ValueError: num_samples should be a positive integer value, but got num_samples=0 about afm_cvpr2019 HOT 10 OPEN

I also encountered this problem, the solution is: delete the .cache folder under data / wireframe, and then run python train.py again.

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@tianyu0523 Did you get a semgentation fault the previous time you ran that command? Because that is happening with me, and I traced it to the fact that the cache wasn't being built because something about the lib.afm_op custom code is failing and seg faulting on my AWS EC2 instance.

So if you comment out lines 48 - 53 in dataset/cache.py maybe you'll also see the same segmentation fault that I'm seeing?

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I'm wondering if there's anything incompatible with the custom cuda operator to CUDA version 9.0 because on the AWS EC2 instance it's running CUDA version 10.1...

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Does anyone meet this issue?

I guess this problem is caused by the cache directory. Please try to clean up the data/.cache directory and run the command again.

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I'm wondering if there's anything incompatible with the custom cuda operator to CUDA version 9.0 because on the AWS EC2 instance it's running CUDA version 10.1...

I tested my code on several machines with CUDA 9.0, 9.2 and 10.0, there is no incompatible issue.

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@cherubicXN thank you for replying!

I have a local GPU running ubuntu v. 18.04, python 3.6, and CUDA 9.2 and I have gotten your code working, but I still can't get it to run on the pytorch_p36 environment on the AWS EC2 GPU machines (p3.2xlarge, with python 3.6, cuda 10.1). For me it fails with a segmentation fault (!) at line 97 in cache.py where the command to the custom code is called:

afmap, label = afm(lines.cuda(),shape_info.cuda(), self.afm_res[0],self.afm_res[1])

If you're able to provide any input on this, so that I can run it on the new AWS EC2 instances, that'd be great!

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@tianyu0523 Did you get a semgentation fault the previous time you ran that command? Because that is happening with me, and I traced it to the fact that the cache wasn't being built because something about the lib.afm_op custom code is failing and seg faulting on my AWS EC2 instance.

So if you comment out lines 48 - 53 in dataset/cache.py maybe you'll also see the same segmentation fault that I'm seeing?

Yes. I met the same issue 'Segmentation fault (core dumped)' when I run the code on remote machine.

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Are you using an AWS EC2 instance, running CUDA 10.1 on python 3.6? If yes, then that version of CUDA may be the problem-I just dont know how to fix it!

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@cherubicXN
I need help in knowing if anyone trained the model for category-specific objects (introducing a new oject category)
I need somewhat precise 2D contour detection that'll allow me to overlay a 3D wireframe on top of that.
Any help will be appreciated.

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I change the 'shuffle=False' in line 17 of build.py and it works.

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