_threading else 1
- dataset_test = tf.data.Dataset.from_tensor_slices((X_test_path_names_tf, y_test_tf))
-
- dataset_test = dataset_test.map(map_func=cls.parse_function,
- num_parallel_calls=num_threads)
-
- dataset_test = dataset_test.batch(y_test.shape[0])
-
- return dataset_test
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/dumpsMultiColProcessor.pkl b/modules/ensemble_modules/trainer_from_storage/logs/dumpsMultiColProcessor.pkl
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/2nd_good/best_model_main.meta b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/2nd_good/best_model_main.meta
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/2nd_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/2nd_good/checkpoint
deleted file mode 100644
index 6e74726..0000000
--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/2nd_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/best_model_main.index b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/best_model_main.index
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/checkpoint
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/hyper_params_main.json
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 160, "img_size_y": 80, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/1st_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/1st_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/1st_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/1st_good/checkpoint
deleted file mode 100644
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/1st_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/best_model_main.meta b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/best_model_main.meta
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/checkpoint
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/checkpoint
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/hyper_params_main.json
deleted file mode 100644
index 939c525..0000000
--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 500, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 237, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/checkpoint
deleted file mode 100644
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/hyper_params_main.json
deleted file mode 100644
index c2ef0b8..0000000
--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 158, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/checkpoint
deleted file mode 100644
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/hyper_params_main.json
deleted file mode 100644
index a073988..0000000
--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 158, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/checkpoint
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/hyper_params_main.json
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 237, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/checkpoint
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/hyper_params_main.json
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 80, "img_size_y": 160, "num_channels": 3}
\ No newline at end of file
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index c843a4a..0000000
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/checkpoint
deleted file mode 100644
index 6e74726..0000000
--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/hyper_params_main.json
deleted file mode 100644
index 1cdbb46..0000000
--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 160, "img_size_y": 80, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/checkpoint
deleted file mode 100644
index fd39759..0000000
--- a/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main"
-all_model_checkpoint_paths: "/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main.data-00000-of-00001
deleted file mode 100644
index 3a9ad9d..0000000
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main.index b/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main.index
deleted file mode 100644
index b1f6576..0000000
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main.meta b/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main.meta
deleted file mode 100644
index cbd80cc..0000000
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diff --git a/modules/ensemble_modules/trainer_from_storage/task.py b/modules/ensemble_modules/trainer_from_storage/task.py
deleted file mode 100644
index f5e3f27..0000000
--- a/modules/ensemble_modules/trainer_from_storage/task.py
+++ /dev/null
@@ -1,173 +0,0 @@
-import argparse
-import tensorflow as tf
-
-## on
-from trainer_from_storage.input import Dataset
-from trainer_from_storage import model
-
-## dev
-# from modules.ensemble_modules.trainer_from_storage.input import Dataset
-# from modules.ensemble_modules.trainer_from_storage import model
-
-##
-def initialise_hyper_params(parser):
- parser.add_argument('--path_to_images', default='data/ImageEveryUnit',
- type=str,
- help='path to images (e.g. gs://...)')
