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qicathetine avatar qicathetine commented on September 18, 2024

Hi@pribadihcr, I just read your code. May I ask you some questions? Do you train your model by 100*100 image crops(random cropping) and test your model by feeding the entire image? If I am right, what is the meaning of training by image crops? Thank you !!!

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pribadihcr avatar pribadihcr commented on September 18, 2024

hi @qicathetine,

I am following the original TF code, as also mention it in the paper https://arxiv.org/abs/1704.02470, section 2, page. 5.

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aiff22 avatar aiff22 commented on September 18, 2024

Hi @pribadihcr

Thank you for your work! I guess that the problem is that you are first rescaling the input images to 720x1280 resolution, and then passing them to a neural network. Since it was trained on larger photos, the results in this case might be worse. Thus, the two possible options are 1) to pass them in their orig res defined in utils.get_resolutions() 2) or to crop them to HD size.

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qicathetine avatar qicathetine commented on September 18, 2024

Hi @pribadi HCR
Do you mean the section of "Generator and Discriminator CNNs"?

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pribadihcr avatar pribadihcr commented on September 18, 2024

@qicathetine
Section.2 2 DSLR Photo Enhancement Dataset. Have you read it?

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pribadihcr avatar pribadihcr commented on September 18, 2024

@aiff22 ,

You talk about inference right?. I mean the result still not good in training phase, For training I am trying to save the enhanced image in line 259 im.save('./samples/enhanced_images.jpg').

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qicathetine avatar qicathetine commented on September 18, 2024

@pribadihcr
Is there any possible to add a deconvolution layer in the resnet block? There are always bugs (partial shape )when writing deconvolution layer. Thank you !

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