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# Model architechture | |
model = Sequential() | |
model.add(Conv2D(32, (3, 3), input_shape=(224, 224, 3), activation='relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) | |
model.add(Conv2D(32, (3, 3), activation='relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) | |
model.add(Conv2D(64, (3, 3), activation='relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) | |
model.add(Flatten()) | |
model.add(Dense(64, activation='relu')) | |
model.add(Dropout(0.24)) | |
model.add(Dense(2,activation='softmax')) | |
model.summary() |
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