INNER CODE UNIT · Python

big_XCEPTION

otaha178/Emotion-recognition · models/cnn.py:298

def big_XCEPTION(input_shape, num_classes):
    img_input = Input(input_shape)
    x = Conv2D(32, (3, 3), strides=(2, 2), use_bias=False)(img_input)
    x = BatchNormalization(name='block1_conv1_bn')(x)
    x = Activation('relu', name='block1_conv1_act')(x)
    x = Conv2D(64, (3, 3), use_bias=False)(x)
    x = BatchNormalization(name='block1_conv2_bn')(x)
    x = Activation('relu', name='block1_conv2_act')(x)

    residual = Conv2D(128, (1, 1), strides=(2, 2),
                      padding='same', use_bias=False)(x)
    residual = BatchNormalization()(residual)

    x = SeparableConv2D(128, (3, 3), padding='same', use_bias=False)(x)
    x = BatchNormalization(name='block2_sepconv1_bn')(x)
    x = Activation('relu', name='block2_sepconv2_act')(x)
    x = SeparableConv2D(128, (3, 3), padding='same', use_bias=False)(x)
    x = BatchNormalization(name='block2_sepconv2_bn')(x)

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