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hi,now i am facing a problem when i ran ./run_test.sh #18

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F0Wen opened this issue Dec 3, 2019 · 3 comments
Closed

hi,now i am facing a problem when i ran ./run_test.sh #18

F0Wen opened this issue Dec 3, 2019 · 3 comments

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@F0Wen
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F0Wen commented Dec 3, 2019

File "test_net.py", line 304, in
RCNN_loss_center, rois_label = fasterRCNN(im_data, im_info, gt_boxes,num_boxes, fixed_center)
File "/home/ld/.conda/envs/dave/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/ld/3d-vehicle-tracking/faster-rcnn.pytorch/lib/model/faster_rcnn/faster_rcnn.py", line 46, in forward
base_feat = self.RCNN_base(im_data)
File "/home/ld/.conda/envs/dave/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/ld/.conda/envs/dave/lib/python3.6/site-packages/torch/nn/modules/container.py", line 91, in forward
input = module(input)
File "/home/ld/.conda/envs/dave/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/ld/.conda/envs/dave/lib/python3.6/site-packages/torch/nn/modules/container.py", line 91, in forward
input = module(input)
File "/home/ld/.conda/envs/dave/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/ld/3d-vehicle-tracking/faster-rcnn.pytorch/lib/model/faster_rcnn/resnet.py", line 86, in forward
out = self.conv1(x)
File "/home/ld/.conda/envs/dave/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/ld/.conda/envs/dave/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 301, in forward
self.padding, self.dilation, self.groups)
RuntimeError: CUDA error: out of memory

@chrisHuxi
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It is exactly as the msg said: CUDA out of memory
I have this issue before too, my GPU is GTX1060 6GB, it is still not sufficient to load faster-rcnn model.
So I would suggest you either use a GPU with more mem., or you use the detection result from the author.

@F0Wen
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F0Wen commented Dec 5, 2019

Thanks! i have solved this problem by change a GPU with 9GB!

@kunshou123
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hi ,I run mono_3d_tracking.py
/home/work/3d-vehicle-tracking-master/3d-tracking/mono_3d_estimation.py gta test --data_split val --json_path /home/work/3d-vehicle-tracking-master/3d-tracking/data/gta5_tracking/val/label/rec_10090911_clouds_21h53m_x-968y-1487tox2523y214_bdd.json -j 2 -b 1 --n_box_limit 300 --resume ./checkpoint/616_gta_checkpoint_030.pth.tar
Using RoIAlign
=> Loading checkpoint './checkpoint/616_gta_checkpoint_030.pth.tar'
=> Successfully loaded checkpoint './checkpoint/616_gta_checkpoint_030.pth.tar' (epoch 30)
Reading /home/gejun/work/3d-vehicle-tracking-master/3d-tracking/data/gta5_tracking/val/label/rec_10090911_clouds_21h53m_x-968y-1487tox2523y214_bdd.json ...
Load single json file
Sequences [463] with total 463 frames
Input images are not normalized
Number of image to test: 463
0
1
Traceback (most recent call last):
File "/home/work/3d-vehicle-tracking-master/3d-tracking/mono_3d_estimation.py", line 539, in
main()
File "/home/work/3d-vehicle-tracking-master/3d-tracking/mono_3d_estimation.py", line 535, in main
test_model(model, args)
File "/home/work/3d-vehicle-tracking-master/3d-tracking/mono_3d_estimation.py", line 426, in test_model
for i, (image, box_info) in enumerate(iter(test_loader)):
File "/home/anaconda3/envs/pytorch041/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 336, in next
return self._process_next_batch(batch)
File "/home/anaconda3/envs/pytorch041/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 357, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
TypeError: init() missing 2 required positional arguments: 'doc' and 'pos'

Process finished with exit code 1

I find the code can iter 2 times normally ,then it broken ,can you give me some advice to solve it???

for i, (image, box_info) in enumerate(iter(test_loader)):
# measure data loading time
data_time.update(time.time() - end)
end = time.time()

    with torch.no_grad():
        box_output, targets = model(image, box_info, args.device, 'test')

    batch_time.update(time.time() - end)

=======================================================

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