SeungjunNah / DeepDeblur-PyTorch

Deep Multi-scale CNN for Dynamic Scene Deblurring
MIT License
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Got errors in pyramid_gaussian function #5

Closed pz0910 closed 4 years ago

pz0910 commented 4 years ago

Got error : pyramid = list(pyramid_gaussian(img, n_scales-1, multichannel=True)) File "/home/jsgx/.conda/envs/pytorch/lib/python3.6/site-packages/skimage/transform/pyramids.py", line 197, in pyramid_gaussian image = img_as_float(image) File "/home/jsgx/.conda/envs/pytorch/lib/python3.6/site-packages/skimage/util/dtype.py", line 378, in img_as_float64 return convert(image, np.float64, force_copy) File "/home/jsgx/.conda/envs/pytorch/lib/python3.6/site-packages/skimage/util/dtype.py", line 244, in convert raise ValueError("Images of type float must be between -1 and 1.") ValueError: Images of type float must be between -1 and 1.

python main.py --n_GPUs 2 --batch_size 16 It seems image tensors have to be normlized to [-1,1]. Should I add --rgb_range=1 to solve this problem

SeungjunNah commented 4 years ago

@pz-AOE Strange. Which version for scikit-image are you using? I tested with scikit-image v0.16.2 and I always have [0, 255] input -> [0, 255] output for float32 type in the pyramid_gaussian function. This is as expected: see the image_as_float function description here. --rgb_range 255 should not have any problems.

pz0910 commented 4 years ago

@pz-AOE Strange. Which version for scikit-image are you using? I tested with scikit-image v0.16.2 and I always have [0, 255] input -> [0, 255] output for float32 type in the pyramid_gaussian function. This is as expected: see the image_as_float function description here. --rgb_range 255 should not have any problems.

Thanks for replying. I am using scikit-image v.014.0. I will try to upgrade the dependencies to check if it works. By the way, could you please share your yaml env file?

SeungjunNah commented 4 years ago

My main conda environment is for multiple purposes and it includes many unrelated packages to this project. Here are the versions I used for main dependencies.

imageio 2.8.0 numpy 1.18.1 matplotlib 3.2.1 tqdm 4.46.1 scikit-image 0.16.2 readline 8.0

If you want to create a new conda environment, the following would suffice.

conda install -y tqdm imageio scikit-image matplotlib readline
conda install -y pytorch torchvision cudatoolkit=10.2 -c pytorch
pz0910 commented 4 years ago

Problem solved by upgrading scikit-image to v0.16.2. Thanks

davidvct commented 7 months ago

if you are using RTX 4090 like me, cuda 10.2 is not compatible with it. I am using cuda 11.3, training seems to work (still ongoing). installation of cuda 11.3: conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.3 -c pytorch