- parser.add_argument('--primary_models_directory',
- default='./logs/primary_models/',
- type=str)
- parser.add_argument('--images_shape',
- default='[None, 224, 224, 3]',
- type=str)
- parser.add_argument('--hidden_units',
- default='[20, 30]',
- type=str)
- parser.add_argument('--learning_rate',
- default=.01,
- type=float)
- parser.add_argument('--retrain_primary_models',
- choices=['True', 'False'],
- default='False',
- type=str)
- parser.add_argument('--batch_size',
- default=2,
- type=int)
- parser.add_argument('--train_epochs',
- default=1,
- type=int)
- parser.add_argument('--epochs_between_evals',
- default=1,
- type=int)
- parser.add_argument('--export_dir',
- default='./logs/exported_model',
- type=str)
- parser.add_argument('--ensemble_architecture_path',
- default='./logs/temporary_models/',
- type=str)
- parser.add_argument('--metric',
- default='accuracy',
- type=str)
- parser.add_argument('--bin_path',
- default='dumps/',
- type=str)
- parser.add_argument('--dev',
- choices=['True', 'False'],
- default='False',
- type=str)
- parser.add_argument('--color_mode',
- default='grayscale',
- type=str)
- parser.add_argument('--random_state',
- default=1911,
- type=int)
- parser.add_argument('--prefetch_buffer_size',
- default=1700000,
- type=int)
- parser.add_argument('--verbosity',
- choices=[
- 'DEBUG',
- 'ERROR',
- 'FATAL',
- 'INFO',
- 'WARN'
- ],
- default='INFO')
- parser.add_argument('--image_processing_multi_threading',
- choices=['True', 'False'],
- default='True',
- type=str
- )
- return parser
-
-##
-def main(argv):
- args = HYPER_PARAMS.parse_args(argv[1:])
-
- ##
- images_shape = eval(args.images_shape)
- path_to_images = args.path_to_images
- color_mode = args.color_mode
- bin_path = args.bin_path
- is_trial = args.dev == 'True'
- primary_models_directory = args.primary_models_directory
- hidden_units = eval(args.hidden_units)
- ensemble_architecture_path = args.ensemble_architecture_path
- learning_rate = args.learning_rate
- retrain_primary_models = args.retrain_primary_models == 'True'
- train_epochs = args.train_epochs
- epochs_between_evals = args.epochs_between_evals
- batch_size = args.batch_size
- export_dir = args.export_dir
- metric = args.metric
- prefetch_buffer_size = args.prefetch_buffer_size
- image_processing_multi_threading = args.image_processing_multi_threading == 'True'
-
- ##
- tf.logging.set_verbosity(args.verbosity)
-
- model.create_ensemble_architecture(hidden_units=hidden_units,
- n_output=31,
- primary_models_directory=primary_models_directory,
- images_shape=images_shape,
- save_path=ensemble_architecture_path)
-
- classifier = tf.estimator.Estimator(
- model_fn=model.model_fn,
- params={
- 'primary_models_directory': primary_models_directory,
- 'images_shape': images_shape,
- 'hidden_units': hidden_units,
- 'learning_rate': learning_rate,
- 'ensemble_architecture_path': ensemble_architecture_path,
- 'retrain_primary_models': retrain_primary_models
- })
-
- # Train and evaluate model.
- model_criteria = 0.0
- image = tf.placeholder(tf.float32, shape=images_shape, name='export_input_image')
- input_fn = tf.estimator.export.build_raw_serving_input_receiver_fn({'X': image})
- ##
- for i in range(train_epochs // epochs_between_evals):
- print('epoch {} .........'.format(i * epochs_between_evals + 1))
- classifier.train(input_fn=lambda: Dataset.prep_train_input_function(
- ver_ratio=0.2,
- container_path=path_to_images,
- prefetch_buffer_size=prefetch_buffer_size,
- epochs_between_evals=epochs_between_evals,
- random_state=19,
- is_trial=is_trial,
- bin_path=bin_path,
- multi_threading=image_processing_multi_threading,
- train_batch_size=batch_size))
-
- eval_result = classifier.evaluate(input_fn=lambda: Dataset.prep_eval_input_function(
- ver_ratio=0.2,
- container_path=path_to_images,
- random_state=19,
- is_trial=is_trial,
- bin_path=bin_path,
- multi_threading=image_processing_multi_threading))
- print('')
- print('')
- print('current validation dataset accuracy is: {}'.format(eval_result['accuracy']))
- print('current highest validation dataset accuracy is: {}'.format(model_criteria))
- if eval_result[metric] > model_criteria:
- model_criteria = eval_result[metric].copy()
- print('current highest validation dataset accuracy updated to: {}'.format(model_criteria))
- print('')
- print('')
- classifier.export_savedmodel(export_dir, input_fn, strip_default_attrs=True)
- print('model updated')
- continue
- print('')
- print('')
-
-##
-args_parser = argparse.ArgumentParser()
-HYPER_PARAMS = initialise_hyper_params(args_parser)
-
-##
-if __name__ == '__main__':
- tf.logging.set_verbosity(tf.logging.INFO)
- tf.app.run(main)
diff --git a/prediction_batch.py b/prediction_batch.py
deleted file mode 100644
index e2f39a8..0000000
--- a/prediction_batch.py
+++ /dev/null
@@ -1,14 +0,0 @@
-from modules.prediction_modules import LoadImgPred
-from modules.prediction_modules import Prediction
-import numpy as np
-
-# The color_mode is either 'rgb' or 'grayscale' (default).
