noise2noise
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denoising text noise
hello,
I tried to clean up an image enriched with text but the result is far from what I expected from the example presented : where can such a difference come from ? the fact that the fonts and colours used (especially black) are not the same as those used in training ?
thank you for sharing your work, regards, lacsaP.
$ python test_model.py --image_dir images/test/ --weight_file models/weights.057-4.796-27.68533_text_noise.hdf5 --test_noise_model clean
$ python test_model.py --image_dir images/test/ --weight_file models/weights.056-4.172-28.07752_text_clean.hdf5 --test_noise_model clean
I have the same problem.
when I input an image with text noise already add, and I used the function "get_noise_model" add text noise, It seems that the model only dealt with the text noise added , and the text noise on origin image remains unresolved.
left is the input , middle added new text noise, right is the result.
Thank you for your reports! Oh... I'm not sure but the trained model seems seriously overfitted to the font used in training. @savort's result is very surprising. The model can distinguish the training font and the other fonts so clearly...
To address this issue, we can do several things; using multiple fonts, data augmentation with geometric transformations, and so forth. I will be busy for one or two weeks so I'll try to solve this issue after that.
@yu4u 3 weeks have gone~
oh , I found out the problem. If I transfer the add_noise_image to a jpeg form, when I re-read the image, the picture have been compressed and the detail of the text in the image is changed, so the model cannot denoise it.
I did not have that idea! In order to tackle the problem, we should train model with some expected noises such as compression, resizing, and so on.
@savort Would you please post out the de-noise result image after solveing the problem?