Thanks for the amazing work again!

After replacing the SORT kalman filter in ocsort.py with the JDE kalman filter, I got higher HOTA and faster speed, which may indicates that ocsort with SORT settings can be improved.

So, do you plan to provide a version of ocsort with BYTE?

Hello, I ran the evaluation code "python tools/run_ocsort_dance.py -f exps/example/mot/yolox_dancetrack_val.py -c pretrained/bytetrack_dance_model.pth.tar -b 1 -d 1 --fp16 --fuse --expn /output", and got the dancetrack0004.txt like this: "1,3.0,772.2,309.5,261.9,767.8,-1,-1,-1,-1 1,2.0,969.3,414.5,299.7,579.2,-1,-1,-1,-1" what are the means of these numbers, and how can i use them?

Dear @noahcao , How you can evaluate the result of KITTI test set? I submit to KITTI tracking benchmark but it is not in right format. Hope to receive your answer soon. BRs, cuong

Update OC-SORT with BYTE in ByteTrack.

With run_ocsort_dance_BYTE.py, pretrained model and default settings, you can simply get both higher MOTA and HOTA than original OC-SORT and ByteTrack.

I want to try and run OC-SORT with a few different detectors (YoloV5, F-RCNN, CNN) just to experiment and see how well the detectors perform with OC-SORT.

when i run the demo given in README, i can not find the pretrained model "bytetrack_dance_model.pth.tar", and i used "ocsort_dancetrack.pth.tar" given in model zoo, python tools/demo_track.py --demo_type video -f exps/example/mot/yolox_dancetrack_test.py -c pretrained/bytetrack_dance_model.pth.tar --path videos/dance_demo.mp4 --fp16 --fuse --save_result --out_path demo_out.mp4, but the result has no any bounding boxes?

I got errors like these:

my environment like this: pytorch==1.7.1 python==3.8 cuda==11.0

and i run this: conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=11.0 -c pytorch

I can successfully run evaluation code for MOT17 and MOT20 and video demo. But I got an error in training for MOT20, using 'python tools/train.py -f exps/example/mot/yolox_x_mix_mot20_ch.py -d 1 -b 48 --fp16 -o -c pretrained/yolox_x.pth', like this:

I successfully ran the code last week. But i failed today. I strcutly follow the readme, and installed libglib2.0-dev. I want to test the video you provided.

python3 tools/demo_track.py --demo_type video -f exps/example/mot/yolox_dancetrack_test.py -c pretrained/bytetrack_dance_model.pth.tar --path videos/dance_demo.mp4 --fp16 --fuse --save_result --out_path demo_out.mp4

And i got an error like this: I also got this error last week, and change the path to solve it, and then i got other errors. I do not want to modify this code. Why is it happen? What should i do to sovle it?

Thanks for the amazing work!

But I find something confusing when using oc-sort. At the beginning of tracking (like frame 2), the input variables of function speed_direction_batch() is detections and previous_obs.

But the previous_obs is [-1, -1, -1, -1, -1], which I don't think is normal.

Is it an issue, or I should just ignore it?

@noahcao Hi! when I run : python3 tools/run_ocsort.py -f exps/example/mot/yolox_x_ablation.py -c pretrained/bytetrack_ablation.pth.tar -b 1 -d 1 --fp16 --fuse --expn MOT17

the error is :

File "tools/run_ocsort.py", line 32, in compare_dataframes accs.append(mmp.utils.compare_to_groundtruth(gts[k], tsacc, 'iou', distth=0.5,vflag = vflag)) TypeError: compare_to_groundtruth() got an unexpected keyword argument 'vflag'

I generated track results using OC-SORT, but facing problem when submitted results to motchallenge server. submission happens successfully but unable to get evaluation results. if you provide your results i can check the issue.

Hi, thanks for your great work.

I've tried to conduct ablation study of OOS/OCM/OCR on MOT17-val. However, in my experiments, OOS doesn't work.

I turn off "OOS" by set orig=True in class KalmanBoxTracker:

class KalmanBoxTracker(object):
    """
    This class represents the internal state of individual tracked objects observed as bbox.
    """
    count = 0

    def __init__(self, bbox, delta_t=3, orig=False):
        """
        Initialises a tracker using initial bounding box.

        """
        orig = True  # <= I added this line
        # define constant velocity model
        ...

And my results is (HOTA/MOTA/IDF1):

• with OOS: 66.341 / 74.504 / 77.874
• w/o OOS: 66.442 / 74.665 / 77.864

Could you tell me if it is because of my mistakes or other reasons? Thanks!

Hi,

I needed to run OC-SORT from MATLAB with a matrix of detections and get a matrix of tracks back. I wrote a simple wrapper function based on your code and it seems to be working. I needed to make a minor change to the init function of the OCSORT class and I changed the result writing portion as well. I seem to be getting the same results as your original script, so I think it is working fine. Would you like me to share the code with you?