Comments (5)
You don't fulfill the minimum requirements @raja1196. I suggest you to upgrade to torch>=1.6 & python3.8.
Let me know if that solves the problem!
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Pip list:
torch 1.5.1+cu101
torchvision 0.6.1+cu101
opencv-python 4.4.0.44
python 3.6.12
Cuda:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
Nvidia:
NVIDIA-SMI 418.87.01 Driver Version: 418.87.01 CUDA Version: 10.1
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I have the same error! do you slove the problem?
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Not yet. I tried running it on different videos as well. Still the same error.
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@mikel-brostrom Yes, updating to the latest version of torch and python helped. Now the code is running as expected.
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Related Issues (20)
- In the boxmot project, the detection results of yolov8 are incorrect. HOT 1
- DEBUG level logs gets disabled after importing boxmot HOT 1
- 'StrongSORT' object has no attribute 'reset' HOT 2
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- Add SAHI techniques to detect small object for tracking task. HOT 3
- NotImplementedError HOT 1
- Is There BoxMOT package in C++ version? HOT 2
- HybridSORT fails due to Numpy Version HOT 9
- Can't create val_utils/scripts/run_mot_challenge.py HOT 1
- "--source streams.txt" cannot work HOT 1
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- can not download deepocsort's model HOT 1
- Inquiry on Replicating Experiments in Enhanced Tracking and ReID through Segmentation HOT 5
- It seems that there are several issues after updating the ultralytics version. Could you please fix the version in the requirements file so that we can easily run the yolo_tracking? HOT 2
- Predict the appearance area of an object after being obscured HOT 1
- HybridSORT errors after Numpy fix HOT 4
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