beala / deep-image-prior-tensorflow Goto Github PK
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License: Other
An implementation of https://dmitryulyanov.github.io/deep_image_prior for tensorflow.
License: Other
You might want to change
def load_image(filename, dim):
with open(image_name, 'rb') as f:
raw_image = tf.image.decode_png(f.read())
...
to
def load_image(filename, dim):
with open(filename, 'rb') as f:
raw_image = tf.image.decode_png(f.read())
...
Thank you, Alex, for your great implementation.
Definitely, this is not an issue! But, can you please explain why you are blurring the output of the generator before computing the mean square error (line 181 of your code)?
Thanks for your code! I have a small question about the detail of your implementation.
In file "deepimg.py", at line 86, why did you choose the number of the conv layer's kernel as 3 instead of 128? The latter setting will result in much faster convergence in denosing case.
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