Release AI-ModelZoo-2.1.0:

- Included additional models compatible with the STM32MP257F-DK2 board.
- Added support for per-tensor quantization.
- Integrated support for ONNX model quantization and evaluation.
- Included support for STEdgeAI (STM32Cube.AI v9.1.0 and subsequent versions).
- Expanded use case support to include Pose Estimation and Semantic Segmentation.
- Standardized logging information for a unified experience.


Signed-off-by: khaoula boutiche <[email protected]>

Author: KBOUSTM

LICENSE.md

@@ -12,6 +12,8 @@ Software BOM for stm32 use cases:
 * [human_activity_recognition](./human_activity_recognition/LICENSE.md)
 * [image_classification](./image_classification/LICENSE.md)
 * [object_detection](./object_detection/LICENSE.md)
+* [semantic_segmentation](./semantic_segmentation/LICENSE.md)
+* [pose_estimation](./pose_estimation/LICENSE.md)
 
 
 Software BOM for stm32 application codes:

README.md

@@ -0,0 +1,18 @@
+#!/bin/sh
+weston_user=$(ps aux | grep '/usr/bin/weston '|grep -v 'grep'|awk '{print $1}')
+DEPLOY_PATH=$1
+MODEL_NAME=$2
+LABELS=$3
+COMPATIBLE=$(cat /proc/device-tree/compatible)
+if [[ "$COMPATIBLE" == *"stm32mp2"* ]]; then
+	cmd="python3 $DEPLOY_PATH/Application/image_classification.py -m $DEPLOY_PATH/$MODEL_NAME -l $DEPLOY_PATH/Resources/$LABELS --framerate 30 --frame_width 640 --frame_height 480"
+else
+	cmd="python3 $DEPLOY_PATH/Application/image_classification.py -m $DEPLOY_PATH/$MODEL_NAME -l $DEPLOY_PATH/Resources/$LABELS --framerate 15 --frame_width 320 --frame_height 240"
+fi
+
+if [ "$weston_user" != "root" ]; then
+	echo "user : "$weston_user
+	script -qc "su -l $weston_user -c '$cmd'"
+else
+	$cmd
+fi

X-LINUX-AI_application_code/image_classification/Application/image_classification.py

@@ -0,0 +1,98 @@
+#!/usr/bin/python3
+#
+# Copyright (c) 2024 STMicroelectronics.
+# All rights reserved.
+#
+# This software is licensed under terms that can be found in the LICENSE file
+# in the root directory of this software component.
+# If no LICENSE file comes with this software, it is provided AS-IS.
+
+from stai_mpu import stai_mpu_network
+import numpy as np
+
+class NeuralNetwork:
+    """
+    Class that handles Neural Network inference
+    """
+    def __init__(self, model_file, label_file, input_mean, input_std):
+        """
+        :param model_path:  model to be executed
+        :param label_file:  name of file containing labels
+        :param input_mean: input_mean
+        :param input_std: input standard deviation
+        """
+
+        def load_labels(filename):
+            my_labels = []
+            input_file = open(filename, 'r')
+            for l in input_file:
+                my_labels.append(l.strip())
+            return my_labels
+
+        self._model_file = model_file
+        print("NN model used : ", self._model_file)
+        self._label_file = label_file
+        self._input_mean = input_mean
+        self._input_std = input_std
+        self._floating_model = False
+
+        # Initialization of network class
+        self.stai_mpu_model = stai_mpu_network(model_path=self._model_file)
+
+        # Read input tensor information
+        self.num_inputs = self.stai_mpu_model.get_num_inputs()
+        self.input_tensor_infos = self.stai_mpu_model.get_input_infos()
+
+        # Read output tensor information
+        self.num_outputs = self.stai_mpu_model.get_num_outputs()
+        self.output_tensor_infos = self.stai_mpu_model.get_output_infos()
+
+        self._labels = load_labels(self._label_file)
+
+    def get_labels(self):
+        """
+        :return: list of NN model labels loaded
+        """
+        return self._labels
+
+    def get_img_size(self):
+        """
+        :return: size of NN input image size
+        """
+        # NxHxWxC, H:1, W:2, C:3
+        input_tensor_shape = self.input_tensor_infos[0].get_shape()
+        input_width =  input_tensor_shape[1]
+        input_height =  input_tensor_shape[2]
+        input_channel =  input_tensor_shape[0]
+        print("input_width",input_width)
+        print("input_height",input_height)
+        print("input_channel",input_channel)
+        return (input_width,input_height,input_channel)
+
+    def launch_inference(self, img):
+        """
+        This method launches inference using the invoke call
+        :param img: the image to be inferred
+        """
+        # add N dim
+        input_data = np.expand_dims(img, axis=0)
+
+        if self.input_tensor_infos[0].get_dtype() == np.float32:
+            input_data = (np.float32(input_data) - self._input_mean) / self._input_std
+
+        self.stai_mpu_model.set_input(0, input_data)
+        self.stai_mpu_model.run()
+
+    def get_results(self):
+        """
+        This method can print and return the top_k results of the inference
+        """
+        output_data = self.stai_mpu_model.get_output(index=0)
+        results = np.squeeze(output_data)
+
+        top_k = results.argsort()[-5:][::-1]
+
+        if self.output_tensor_infos[0].get_dtype() == np.uint8 :
+            return (results[top_k[0]]/255, top_k[0])
+        else:
+            return (results[top_k[0]], top_k[0])

