yolov4-deepsort
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can't see bounding boxes
I couldn't see any bounding box can anyone please suggest me a solution and also the info flag is not working.
Hi. I am facing the same issue on my local PC with GeForce RTX 3060 (6GB) but when I run the code on Goolge Colab, everything seems to work very much fine. If you are able to dig into the issue and find a solution please do share.
Hey I resolved the issue by upgrading the tensorflow version to 2.5.
pip install tensorflow-gpu==2.5
The above command did the job for me. Good luck.
Thanks for your suggestion brother but i am already having tensorflow-gpu 2.8.0 still no bounding boxes.
I also couldn't see any bounding box and I print the pred_bbox, only the first frame have output pred_bbox. I had this problem before starting. QObject::moveToThread: Current thread (0x563bcd421950) is not the object's thread (0x563b8b6d2fb0). Cannot move to target thread (0x563bcd421950)
I don't know it is affects the result?
tensorflow-gpu 2.8.0 yolov4-tiny I couldn't see any bounding boxes
tensorflow-gpu 2.8.0 yolov4-tiny I couldn't see any bounding boxes
I used tensorflow-gpu 2.3.0 and It worked finally
Hello guys, I also face the same issue with the gpu, but the code work fine on the cpu. So i try to convert the model with tensorflow cpu and run the object_tracking with tensorflow gpu.
Yes, it is working fine with CPU. I there is an issue with the working of GPU tensorflow
due to dependency
Hello guys, I also face the same issue with the gpu, but the code work fine on the cpu. So i try to convert the model with tensorflow cpu and run the object_tracking with tensorflow gpu.
I confirm this method works and I managed to get the bounding box now!!! Specifically, I performed the save_model.py command using tf-cpu (i.e., tensorflow==2.3.0) environment. For real-time inference, I use the tf-gpu (i.e., tensorflow==2.4.1) environment. Note that the libraries are created via anaconda environment only (i.e., no pip required).
Take the demo.avi as an example, the mean real-time inference performance I observed are 2fps (tf-cpu) as opposed to 22fps (tf-gpu) on a 2080Ti.
Hope this information helps everyone else.
tensorflow-gpu 2.8.0 yolov4-tiny I couldn't see any bounding boxes
I used tensorflow-gpu 2.3.0 and It worked finally
For the benefit of people like me, note the OS dependency differences for tensorflow-gpu package, I observed the following based on conda-forge channel:
- (Windows OS) tensorflow-gpu -> {2.3.0, 2.5.0, 2.6.0} are available
- (Linux OS - Ubuntu) tensorflow-gpu -> {2.2.0, 2.4.1, 2.6, 2.7, 2.8} are available
Hello guys, I also face the same issue with the gpu, but the code work fine on the cpu. So i try to convert the model with tensorflow cpu and run the object_tracking with tensorflow gpu.
I confirm this method works and I managed to get the bounding box now!!! Specifically, I performed the save_model.py command using tf-cpu (i.e., tensorflow==2.3.0) environment. For real-time inference, I use the tf-gpu (i.e., tensorflow==2.4.1) environment. Note that the libraries are created via anaconda environment only (i.e., no pip required).
Take the demo.avi as an example, the mean real-time inference performance I observed are 2fps (tf-cpu) as opposed to 22fps (tf-gpu) on a 2080Ti.
Hope this information helps everyone else.
Hello, I did as your tip that performed the save_model.py command using tf-cpu ( tensorflow==2.3.0) environment. For real-time inference, I use the tf-gpu (tensorflow-gpu==2.3.0) environment. But there is no detection.
How to deal with that.
Best wishes
Hi. I am facing the same issue on my local PC with GeForce RTX 3060 (6GB) but when I run the code on Goolge Colab, everything seems to work very much fine. If you are able to dig into the issue and find a solution please do share.
Could you once state the tensorflow-gpu and opencv-python versions you were using back then to run the deepSORT model?
Hello guys, I also face the same issue with the gpu, but the code work fine on the cpu. So i try to convert the model with tensorflow cpu and run the object_tracking with tensorflow gpu.
I confirm this method works and I managed to get the bounding box now!!! Specifically, I performed the save_model.py command using tf-cpu (i.e., tensorflow==2.3.0) environment. For real-time inference, I use the tf-gpu (i.e., tensorflow==2.4.1) environment. Note that the libraries are created via anaconda environment only (i.e., no pip required). Take the demo.avi as an example, the mean real-time inference performance I observed are 2fps (tf-cpu) as opposed to 22fps (tf-gpu) on a 2080Ti. Hope this information helps everyone else.
Hello, I did as your tip that performed the save_model.py command using tf-cpu ( tensorflow==2.3.0) environment. For real-time inference, I use the tf-gpu (tensorflow-gpu==2.3.0) environment. But there is no detection.
How to deal with that.
Best wishes
Did you find the solution to this? Even I'm facing the same issues.
tensorflow-gpu 2.8.0 yolov4-tiny I couldn't see any bounding boxes
I used tensorflow-gpu 2.3.0 and It worked finally
Opencv_python version?