Tracking code for the winner of track 1 in the MMP-Tracking Challenge at ICCV 2021 Workshop.

Related tags

Deep LearningMMP_Track1_ICCV21
Overview

Tracking Code for the winner of track1 in MMP-Trakcing challenge

This repository contains our tracking code for the Multi-camera Multiple People Tracking (MMP-Tracking) Challenge at ICCV 2021 Workshop.

1. Environment setup

This tracking code has been tested on Python 3.7.6, Pytorch 1.5.1, CUDA 10.1, please install related libraries before running this code:

pip install -r requirements.txt
pip install torch==1.5.1+cu101 torchvision==0.6.1+cu101 -f https://download.pytorch.org/whl/torch_stable.html

2. Detection

We provide the detection results on the test split in yolox_baseline.zip and yolox_finetune.zip. They should be extracted first.

3. Tracking

Run the following script to reproduce our tracking results.

sh auto_run.sh

4. Acknowledgement

We use YOLOX to train our detection model. Some code from deep_sort, FairMOT, and tao.

Owner
DamoCV
CV team of DAMO academy
DamoCV
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