-X_pred, y_true, guage_files = LoadImgPred.DatasetForPrediction.return_datasets(
- container_path='data/testData_PILed',
- final_img_width=80,
- final_img_height=80*2, color_mode="grayscale")
-#'./logs/models/main/'
-logits_pred, pred_acc, pandas_final_result = Prediction. \
- Predict.predict_batch(checkpoint_path='./logs/primary_models/8th_good',
- X_pred=X_pred,
- y_true=y_true)
diff --git a/prediction_online.py b/prediction_online.py
deleted file mode 100644
index 2021129..0000000
--- a/prediction_online.py
+++ /dev/null
@@ -1,6 +0,0 @@
-from modules.prediction_modules import Prediction
-
-Prediction.Predict.predict_online(checkpoint_path='./logs/models/main/',
- final_img_width=80,
- final_img_height=160,
- color_mode="grayscale")
diff --git a/requirements.txt b/requirements.txt
index 677307d..2fa84f3 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,7 +4,7 @@ keras == 2.2.2
pillow == 5.2.0
pandas == 0.23.4
MultiColProcessor == 1.0.15
-tensorflow-gpu == 1.3.0
+tensorflow-gpu ~> 1.3.0
matplotlib == 2.2.3
opencv-python == 3.4.2.17
np-utils == 0.5.5.2
diff --git a/train_ensemble.py b/train_ensemble.py
deleted file mode 100644
index 244a2eb..0000000
--- a/train_ensemble.py
+++ /dev/null
@@ -1,20 +0,0 @@
-from modules.ensemble_modules import obsolete_EnsenmbleData
-from modules import OptimizeAndLog
-import importlib
-
-## load data
-X_train, X_test, y_train, y_test, cls_indices = \
- obsolete_EnsenmbleData.load_ensemble_data(data_path='./data/ensembleDatasets/pre_ensembleData_final.pkl')
-
-##
-importlib.reload(OptimizeAndLog)
-OptimizeAndLog.OptimizerLogger. \
- train_and_save_two_fc_ensemble(fc_size_1=500, fc_size_2=100,
- use_drop_out_1=True, use_drop_out_2=True,
- num_iterations=250,
- learning_rate=3e-4, momentum=None,
- X_train=X_train, y_train=y_train,
- X_test=X_test, y_test=y_test,
- cls_indices=cls_indices,
- models_log_path='./logs/models_ensemble/',
- device_name="/cpu:0")
diff --git a/trial.py b/trial.py
deleted file mode 100644
index e0fcbb4..0000000
--- a/trial.py
+++ /dev/null
@@ -1,261 +0,0 @@
-import os
-import tensorflow as tf
-from modules import LoadImg
-from tensorflow.python.framework import meta_graph
-
-graph_model = tf.Graph()
-with graph_model.as_default():
- ##################################
- params = {"checkpoint_path": "./logs/primary_models/1st_good"}
- with tf.Session(graph=graph_model) as sess:
- params = {"checkpoint_path": "./logs/primary_models/1st_good"}
-
- saver = tf.train.import_meta_graph(os.path.join(params["checkpoint_path"], 'best_model_main.meta'),
- clear_devices=True,
- import_scope='')
- saver.restore(tf.get_default_session(),
- tf.train.latest_checkpoint(params["checkpoint_path"]))
- # meta_graph.import_scoped_meta_graph(os.path.join(params["checkpoint_path"],
- # 'best_model_main.meta'),
- # clear_devices=True,
- # import_scope='graph_model')
- # tf.train.list_variables(params["checkpoint_path"])
- # tf.train.load_variable(params["checkpoint_path"], 'Variable_9/Adam_1')
- # tf.train.init_from_checkpoint(ckpt_dir_or_file=params["checkpoint_path"],
