The model creation is upgraded to the latest tensorflow SGD

Section #4 - Capstone/simpsons.ipynb

@@ -50,6 +50,12 @@
         "import numpy as np\n",
         "import cv2 as cv\n",
         "import gc\n",
+        "import tensorflow as tf\n",
+"import keras\n",
+"from keras.models import Sequential, Model\n",
+"from keras.layers import Conv2D, Flatten, MaxPooling2D, Dense, Input, Reshape, Concatenate, GlobalAveragePooling2D, BatchNormalization, Dropout, Activation, GlobalMaxPooling2D\n",
+"from keras.utils import Sequence\n",
+
         "#pylint:disable=no-member (Removes linting problems with cv)"
       ],
       "outputs": [],
@@ -245,9 +251,16 @@
       "execution_count": null,
       "source": [
         "# Create our model (returns a compiled model)\n",
-        "model = canaro.models.createSimpsonsModel(IMG_SIZE=IMG_SIZE, channels=channels, output_dim=len(characters), \n",
-        "                                         loss='binary_crossentropy', decay=1e-7, learning_rate=0.001, momentum=0.9,\n",
-        "                                         nesterov=True)"
+        "def create_ST_layer(input_shape = (64, 128, 3)):\n",
+    "input_img = Input(shape=input_shape)\n",
+    "model = Conv2D(48, kernel_size=(5, 5), input_shape = input_shape, strides = (1, 1), activation = 'relu')(input_img)\n",
+    "model = MaxPooling2D(pool_size=(2, 2), strides = (2, 2))(model)\n",
+    "model = Conv2D(32, kernel_size=(5, 5), strides = (1, 1), activation = 'relu')(model)\n",
+    "model = MaxPooling2D(pool_size=(2, 2), strides = (2, 2))(model)\n",
+    "model = Dense(50, activation = 'relu')(model)\n",
+    "model = Dense(6)(model)\n",
+    "model = tf.keras.Model(inputs=input_img, outputs= model)\n",
+    "return model"
       ],
       "outputs": [],
       "metadata": {
@@ -259,6 +272,7 @@
       "cell_type": "code",
       "execution_count": null,
       "source": [
+        "model = create_ST_layer()\n",
         "model.summary()"
       ],
       "outputs": [],
@@ -368,4 +382,4 @@
       }
     }
   ]
-}
+}