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View Code? Open in Web Editor NEWPytorch implementation of ICRA 2020 paper "360° Stereo Depth Estimation with Learnable Cost Volume"
License: MIT License
Pytorch implementation of ICRA 2020 paper "360° Stereo Depth Estimation with Learnable Cost Volume"
License: MIT License
Can you help me with this?
Epoch: 0%| | 0/500 [00:17<?, ?it/s]
Traceback (most recent call last):
File "main.py", line 348, in
main()
File "main.py", line 286, in main
loss = train(imgU_crop, imgD_crop, disp_crop)
File "main.py", line 196, in train
output1, output2, output3 = model(imgU, imgD)
File "/ssoft/spack/arvine/v1/opt/spack/linux-rhel7-skylake_avx512/gcc-8.4.0/py-torch-1.6.0-43xbre3fdhzp6upz6mfe3jk6rpwt5uky/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
result = self.forward(*input, **kwargs)
File "/ssoft/spack/arvine/v1/opt/spack/linux-rhel7-skylake_avx512/gcc-8.4.0/py-torch-1.6.0-43xbre3fdhzp6upz6mfe3jk6rpwt5uky/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 155, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/ssoft/spack/arvine/v1/opt/spack/linux-rhel7-skylake_avx512/gcc-8.4.0/py-torch-1.6.0-43xbre3fdhzp6upz6mfe3jk6rpwt5uky/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 165, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/ssoft/spack/arvine/v1/opt/spack/linux-rhel7-skylake_avx512/gcc-8.4.0/py-torch-1.6.0-43xbre3fdhzp6upz6mfe3jk6rpwt5uky/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 85, in parallel_apply
output.reraise()
File "/ssoft/spack/arvine/v1/opt/spack/linux-rhel7-skylake_avx512/gcc-8.4.0/py-torch-1.6.0-43xbre3fdhzp6upz6mfe3jk6rpwt5uky/lib/python3.7/site-packages/torch/_utils.py", line 395, in reraise
raise self.exc_type(msg)
TypeError: Caught TypeError in replica 0 on device 0.
Original Traceback (most recent call last):
File "/ssoft/spack/arvine/v1/opt/spack/linux-rhel7-skylake_avx512/gcc-8.4.0/py-torch-1.6.0-43xbre3fdhzp6upz6mfe3jk6rpwt5uky/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 60, in _worker
output = module(*input, **kwargs)
File "/ssoft/spack/arvine/v1/opt/spack/linux-rhel7-skylake_avx512/gcc-8.4.0/py-torch-1.6.0-43xbre3fdhzp6upz6mfe3jk6rpwt5uky/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in call_impl
result = self.forward(*input, **kwargs)
File "/work/vita/danial/360SD-Net/models/LCV_ours_sub3.py", line 187, in forward
refimg_fea.size()[3]).zero()).cuda()
TypeError: new(): argument 'size' must be tuple of ints, but found element of type float at pos 3
Can you please provide the pretrained model as I do not have the resources to train this data set?
Hi, nice work and thank you for your sharing !
From my perspective, the pixel in equirectangular projection is proportional to the degree_disparity.
For a 2*pi×pi equirectangular projection map, degree_disparity=i/pi where i in pixel coordinates disparity.
Please correct me if I'm wrong.
I have been creating 360 panos for some time now with my drone and the theta z1 camera.. can I inject my images to get 3d depth maps out of it?
Hi,
I am trying to run this code with our own synthetic dataset.
I rendered two equirectangular images 512x1024 with a vertical stereo setup as yours.
However, I got a questionalble result.
Belows are input_up_image, input_down_image, result_with_MP3D_ckpt, result_with_SF3D_ckpt, and result_with_Real_ckpt.
For the last one, I gave args.real = True.
Do you think I am running incorrectly? or are these expected results? Please let me know.
For more information, I ran testing.py, and I changed __imagenet_status in preprocess.py.
I didn't work with the original code:
__imagenet_stats = { 'mean': [0.485, 0.456, 0.406], 'std': [0.229, 0.224, 0.225] }
, so I added some numbers like
__imagenet_stats = { 'mean': [0.485, 0.456, 0.406, 1], 'std': [0.229, 0.224, 0.225, 1] }
and it didn't matter much which number I gave. Should I change these numbers to reproduce your performance?
I test the small inference,the output are "0.npy,1.npy,2.npy". how can i view the disparity image?
tensor.sub_(mean[:, None, None]).div_(std[:, None, None])
RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0
Could you please help me?
Hello, I download your sample images from MP3D and SF3D provided in this repository. But I found that the up-view and down-view pictures are almost the same in your folders. So there are no differences between them.
The same thing occur in realworld folder, too. Please check out in your convenience, and let me know if I am wrong.
Best.
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