- # assignment_map={'/': '/'})
- # meta_graph.read_meta_graph_file(filename="./logs/primary_models/1st_good/best_model_main.meta")
- # graph_model.clear_collection('trainable_variables')
- # graph_model.clear_collection('train_op')
- # graph_model.clear_collection('variables')
-
- X_image_tf = graph_model.get_tensor_by_name("X_image_tf:0")
- logits_tf = graph_model.get_tensor_by_name("logits_tf:0")
- logits_tf_sg = tf.stop_gradient(logits_tf)
- ####################################
-
-graph_pipeline = tf.Graph()
-with graph_pipeline.as_default():
- ##################################
- X_raw = tf.placeholder(tf.float32, shape=[None, None, None, None], name="X_raw")
- params = {"checkpoint_path": "./logs/primary_models/1st_good"}
- meta_graph.import_scoped_meta_graph(os.path.join(params["checkpoint_path"],
- 'best_model_main.meta'),
- clear_devices=True,
- import_scope='')
-
- X_image_tf = graph_pipeline.get_tensor_by_name("X_image_tf:0")
- # X_image_tf = tf.placeholder(tf.float32, shape=[None, None, None, None], name="X_image_tf")
-
- resized_imgs = tf.identity(tf.image.resize_images(X_raw, (X_image_tf.get_shape().as_list()[1],
- X_image_tf.get_shape().as_list()[2])),
- name='resized_imgs')
- ####################################
-
-graph = tf.get_default_graph()
-
-raw_imgs = tf.placeholder(tf.float32, shape=[None, 224, 224, 3],
- name='raw_imgs')
-
-meta_graph_1 = tf.train.export_meta_graph(graph=graph_pipeline)
-meta_graph.import_scoped_meta_graph(meta_graph_1,
- input_map={"X_raw": raw_imgs},
- import_scope='graph_pipeline')
-
-out_1 = graph.get_tensor_by_name('graph_pipeline/resized_imgs:0')
-
-meta_graph_2 = tf.train.export_meta_graph(graph=graph_model)
-meta_graph.import_scoped_meta_graph(meta_graph_2,
- input_map={"X_image_tf": out_1},
- import_scope='graph_model')
-
-out_2 = graph.get_tensor_by_name('graph_model/logits_tf:0')
-
-print(tf.global_variables())
-
-X_train, X_test, y_train, y_test, cls_indices = LoadImg.Dataset.prep_datasets(
- ver_ratio=0.2, container_path='data/ImageEveryUnit',
- final_img_width=224, final_img_height=224,
- color_mode="grayscale", random_state=1911, is_trial=True)
-
-# with tf.device('CPU:0'):
-with tf.Session() as sess:
- sess.run(tf.global_variables_initializer())
- writer = tf.summary.FileWriter('./trial/writer', sess.graph)
- res = sess.run(out_2, feed_dict={raw_imgs: X_train})
- ##
- saver = tf.train.Saver(max_to_keep=1)
- saver.save(sess, './trial/best_model_main')
- writer.close()
-
-##### prediction
-import tensorflow as tf
-from modules import LoadImg
-
-X_train, X_test, y_train, y_test, cls_indices = LoadImg.Dataset.prep_datasets(
- ver_ratio=0.2, container_path='data/ImageEveryUnit',
- final_img_width=224, final_img_height=224,
- color_mode="grayscale", random_state=1911, is_trial=True)
-
-with tf.Session() as session:
- writer = tf.summary.FileWriter('./trial/writer_prediction', session.graph)
- saver_3 = tf.train.import_meta_graph('./trial/best_model_main.meta',
- clear_devices=True)
- saver_3.restore(tf.get_default_session(),
