How did you train your instagan model? about instagan HOT 11 CLOSED

OK, I will try, thank you very much! And I just find the result of the 200th epoch on the training set is pretty good and the performance of 600th epoch is poor.

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Great! Maybe 600 epoch is too much for low-resolution images (overfitting?). Early stopping could be a solution :)

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Hi, did you trained InstaGAN model with predicted masks?
In my experience, the performance of InstaGAN was pretty sensitive to the mask qualities. Hence, although the results of pix2pix model is "pretty good", it may not enough for training of InstaGAN.
In my experiments, I trained InstaGAN with "real masks" and only used predicted masks for inference. Improving the robustness to the mask quality would be an interesting research direction.

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Thank you. I train the instagan with real mask, but test it with the predict masks.

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I used real masks to train the instagan model by running: python train.py --dataroot ./datasets/jeans2skirts_ccp_crop --model insta_gan --name jeans2skirts_ccp_crop_instagan --loadSizeH 200 --loadSizeW 80 --fineSizeH 200 --fineSizeW 80 --niter 400 --niter_decay 200 --batch_size 3 --gpu_ids 0,1,2. And I just test it with real mask of jeans and skirts, and the result is very bad either.

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Hi, how about performance on your training set? Can you try with the pretrained network?
Also, as the training set and test set are different, although it performs okay for training set, it may fail for test set. In my experience, front-looking images were easier to transform.

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Hi, performance on on my training set is bad either. The perfomance of pretrain network is good on the CCP dataset, but not good enough on some low pixel photos.

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As the pretrained networks are trained on high-resolution images, it'd be better to match the resolution. How about scale up your low-resolution images and use pretrained networks?

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That's a good idea. But I want to apply the model to the low resolution photos, so I compressed the image of the CCP data set and tried to train to instaGAN model with the real mask and those low resolution photos. However the trainning result were not satisfied.

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Why not translate high-resolution images and resize it to low-resolution?
Maybe the current model parameter is too big for low-resolution images. You can try smaller models.

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Yeah, that's what I think.

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