Comments (8)
Note: Here is the file that I could not get to process without running out of memory -- it would be really nice to be able to process larger videos like this:
https://drive.google.com/file/d/1o2dXzchZGa1hsep8z9NKLn411_cU6jfV/view?usp=sharing
from zooming-slow-mo-cvpr-2020.
I actually found out the solution myself. :)
It is as simple as changing the line 8 in train_zsm.yml
from
gpu_ids: [2]
to
gpu_ids: [0]
because Google Colab just provides one GPU instead of three.
I hope in case anyone else runs into that problem that this comment helps.
from zooming-slow-mo-cvpr-2020.
I'm suffering from a problem with the window system that prevents me from running the project.But the approach you suggested allowed me to successfully test the project, thank you so much for your selfless dedication!
from zooming-slow-mo-cvpr-2020.
Hello everyone!
@Mukosame: Thank you for this amazing work. It is fascinating how well the interpolation works.
@HanClinto: thanks for sharing the code for the Colab notebook - it works very well for the testing.
I am trying to train a new model from scratch with just 2x magnification on google colab and I run into some problems here.
When I use thetorch==1.4.0 torchvision==0.5.0 as done by HanClinto I get the following error when running:
!python train.py -opt options/train/train_zsm.yml
RuntimeError: cuda runtime error (100) : no CUDA-capable device is detected at /pytorch/aten/src/THC/THCGeneral.cpp:50
I also tried to exchange the DCNv2 for a different version provided from:
https://github.com/jinfagang/DCNv2_latest.git
which works also fine with torch==1.5.0+cu101 torchvision==0.6.0+cu101 and normal pytorch 1.6 for the interpolation of videos but when I try the training again I get the following error:
THCudaCheck FAIL file=/pytorch/aten/src/THC/THCGeneral.cpp line=47 error=100 : no CUDA-capable device is detected terminate called after throwing an instance of 'std::runtime_error' what(): cuda runtime error (100) : no CUDA-capable device is detected at /pytorch/aten/src/THC/THCGeneral.cpp:47
When trying torch==1.2.0 torchvision==0.4.0 with installing pillow==6.1 (otherwise Pillow==6.1 error) I got the following error:
RuntimeError: cuda runtime error (38) : no CUDA-capable device is detected at /pytorch/aten/src/THC/THCGeneral.cpp:50
All the trails the torch.cuda.is_available()
gives me "True". Therefore I don't understand why I get these errors.
The grafic card is: Tesla V100-SXM2-16GB
Does anyone know how to solve this problem?
Thank you!
from zooming-slow-mo-cvpr-2020.
Hi @HanClinto , thanks for your comments! I'm sure your gist would be very helpful for other ones.
As for the OOM issue, I recalled that it was also mentioned in previous issues. Thanks for your detailed feedback and the provided video again. I will try to modify my code to make it more memory-efficient for video processing.
from zooming-slow-mo-cvpr-2020.
@freedomlyle Very glad to hear it was helpful, thank you! :)
from zooming-slow-mo-cvpr-2020.
This no longer works. please update or delete
from zooming-slow-mo-cvpr-2020.
This no longer works. please update or delete
@noobtoob4lyfe what error are you having?
from zooming-slow-mo-cvpr-2020.
Related Issues (20)
- Windows support
- ValueError: Unknown CUDA arch (8.0) or GPU not supported HOT 1
- Zooming-Slow-Mo-CVPR-2020/codes/models/modules/DCNv2/_ext.cpython-37m-x86_64-linux-gnu.so: undefined symbol: HOT 1
- question about create_lmdb_mp.py HOT 2
- Regarding downsampling HOT 1
- Shared cells for bidirectional lstm HOT 2
- SSIM results HOT 1
- Change scale in video_to_zsm? HOT 4
- about video_to_zsm.py output HOT 1
- How can i train and test my datasets? HOT 7
- OOM HOT 11
- inference device HOT 1
- Offset mean is 145.10989379882812, larger than 100 HOT 1
- list object has no attribute 'add' HOT 2
- Custom Dataset Format
- Questions about Zooming Slow-mo validation on Vid4
- About Image Down Sampling
- OOM in train.py .
- some questions about testing HOT 1
- pytorch2
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from zooming-slow-mo-cvpr-2020.