Training time about real-esrgan HOT 17 OPEN

Hi @xinntao could I ask the license of ESRGAN_SRx4_DF2KOST_official-ff704c30.pth model?
Thank you!

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@cs20162004 Don't forget resize all images to 400x400 manually

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Train with this instead, it has tons of advanced options, auto-cropping, etc:

https://github.com/victorca25/traiNNer

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@tg-bomze why do I need to resize images to 400x400 manually?

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@cs20162004

1. It takes about 6-7 days for training RealESRNet; and 4-5 days for RealESRGAN.

2. You can directly finetune from the pretrained RealESRGAN with fewer iterations (I think 100k ~200k, you can see the difference). There is no need to train from scratch.

3. Including more face images will improve its ability to restore faces. For now, I recommend using together with GFPGAN, here is the script: https://github.com/TencentARC/GFPGAN/blob/master/inference_gfpgan.py I will also integrate GFPGAN to Real-ESRGAN.

4. @tg-bomze I think there is no need to resize all images to 400x400

5. @n00mkrad Thanks for the information. I will also improve Real-ESRGAN for easier use.

If you still have training issues, please let me know.
I will later improve the repo for more handy training and fine-tuning. 😄

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@xinntao
Thank you for your detailed answer!
Could you please explain what do you exactly mean by integrating with GFPGAN? Do you mean: run the input image on both networks (first on Real_ESRGAN and then on GFPGAN or vice versa)?

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GFPGAN network by default uses Real-ESRGAN on regions that don't contain human face (using detection algorithm maybe). But for some images containing face, the generated face image looks unnatural. Like the following:

@xinntao do you have any other idea to improve Real_ESRGAN for human face?

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@xinntao
Thank you for your detailed answer!
Could you please explain what do you exactly mean by integrating with GFPGAN? Do you mean: run the input image on both networks (first on Real_ESRGAN and then on GFPGAN or vice versa)?

Yes, your understanding is right~

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GFPGAN network by default uses Real-ESRGAN on regions that don't contain human face (using detection algorithm maybe). But for some images containing face, the generated face image looks unnatural. Like the following:

@xinntao do you have any other idea to improve Real_ESRGAN for human face?

These failures are limitations of GFPGAN.
Training with human faces will improve Real-ESRGAN performance on faces.
Another way is to improve the GFPGAN performance.

We also want to improve Real-ESRGAN's performance on human faces by utilizing more face data.
I think you can also contribute to Real-ESRGAN, if you want or obtain better results 😄

BTW, could you please share with me the original faces that GFPGAN failed in your examples? (Email: [email protected])

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Sure.
The pretrained model you shared (RealESRGAN_x4plus.pth) contains only the Generator's weights I guess. If I want to use your pretraining I will also need the Discriminator's weights.
Could you please share it if you have?

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@cs20162004
Sure, I will release the Discriminator.

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@xinntao Thanks a lot for this repository!
I've been trying to train the RealESRGAN with my own image dataset for a very specific application. Is there any way for me to check if iterations are progressing? I ran it and it threw out a bunch of text and here's the last few lines :

2021-12-01 07:02:47,942 INFO: Loading UNetDiscriminatorSN model from experiments/pretrained_models/RealESRGAN_x4plus_netD.pth, with param key: [params].
2021-12-01 07:02:47,964 INFO: Loss [L1Loss] is created.
2021-12-01 07:02:49,612 INFO: Loss [PerceptualLoss] is created.
2021-12-01 07:02:49,648 INFO: Loss [GANLoss] is created.
2021-12-01 07:02:49,678 INFO: Model [RealESRGANModel] is created.
2021-12-01 07:02:50,093 INFO: Start training from epoch: 0, iter: 0

It has just been like this for the past 5-6 hours. Will the text on the screen progress further?
I checked the directory in "experiments" that it created and it has a log file that has exactly the above (which it returned to stdout). This directory also has three sub-directories (models, training_states, visualization), all of which are completely empty.

I am using the "finetune_realesrgan_x4plus.yml" file , making modifications to point to my data directory. I'm running it with 4 GPUs (Tesla P100-SXM2).

Please let me know if there's anything I might be doing wrong.
Thank you.

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@Nidish96 Hey I met the same problem, please tell me how it goes if you get any solution

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@Doris1887 I haven't solved it, but I found something. In "train.py" in basicsr, the iterations start in line 154, where the training data (in variable "train_data") is invoked through "prefetcher.next()". This always seems to be "None" and I don't understand why. I've checked the path of the dataset, etc..

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lower your GPU batch size
then restart your environment

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Meaning?

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