Saved image is NAN

[H-deep]

Thank you for the provided code and the pre-trained weights.
I ran your test code for bdd100k dataset. However, I got the output saved images as black images. I check the output of the model:
fake_img, = self.sess.run([out_var], feed_dict={in_var: sample_image}) in AUGAN.py script
and the result is all NAN list:
fake_img, = self.sess.run([out_var], feed_dict={in_var: sample_image})

The sample image is as follows:
sample_image: [[[[-0.85882354 -0.81960785 -0.7882353 ]
[-0.85882354 -0.81960785 -0.7882353 ]
[-0.85882354 -0.81960785 -0.7882353 ]
...

But fake_img is as follows:
fake_img: [[[[nan nan nan]
[nan nan nan]
[nan nan nan]
...

So the output of the concatenation is a nan also.

What do you think is the source of the problem?

Thank you

[jgkwak95]

Hi. Please check the resolution or scale of your input images.