- tf.train.latest_checkpoint('./trial'))
- graph_pred = tf.get_default_graph()
- raw_imgs = graph_pred.get_tensor_by_name("raw_imgs:0")
- logits_tf = graph_pred.get_tensor_by_name("graph_model/logits_tf:0")
-
- ##
- feed_dict_pred = {raw_imgs: X_train}
-
- ##
- logits = session.run(logits_tf, feed_dict=feed_dict_pred)
- writer.close()
-
-# graph_img_pipe = tf.Graph()
-# with graph_img_pipe.as_default():
-# ########################################
-# X_raw = tf.placeholder(tf.float32, shape=[None, 224, 224, 3], name="X_raw")
-#
-# meta_graph_img_raw = tf.train.export_meta_graph(graph=graph)
-# meta_graph.import_scoped_meta_graph(meta_graph_img_raw,
-# input_map={"raw_imgs": X_raw},
-# import_scope='graph_img_pipe')
-#
-# meta_graph_model = tf.train.export_meta_graph(graph=graph_model)
-# meta_graph.import_scoped_meta_graph(meta_graph_model,
-# import_scope='graph_img_pipe')
-#
-# img_tf = graph_model.get_tensor_by_name('graph_model/X_image_tf:0')
-# ##################
-# resized_imgs = tf.identity(tf.image.resize_images(X_raw, (img_tf.get_shape().as_list()[1],
-# img_tf.get_shape().as_list()[2])),
-# name='resized_imgs')
-# ################################################
-
-# graph = tf.get_default_graph()
-# x = tf.placeholder(tf.float32, shape=[1], name="xx")
-# raw_imgs = tf.placeholder(tf.float32, shape=[None, 224, 224, 3],
-# name='raw_imgs')
-# meta_graph_1 = tf.train.export_meta_graph(graph=graph_img_raw)
-# meta_graph.import_scoped_meta_graph(meta_graph_1,
-# input_map={"X_img_raw": raw_imgs},
-# import_scope='')
-
-
-# a = tf.image.resize_images(X_train, (80,80))
-#
-# with tf.Session(graph=graph) as sess:
-# res = sess.run(a, feed_dict={raw_imgs: X_train})
-
-# X_train, X_test, y_train, y_test, cls_indices = LoadImg.Dataset.prep_datasets(
-# ver_ratio=0.2, container_path='data/ImageEveryUnit',
-# final_img_width=244, final_img_height=244,
-# color_mode="grayscale", random_state=1911)
-#
-# imgs = X_train[:10, :, :, :]
-#
-# with tf.Session() as sess:
-# writer = tf.summary.FileWriter('trial', sess.graph)
-#
-# img_size_x = imgs.shape[1]
-# img_size_y = imgs.shape[2]
-# num_channels = imgs.shape[3]
-# X_image_tf_ensemble = tf.placeholder(tf.float32,
-# shape=[None, img_size_x, img_size_y, num_channels],
-# name='X_image_tf_ensemble') #############################
-#
-# params = {"checkpoint_path": "./logs/primary_models/1st_good"}
-#
-# saver = tf.train.import_meta_graph(os.path.join(params["checkpoint_path"], 'best_model_main.meta'),
-# clear_devices=True)
-# saver.restore(tf.get_default_session(),
-# tf.train.latest_checkpoint(params["checkpoint_path"]))
-# graph = tf.get_default_graph()
-#
-# ##
-# X_image_tf = graph.get_tensor_by_name("X_image_tf:0")
-#
-# input_shape = X_image_tf.get_shape().as_list()
-#
-# ##
-# resize_op = tf.image.resize_images(X_image_tf_ensemble,
-# (input_shape[1], input_shape[2]))
-#
-# model_input = tf.get_default_session().run(resize_op,
-# feed_dict={X_image_tf_ensemble: imgs})
-#
-# ##
-# logits_tf = graph.get_tensor_by_name("logits_tf:0")
-# # #
-# feed_dict_pred = {X_image_tf: model_input}
-# # #
-# logits_pred = tf.get_default_session().run(logits_tf, feed_dict=feed_dict_pred)
-# saver_2 = tf.train.Saver(max_to_keep=1000000)
-# saver_2.save(tf.get_default_session(), os.path.join('./trial/best_model_main'))
-# writer.close()
-#
-# ##### prediction
-# with tf.Session() as session:
-# saver_3 = tf.train.import_meta_graph('./trial/best_model_main.meta',
-# clear_devices=True)
-# saver_3.restore(tf.get_default_session(),
-# tf.train.latest_checkpoint(params["checkpoint_path"]))
-# graph_2 = tf.get_default_graph()
-# X_image_tf_ensemble_2 = graph_2.get_tensor_by_name("X_image_tf_ensemble:0")
-# logits_tf_2 = graph_2.get_tensor_by_name("logits_tf:0")
-#
-# ##
-# feed_dict_pred = {X_image_tf_ensemble_2: imgs}
-#
-# ##
-# logits_pred_2 = session.run(logits_tf_2, feed_dict=feed_dict_pred)
-
-
-# graph_1 = tf.Graph()
-# with graph_1.as_default():
-# a = tf.placeholder(tf.float32, shape=[1], name="aa")
-# c = tf.sqrt(a, name='out_1')
-#
-# graph_2 = tf.Graph()
-# with graph_2.as_default():
-# u = tf.placeholder(tf.float32, shape=[1], name="uu")
-# y = tf.sqrt(u, name='out_2')
-#
-# graph = tf.get_default_graph()
-# x = tf.placeholder(tf.float32, shape=[1], name="xx")
-#
-# meta_graph_1 = tf.train.export_meta_graph(graph=graph_1)
-# meta_graph.import_scoped_meta_graph(meta_graph_1,
-# input_map={"aa": x},
-# import_scope='graph_1')
-# out_1=graph.get_tensor_by_name('graph_1/out_1:0')
-#
-# meta_graph_2 = tf.train.export_meta_graph(graph=graph_2)
-# meta_graph.import_scoped_meta_graph(meta_graph_2,
-# input_map={"uu": out_1},
-# import_scope='graph_2')
-# out_2=graph.get_tensor_by_name('graph_2/out_2:0')
-#
-# print(tf.global_variables())
-#
-# with tf.Session(graph=graph) as sess:
-# res = sess.run(out_2, feed_dict={x:[16.0]})
-path_to_images='data/ImageEveryUnit'
-bin_path='dumps/'
-prefetch_buffer_size=1700000
-
-from modules.ensemble_modules.trainer_from_storage.input import Dataset
-
-input_fn_train, input_fn_eval, n_output = Dataset.prep_dataflow_functions(
- ver_ratio=0.2,
- container_path=path_to_images,
- prefetch_buffer_size=prefetch_buffer_size,
- epochs_between_evals=1,
- random_state=19,
- is_trial='True',
- bin_path=bin_path,
- multi_threading='False',
- train_batch_size=4)
-
diff --git a/trial/best_model_main.data-00000-of-00001 b/trial/best_model_main.data-00000-of-00001
deleted file mode 100644
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diff --git a/trial/best_model_main.index b/trial/best_model_main.index
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diff --git a/trial/best_model_main.meta b/trial/best_model_main.meta
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diff --git a/trial/checkpoint b/trial/checkpoint
deleted file mode 100644
index 6e74726..0000000
--- a/trial/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/trial/writer/events.out.tfevents.1540410053.OCI1602 b/trial/writer/events.out.tfevents.1540410053.OCI1602
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 }})
+  }})
+ >
+}})
+