LoSealL / VideoSuperResolution

A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.

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Hi,How can i save the result image?

Undercut opened this issue · comments

commented

I found the result images in the Results/model-name/test-datasets-name. But if i use <--infer >,where to find my result images?

Still under Results/model-name/infer-folder-name

commented

Still under Results/model-name/infer-folder-name

谢谢回答,我这里还有一个问题想请教,我在测试使用Vespcn-tensorflow获得超分辨率视频,15秒24帧720P的视频被我切分成200多张图片,这组图片序列通过Vespcn需要非常长的时间,大约1个多小时(在2600X上进行测试,未使用GPU加速),请问有没有什么办法能够加快预测的速度,使用Pytorch会有帮助吗?
同时我查阅了Vespcn那篇论文,原论文声称使用了动作补偿来加快视频超分辨率化的速度,但在这个模型上似乎并没有体现,请问是否有完整复现论文的模型?

  1. Pytorch's CPU implementation is quite slow.
  2. For VESPCN, it will process 3 frames to generate 1 output.
  3. Motion compensation is not for acceleration...
commented

Thank you, I got it. By the way, which model should i choose if i want a fast VSR.

FRVSR is highly recommended

commented

Thank you so much.

hi,when I test the vespcn-tensorflow, it can't save image to infer,can you give me some advice ? @Undercut @LoSealL
It just return
Test: 0it [00:00, ?it/s]
my command is
python eval.py dbpn -t vid4 --pretrain=../Results/vespcn/save

You should use
python eval.py vespcn -t vid4 --pretrain=../Results/vespcn/save

Thanks, I see that you have change the '/VSR/Backend/TF/Framework/Trainer.py', it works for testing vespcn model. Thank you very much!

Hi, when I use
python eval.py vespcn -t vid4 --pretrain=../Results/vespcn/save

The terminal reports some issues. I don't know how to solve it. Can you give me some advice?

Here is the report information:
(TF2.1) D:\GP_AI\Super Resolution\VideoSuperResolution\Train>python eval.py vespcn -t vid4 --pretrain=../Results/vespcn/save
2022-05-07 20:01:40,213 INFO: LICENSE: VESPCN is proposed at CVPR2017 by Twitter. Implemented by myself @LoSealL.
Traceback (most recent call last):
File "eval.py", line 122, in
main()
File "eval.py", line 83, in main
model.load(opt.pretrain)
File "d:\gp_ai\super resolution\videosuperresolution\VSR\Backend\Torch\Models\Model.py", line 137, in load
self.sequential_load(model, str(pth), map_location)
File "d:\gp_ai\super resolution\videosuperresolution\VSR\Backend\Torch\Models\Model.py", line 148, in sequential_load
state_dict = torch.load(pth, map_location=map_location)
File "F:\Anaconda\envs\TF2.1\lib\site-packages\torch\serialization.py", line 699, in load
with _open_file_like(f, 'rb') as opened_file:
File "F:\Anaconda\envs\TF2.1\lib\site-packages\torch\serialization.py", line 231, in _open_file_like
return _open_file(name_or_buffer, mode)
File "F:\Anaconda\envs\TF2.1\lib\site-packages\torch\serialization.py", line 212, in init
super(_open_file, self).init(open(name, mode))
PermissionError: [Errno 13] Permission denied: '../Results/vespcn/save'