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ankanbhunia / AdverseBiNet

Improving Document Binarization via Adversarial Noise-Texture Augmentation (ICIP 2019)
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question about results #2

Open vince2003 opened 5 years ago

vince2003 commented 5 years ago

Thank you very much for your source code! However, I met problem when I run your code again. I use datasets as you mentioned. convert to patchs 256x256 and augmentation rotation 90, 180 and 270(and I created 18792 new patchs for training) and train. My F-measure on Dibco2013 is 79,73% that is so far from paper(97.8%). So my question is: Do you only use image from TA Gan or both fake image of TA Gan and original image for training? Do you have using other technique? Can you guess what I am wrong ? Thank you!

tonsquemike commented 5 years ago

Dear @quangvinh242003, can you provide me the script for binarize images? I was trying to run the repo in test mode but I couldn't run it

justinner commented 4 years ago

could you provide the code for binarized? thanks very much!