Matiur Rahman Minar

> This code will help you out for re-arranging the labels according to the paper or repo > > `test = np.zeros(shape=img2.shape) for i in range(img2.shape[0]): for j in range(img2.shape[1]):...

Hi @andrewjong , thank you very much for your kind words. It's very great to hear from you. Thank you for the suggestion. I will at least try to mark...

@amandazw , actually this is the expected result for CP-VTON+. As you can see, the try-on cloth is shorter than the one the user was wearing, so the generative network...

This is due to the wrong pair/images id in the GMM/TOM step. Please debug your inputs or check the previous issues here.

Hi @TamerElsherif , yes, the folder seems to be the correct one for the try-on results. However, as you can see, before running the try-on (TOM) network, you need to...

Yes, your testing process seems to be okay. Is the result still same as before?  See here, cloth is not warped. You can check if the GMM pretrained model...

Hi @trilokpadhi , please check why the cloth is not warped from the GMM testing. As I mentioned above, you can check whether the GMM model is correctly loaded and...

Hi, @Testhjf , the current model is trained and designed for this fixed resolution. If you need a different size, you need to re-design and re-train the model.

Hi @amnesytoolkit , this is most probably due to the wrong folder path of cloth mask or image-parse. Can you please check which folder is set in your cp_dataset.py file?...

@iamnaazib , you can add your gpu id(s) here: https://github.com/minar09/cp-vton-plus/blob/master/train.py#L21 as `parser.add_argument("--gpu_ids", default="0")` or add the argument in the run command: `python train.py --name GMM --stage GMM --workers 1 --save_count...