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Comments (5)

ajtao avatar ajtao commented on May 24, 2024 1

Thanks @NirAharon , this is almost exactly what i ended up doing too. Appreciate your quick help.

BotSORT has been quite a nice improvement for me on challenging sports tracking cases. Thank you for the great tech!

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NirAharon avatar NirAharon commented on May 24, 2024

Hi, please try to use the demo.py I uploaded today.
Please let me know if errors occur.

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ajtao avatar ajtao commented on May 24, 2024

In code just pulled right now, seeing same error after a few hundred frames of tracking successfully.

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NirAharon avatar NirAharon commented on May 24, 2024

I found out that for cmc-method with ORB flag, the OpenCV function estimateAffinePartial2D could get too few matching points, which lead to an error.
I just updated the gmc.py code.
Thank you for your help.

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nmditai avatar nmditai commented on May 24, 2024

Hi @NirAharon , I just clone new code today, when demo I keep getting the same error. Can anyone help me figure out why?

[6:14 PM] Nguyen Minh Duc (QAI.DEL)
File "tools/demo.py", line 371, in
main(exp, args)
File "tools/demo.py", line 359, in main
imageflow_demo(predictor, vis_folder, current_time, args)
File "tools/demo.py", line 255, in imageflow_demo
online_targets = tracker.update(detections, img_info["raw_img"])
File "/home/Akacam/ducnm57/akacam_tracking/bot_tracking/tracker/bot_sort.py", line 285, in update
warp = self.gmc.apply(img, dets)
File "/home/Akacam/ducnm57/akacam_tracking/bot_tracking/tracker/gmc.py", line 62, in apply
return self.applyFeaures(raw_frame, detections)
File "/home/Akacam/ducnm57/akacam_tracking/bot_tracking/tracker/gmc.py", line 205, in applyFeaures
H, inliesrs = cv2.estimateAffinePartial2D(prevPoints, currPoints, cv2.RANSAC)
cv2.error: OpenCV(4.6.0) /io/opencv/modules/calib3d/src/ptsetreg.cpp:1108: error: (-215:Assertion failed) count >= 0 && to.checkVector(2) == count in function 'estimateAffinePartial2D

My command: python3 tools/demo.py video --path ./videos/cam1_ds.mp4 -f yolox/exps/example/mot/yolox_s_mix_det.py -c pretrained/bytetrack_s_mot17.pth.tar --with-reid --fuse-score --fp16 --fuse --save_result

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