fullfanta/pix2pix-tensorflow

pix2pix tensorflow implementation

pix2pix-tensorflow's Issues

Test results are all blue washed images

Hi, I trained facades dataset and added testing function but the results look like all blue color intensified image.

Image link: https://imgur.com/2LZgl8E

I think post-processing is the one causes the issue.
I used the np scaling.

result = np.interp(output_image, (-1, 1), (0, 255))

Is there any method you used for post-processing?
Thanks,

Here is the code:

def test(argv=None):
    with tf.device("/%s:0" % (FLAGS.device)):        
        input_image         = tf.placeholder(tf.float32, [FLAGS.batch_size, FLAGS.fine_size, FLAGS.fine_size, 3])
        gt_image            = tf.placeholder(tf.float32, [FLAGS.batch_size, FLAGS.fine_size, FLAGS.fine_size, 3])
        generated_image     = generator.get_inference(input_image, FLAGS, reuse=False, drop_prob = 0.5)
     

    test_list = get_test_list()
    total_test_size = len(test_list)

    print ('train list - ', total_test_size)
    test_images = get_test_batch(test_list)

    # Create a saver.
    saver = tf.train.Saver(tf.global_variables())

    gpu_options = tf.GPUOptions(allow_growth=True)
    with tf.Session(config=tf.ConfigProto(log_device_placement=False, allow_soft_placement=True, gpu_options=gpu_options)) as sess: 
        # initialize the variables
        sess.run(tf.global_variables_initializer())

        # load pretrained model
        if FLAGS.pretrained_model:
            point = tf.train.latest_checkpoint(FLAGS.train_dir + '_' + FLAGS.dataset)
            print ('check point - ', point)
            saver.restore(sess, point)

        # initialize the queue threads to start to shovel data
        coord = tf.train.Coordinator()
        threads = tf.train.start_queue_runners(coord=coord)

        for elk in range(20):        
            test_info = sess.run(test_images)
            test_input_images = test_info[0]
            test_gt_images = test_info[1]

            inferred_image = sess.run(generated_image, feed_dict = {input_image : test_input_images, gt_image : test_gt_images})    
            output_image = inferred_image[0]
            result = np.interp(output_image, (-1, 1), (0, 255))  
            cv2.imwrite('inferred_image_' + str(elk) +'.jpg', result) 

        coord.request_stop()
        coord.join(threads)
        sess.close()  `