the generation of the final output image about rvgan

[SharifAmit]

I will upload the infer.py file that can be used for running inference/testing images.

In the meantime, you can check the visualization.py and dataloader.py files in the 'src' folder to see how to do prediction.
If you check the strided_crop_DRIVE.py files then we are taking N number of a crops from each image and mask.
The prediction will be something like this:

X_coarse, x_global = coarse_model.predict([Coarse_Crop Coarse_Mask])
X_fine = g_model.predict([Fine_crop,Fine_Mask,x_global])

Fine_crop = 128x128 crop from the fine image
Fine_mask = 128x128 crop from the fine mask
Coarse_crop= 64x64 crop by dividing the Fine_crop / / 2
Coarse_mask = 64x64 crop by dividing the Fine_mask // 2

You can save both the X_coarse and X_fine as .PNG and show it as a Plot ( Already provided in visualization.py)

N. B. you have to do it for all the crops in one image, then overlap all the crops and average the pixel values. I will provide that code in the infer.py file.

Hope this helps !

[mjm92]

I think I understand your meaning, thank you very much!