train-ingame-classifier.py 文件源码

def get_model(img_channels, img_width, img_height, dropout=0.5):

    model = Sequential()
    model.add(Convolution2D(32, 3, 3, input_shape=(
        img_channels, img_width, img_height)))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Convolution2D(32, 3, 3))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Convolution2D(32, 3, 3))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Flatten())
    model.add(Dense(64))
    model.add(Activation('relu'))
    model.add(Dropout(dropout))
    model.add(Dense(1))
    model.add(Activation('sigmoid'))

    return model