INNER CODE UNIT · Python

c11

aiff22/DPED · models.py:49

        c11 = tf.nn.relu(conv2d(c10, W11) + b11)

        # Final

        W12 = weight_variable([9, 9, 64, 3], name="W12"); b12 = bias_variable([3], name="b12");
        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)

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