The first stage training is very effective, but when I want to test the accuracy, some issues turned out:
in the model.py anomaly_detector() self.ano_y = none. it will report an error in the def _sampler:
yb = tf.reshape(y, [-1, 1, 1, self.y_dim]),because none cannot be reshaped.
2.and when test, the batch_size is set to 1, the self.batch_size in _sampler should also be set to 1.
3.After I modify these codes, and change the input from images into the same data with train, the samples are just like some noises, and I wonder why.
@lzzlxxlsz I tested the images and no, the generated images seem to be noise and the other image is most likely the gray scale image of the test image.
The first stage training is very effective, but when I want to test the accuracy, some issues turned out: