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model = Sequential() | |
model.add(Conv2D(filters = 64, kernel_size = (3,3),padding = 'Same',activation ='relu', input_shape = (SIZE,SIZE,3))) | |
model.add(MaxPooling2D(pool_size=(2,2))) | |
model.add(Conv2D(filters = 128, kernel_size = (3,3),padding = 'Same',activation ='relu')) | |
model.add(Conv2D(filters = 128, kernel_size = (3,3),padding = 'Same',activation ='relu')) | |
model.add(Conv2D(filters = 128, kernel_size = (3,3),padding = 'Same',activation ='relu')) | |
model.add(MaxPooling2D(pool_size=(2,2))) | |
model.add(Flatten()) | |
model.add(Dense(128, activation='relu')) | |
model.add(Dense(64, activation='relu')) | |
model.add(Dropout(rate=0.5)) | |
model.add(Dense(5, activation = "softmax")) |
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