Merge branch 'master' of https://github.com/acmucsd/acm-ai-workshops

Author: catherinelee274

Fall20/NeuralNetworks4/layers.py

@@ -0,0 +1,39 @@
+from tensorflow.keras import Model, layers, Input
+import numpy as np
+
+temp_im_test = np.ones((1,128,128,3))
+
+input_shape_img = (128,128,3)
+
+img_input = Input(shape=input_shape_img)
+
+# convolutional layers with 64 neurons and (3,3) kernel each
+conv1_1 = layers.Conv2D(64, (3, 3), activation='relu', padding='same', name='block1_conv1')(img_input)
+conv1_2 = layers.Conv2D(64, (3, 3), activation='relu', padding='same', name='block1_conv2')(conv1_1)
+
+# maxpool2D layer with (2,2) filter and stride (2,2)
+max1 = layers.MaxPool2D((2, 2), strides=(2, 2), name='block1_pool')(conv1_2)
+
+# globalmax layer
+globalmax1 = layers.GlobalMaxPool2D()(max1)
+
+# flattens input to 1D array
+flatten1 = layers.Flatten()(globalmax1)
+
+# dropout layer modifies input layer so some values become 0
+drop1 = layers.Dropout(.2)(flatten1)
+
+# standard dense layer
+dense1 = layers.Dense(32)(drop1)
+
+# compiles model with input: img_input and output as output from dense1
+model = Model(inputs = img_input, outputs= dense1)
+model.compile(optimizer='sgd', loss='mse')
+
+# shows model
+model.summary()
+
+# show result on one input
+values = model.predict(temp_im_test)
+print(values.shape)
+print(values)