Open dev6969 opened 6 years ago
1.randomly leak original color information 2.data augmentation for stable training
thank you for your reply. !!!!(comments did not come up.) I understood the way. and
image1 = np.insert(image1, 1, -512, axis=2) # -512?!
image1 = np.insert(image1, 2, 128, axis=2)
image1 = np.insert(image1, 3, 128, axis=2)
Adjusting the color range in this way for recognize a range does not have color information?
not adjusting the range -1 ~ 1
would like to keep learning the code while continuing to use another network model. But I do not understand how to learn color information in this project ....
I think one of the four input channels is a line channel and the remaining three channels are color information. However, I can not understand how to create color hints from the original image. What I understood = 4ch -> 1ch (line) + 3ch (color hint)[how create color hint!?]
Why does "img2imgDataset.get_example ()" randomly add noise to the image?