INNER CODE UNIT · Python

enhanced

aiff22/DPED · models.py:54

        enhanced = tf.nn.tanh(conv2d(c11, W12) + b12) * 0.58 + 0.5

    return enhanced


def adversarial(image_):

    with tf.compat.v1.variable_scope("discriminator"):

        conv1 = _conv_layer(image_, 48, 11, 4, batch_nn = False)
        conv2 = _conv_layer(conv1, 128, 5, 2)
        conv3 = _conv_layer(conv2, 192, 3, 1)
        conv4 = _conv_layer(conv3, 192, 3, 1)
        conv5 = _conv_layer(conv4, 128, 3, 2)
        
        flat_size = 128 * 7 * 7
        conv5_flat = tf.reshape(conv5, [-1, flat_size])

View source record →