X-LINUX-AI_application_code/image_classification/Application/launch_python_image_classification.sh

@@ -0,0 +1,80 @@
+SLA0044 Rev5/February 2018
+
+Software license agreement
+
+ULTIMATE LIBERTY SOFTWARE LICENSE AGREEMENT
+
+BY INSTALLING, COPYING, DOWNLOADING, ACCESSING OR OTHERWISE USING THIS SOFTWARE
+OR ANY PART THEREOF (AND THE RELATED DOCUMENTATION) FROM STMICROELECTRONICS
+INTERNATIONAL N.V, SWISS BRANCH AND/OR ITS AFFILIATED COMPANIES
+(STMICROELECTRONICS), THE RECIPIENT, ON BEHALF OF HIMSELF OR HERSELF, OR ON
+BEHALF OF ANY ENTITY BY WHICH SUCH RECIPIENT IS EMPLOYED AND/OR ENGAGED AGREES
+TO BE BOUND BY THIS SOFTWARE LICENSE AGREEMENT.
+
+Under STMicroelectronics’ intellectual property rights, the redistribution,
+reproduction and use in source and binary forms of the software or any part
+thereof, with or without modification, are permitted provided that the following
+conditions are met:
+
+1. Redistribution of source code (modified or not) must retain any copyright
+notice, this list of conditions and the disclaimer set forth below as items 10
+and 11.
+
+2. Redistributions in binary form, except as embedded into microcontroller or
+microprocessor device manufactured by or for STMicroelectronics or a software
+update for such device, must reproduce any copyright notice provided with the
+binary code, this list of conditions, and the disclaimer set forth below as
+items 10 and 11, in documentation and/or other materials provided with the
+distribution.
+
+3. Neither the name of STMicroelectronics nor the names of other contributors to
+this software may be used to endorse or promote products derived from this
+software or part thereof without specific written permission.
+
+4. This software or any part thereof, including modifications and/or derivative
+works of this software, must be used and execute solely and exclusively on or in
+combination with a microcontroller or microprocessor device manufactured by or
+for STMicroelectronics.
+
+5. No use, reproduction or redistribution of this software partially or totally
+may be done in any manner that would subject this software to any Open Source
+Terms. “Open Source Terms” shall mean any open source license which requires as
+part of distribution of software that the source code of such software is
+distributed therewith or otherwise made available, or open source license that
+substantially complies with the Open Source definition specified at
+www.opensource.org and any other comparable open source license such as for
+example GNU General Public License (GPL), Eclipse Public License (EPL), Apache
+Software License, BSD license or MIT license.
+
+6. STMicroelectronics has no obligation to provide any maintenance, support or
+updates for the software.
+
+7. The software is and will remain the exclusive property of STMicroelectronics
+and its licensors. The recipient will not take any action that jeopardizes
+STMicroelectronics and its licensors' proprietary rights or acquire any rights
+in the software, except the limited rights specified hereunder.
+
+8. The recipient shall comply with all applicable laws and regulations affecting
+the use of the software or any part thereof including any applicable export
+control law or regulation.
+
+9. Redistribution and use of this software or any part thereof other than as
+permitted under this license is void and will automatically terminate your
+rights under this license.
+
+10. THIS SOFTWARE IS PROVIDED BY STMICROELECTRONICS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS, IMPLIED OR STATUTORY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+NON-INFRINGEMENT OF THIRD PARTY INTELLECTUAL PROPERTY RIGHTS, WHICH ARE
+DISCLAIMED TO THE FULLEST EXTENT PERMITTED BY LAW. IN NO EVENT SHALL
+STMICROELECTRONICS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
+OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
+ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+11. EXCEPT AS EXPRESSLY PERMITTED HEREUNDER, NO LICENSE OR OTHER RIGHTS, WHETHER
+EXPRESS OR IMPLIED, ARE GRANTED UNDER ANY PATENT OR OTHER INTELLECTUAL PROPERTY
+RIGHTS OF STMICROELECTRONICS OR ANY THIRD PARTY.

X-LINUX-AI_application_code/image_classification/Application/mobilenet_v2_pp.py

@@ -0,0 +1,6 @@
+# __Image classification Getting Started package__
+
+The respective README of each board can be found in the `<STM32_Serie_Name>` folder. The boards currently supported are the following ones:
+
+- [STM32MP1X](./STM32MP1/README.md)
+- [STM32MP2X](./STM32MP2/README.md)

X-LINUX-AI_application_code/image_classification/LICENSE.md

@@ -0,0 +1,45 @@
+window {
+    background-color: #000000;
+  }
+
+  window#overlay_window {
+    background-color: transparent;
+  }
+
+  widget {
+    background-color: transparent;
+  }
+
+  box#gui_main_stbox {
+    background-color: #000000;
+    color: #FFFFFF;
+  }
+
+  box#gui_overlay_stbox {
+    background-color: #000000;
+    color: #FFFFFF;
+  }
+
+  box#gui_main_video {
+    background-color: #000000;
+  }
+
+  box#gui_overlay_video {
+    background-color: transparent;
+  }
+
+  box#gui_main_exit {
+    background-color: #000000;
+  }
+
+  box#gui_overlay_exit {
+    background-color: transparent;
+  }
+
+  box#gui_main {
+    background-color: #000000;
+  }
+
+  drawing_area#overlay_draw {
+    background-color: transparent;
+  }