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https://github.com/peizhaoli05/EDA_GNN
Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
https://github.com/peizhaoli05/EDA_GNN
Last synced: about 1 month ago
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Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
- Host: GitHub
- URL: https://github.com/peizhaoli05/EDA_GNN
- Owner: peizhaoli05
- Created: 2019-05-04T09:19:26.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2022-11-22T03:47:46.000Z (about 2 years ago)
- Last Synced: 2024-08-03T22:14:03.638Z (5 months ago)
- Language: Python
- Homepage:
- Size: 35.2 KB
- Stars: 64
- Watchers: 4
- Forks: 19
- Open Issues: 8
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-multiple-object-tracking - [code
README
# Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
A PyTorch implementation combines with Siamese Network and Graph Neural Network for Online Multiple-Object Tracking.Dataset available at [https://motchallenge.net/]
According paper can be found at [https://arxiv.org/abs/1907.05315]
## How to run
Use `python main.py` to train a model from scratch. Settings for training is in `config.yml`.
Use `python tracking.py` to track a test video, meanwhile you need to provide the detected objects & tracking results for the first five frames. Setting for tracking is in `setting/`.## Requirements
- Python 2.7.12
- numpy 1.11.0
- scipy 1.1.0
- torchvision 0.2.1
- opencv_python 3.3.0.10
- easydict 1.7
- torch 0.4.1
- Pillow 6.2.0
- PyYAML 5.1