mikel-brostrom / yolov3_deepsort_pytorch Goto Github PK

🐛 Bug

the link is 404 not found

RuntimeError: Could not run 'torchvision::nms' with arguments from the 'CUDA' backend. 'torchvision::nms' is only available for these backends: [CPU, BackendSelect, Named, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, Tracer, Autocast, Batched, VmapMode].

Actually, I didn't get this error and couldn't search anything about this on google.
Is there anybody who knows the way to handle this?

Info:
I installed the CUDA v11.1 from https://developer.nvidia.com/cuda-downloads
torch version: 1.7.0
torchvision version: 0.8.0

I am having trouble running the file and hope someone can help me.
When I run the track.py, I get the following:

F:\OOHAN\ZhuXY-Projects\MOT\DeepSort-mikel-brostrom\Yolov3_DeepSort_Pytorch>python track.py --source test.mp4
Loading weights from deep_sort/deep/checkpoint/ckpt.t7... Done!
return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
File "C:\python\anzhuang\envs\OOHANpytorch\lib\site-packages\torch\serialization.py", line 882, in _load
result = unpickler.load()
File "C:\python\anzhuang\envs\OOHANpytorch\lib\site-packages\torch\serialization.py", line 875, in find_class
return super().find_class(mod_name, name)
ModuleNotFoundError: No module named 'models'

Hi, I was trying to use the trained weights on my own model and was unable to access the file from google drive.

I was wondering if this file could be made public again?

Thank you!

Hi there, really appreciate ur sharing. Could u tell me what datasets u used when training the yolo in this person-only mode?

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During inference there's a small mistake you've done or maybe you didn't notice it.
when you check the detected output of yolo that is 'det'. you update the tracker using a list. now the thing you've missed is you push xywh list again and again into the tracker because of the iteration. all you have to do is do this push the entire list once. I've attached an image so you'll understand. just move the indent of deepsort.update and the next if loop which consist of drawing bounding box. this will make updating tracker and drawing bounding box n (number of objects detected in frame) times faster.

Hello,
I wanted to use the tracker with the GPU that I have on my machine, I dont want to use the docker file. I tried providing the --device argument but it doent work. I have a single GPU machine with Nvidia GTX 1060.

你好，
Downloading https://pjreddie.com/media/files/yolov3-spp-ultralytics.pt

链接失效，能提供百度云链接的.pt文件吗，非常感谢