GraphNN-Multi-Object-Tracking
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Unofficial PyTorch implementation of "Learning a Neural Solver for Multiple Object Tracking"
Hi @selflein , I'm trying to do testing using a test set on which I've used YOLOV4; the output format is the same as MOT16, so I think I need...
I tried to reproduce the result of MOT16-02 in inference.ipynb by using the provided pretrained weight. But got this result. IDF1 IDP IDR Rcll Prcn GT MT PT ML FP...
hi, thank you for the wonderful work and offer the code for us. If I train a separate ReID model, then I want to add this model in the code,...
parser.add_argument('--preprocessed_dir', type=str...., ) all_tracks = get_track_dict(Path(args.preprocessed_dir), Path(args.net_weights)) ##the all_tracks nedds args.preprocessed_dir, but it is preprocessed_sequences in parser. so this makes a error is 'Namespace' object has no attribute 'preprocessed_dir'
Thank you so much for sharing the implementation. I tried to train the model by the original setting of this implementation but the results are not good. Do you use...
Hi, thanks for sharing this valuable code. I just want to learn if we can modify your approach to train on our custom datasets, which may contain multiple classes other...
Hi, thank you for share your wonderful work! But how can I get the supplementary material for this paper?
As the title indicates, I hope to get your help, thank you!