Frame Rate Agnostic Multi-Object Tracking
This project aims to perform Multi-Object Tracking on multiple frame rate inputs, unknown frame rate inputs and dynamic frame rate inputs, leading to a smarter tracking solution called Frame Rate Agnositic Multi-Object Tracking.
Our paper: paper
This repo is still under development and refactorization.
MOT20 checkpoints: Joint Extractor Association Module
put the joint extractor checkpoint as checkpoints/assoc_re2/ckpt_latest.pth and put the association module checkpoint as checkpoints/assoc_re2/association.pth
Comming Soon!
Taking inference on MOT20 as an example:
cd EOD
python -u -m eod train --config configs/tracking/base_x_m20_mhvfl_assoc_base_afr_p3.yaml --nm 1 --ng 4 --launch pytorch -e--ng is to set how many GPU could be used, modify as the number of your devices.
Coming Soon!
The multi-frame-rate dataset generation and evaluation code can be found at https://github.com/Helicopt/FraMOT-eval.
A large part of the code base is borrowed from an older version of project ModelTC/United-Perception (previously called EOD). Thanks for the hardwork of contributors in the UP project!