Created
June 12, 2020 08:46
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model = Sequential() | |
model.add(Conv2D(32, (3, 3), padding='same', input_shape=(80, 80, 3), activation='relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) #40x40 | |
model.add(Dropout(0.25)) | |
model.add(Conv2D(32, (3, 3), padding='same', activation='relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) #20x20 | |
model.add(Dropout(0.25)) | |
model.add(Conv2D(32, (3, 3), padding='same', activation='relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) #10x10 | |
model.add(Dropout(0.25)) | |
model.add(Conv2D(32, (10, 10), padding='same', activation='relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) #5x5 | |
model.add(Dropout(0.25)) | |
model.add(Flatten()) | |
model.add(Dense(512, activation='relu')) | |
model.add(Dropout(0.5)) | |
model.add(Dense(2, activation='softmax')) |
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