pytorch dataloader stucked if using opencv resize method

I can run all the cells of the tutorial notebook of Pytorch about dataloading (pytorch tutorial).
But when I use OpenCV in place of Skimage to resize the image, the dataloader gets stuck, i.e nothing happens.

In the Rescale class:

class Rescale(object):

    .....

    def __call__(self, sample):

       ....

       #img = transform.resize(image, (new_h, new_w))

       img = cv2.resize(image, (new_h, new_w))

       .....

The dataloader and the for loop are defined with:

dataloader = DataLoader(transformed_dataset, batch_size=4,

                        shuffle=True, num_workers=4)



for i_batch, sample_batched in enumerate(dataloader):

    print(i_batch, sample_batched['image'].size(),

          sample_batched['landmarks'].size())

I can get the iterator to print something if num_workers=0. It looks like opencv does not play well with the Multiprocessing of pytorch.
I would really prefer to use same package to transform the images at train time and test time (and I am already using OpenCV for the image rescale at test time).
Any suggestions would be greatly appreciated.

asked Jan 2 at 22:11

JMarc

445615

Try cv2.ocl.setUseOpenCL(False)

– Kinght 金
Jan 3 at 1:14

add a comment |

In the Rescale class:

class Rescale(object):

    .....

    def __call__(self, sample):

       ....

       #img = transform.resize(image, (new_h, new_w))

       img = cv2.resize(image, (new_h, new_w))

       .....

The dataloader and the for loop are defined with:

dataloader = DataLoader(transformed_dataset, batch_size=4,

                        shuffle=True, num_workers=4)



for i_batch, sample_batched in enumerate(dataloader):

    print(i_batch, sample_batched['image'].size(),

          sample_batched['landmarks'].size())

asked Jan 2 at 22:11

JMarc

445615

Try cv2.ocl.setUseOpenCL(False)

– Kinght 金
Jan 3 at 1:14

add a comment |

In the Rescale class:

class Rescale(object):

    .....

    def __call__(self, sample):

       ....

       #img = transform.resize(image, (new_h, new_w))

       img = cv2.resize(image, (new_h, new_w))

       .....

The dataloader and the for loop are defined with:

dataloader = DataLoader(transformed_dataset, batch_size=4,

                        shuffle=True, num_workers=4)



for i_batch, sample_batched in enumerate(dataloader):

    print(i_batch, sample_batched['image'].size(),

          sample_batched['landmarks'].size())

asked Jan 2 at 22:11

JMarc

445615

In the Rescale class:

class Rescale(object):

    .....

    def __call__(self, sample):

       ....

       #img = transform.resize(image, (new_h, new_w))

       img = cv2.resize(image, (new_h, new_w))

       .....

The dataloader and the for loop are defined with:

dataloader = DataLoader(transformed_dataset, batch_size=4,

                        shuffle=True, num_workers=4)



for i_batch, sample_batched in enumerate(dataloader):

    print(i_batch, sample_batched['image'].size(),

          sample_batched['landmarks'].size())

python-2.7 opencv multiprocessing pytorch scikit-image

asked Jan 2 at 22:11

JMarc

445615

asked Jan 2 at 22:11

JMarc

445615

asked Jan 2 at 22:11

JMarc

445615

asked Jan 2 at 22:11

JMarc

445615

asked Jan 2 at 22:11

JMarc

445615

Try cv2.ocl.setUseOpenCL(False)

– Kinght 金
Jan 3 at 1:14

add a comment |

Try cv2.ocl.setUseOpenCL(False)

– Kinght 金
Jan 3 at 1:14

Try cv2.ocl.setUseOpenCL(False)

– Kinght 金
Jan 3 at 1:14

add a comment |

1 Answer
1

active

oldest

votes

I had a very similar problem and that's how I solved it:

when you import cv2 set cv2.setNumThreads(0)
and then you can set num_workers>0 in the dataloader in PyTorch.

Seems like OpenCV tries to multithread and somewhere something goes into a deadlock.

Hope it helps.

answered Feb 9 at 3:25

Aidas Liaudanskas

214

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

I had a very similar problem and that's how I solved it:

when you import cv2 set cv2.setNumThreads(0)
and then you can set num_workers>0 in the dataloader in PyTorch.

Seems like OpenCV tries to multithread and somewhere something goes into a deadlock.

Hope it helps.

answered Feb 9 at 3:25

Aidas Liaudanskas

214

add a comment |

I had a very similar problem and that's how I solved it:

when you import cv2 set cv2.setNumThreads(0)
and then you can set num_workers>0 in the dataloader in PyTorch.

Seems like OpenCV tries to multithread and somewhere something goes into a deadlock.

Hope it helps.

answered Feb 9 at 3:25

Aidas Liaudanskas

214

add a comment |

I had a very similar problem and that's how I solved it:

when you import cv2 set cv2.setNumThreads(0)
and then you can set num_workers>0 in the dataloader in PyTorch.

Seems like OpenCV tries to multithread and somewhere something goes into a deadlock.

Hope it helps.

answered Feb 9 at 3:25

Aidas Liaudanskas

214

I had a very similar problem and that's how I solved it:

when you import cv2 set cv2.setNumThreads(0)
and then you can set num_workers>0 in the dataloader in PyTorch.

Seems like OpenCV tries to multithread and somewhere something goes into a deadlock.

Hope it helps.

answered Feb 9 at 3:25

Aidas Liaudanskas

214

answered Feb 9 at 3:25

Aidas Liaudanskas

214

answered Feb 9 at 3:25

Aidas Liaudanskas

214

answered Feb 9 at 3:25

Aidas Liaudanskas

214

add a comment |

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