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# Towards-Realtime-MOT # Towards-Realtime-MOT
**NOTE:** Still in progress, will update constantly, thank you for your attention! **NEWS:**
- **[2019.10.11]** Training and evaluation data uploaded! Please see [DATASET_ZOO.MD](https://github.com/Zhongdao/Towards-Realtime-MOT/blob/master/DATASET_ZOO.MD) for details.
- **[2019.10.01]** Demo code and pre-trained model released!
## Introduction ## Introduction
This repo is the a codebase of the Joint Detection and Embedding (JDE) model. JDE is a fast and high-performance multiple-object tracker that learns the object detection task and appearance embedding task simutaneously in a shared neural network. Techical details are described in our [arXiv preprint paper](https://arxiv.org/pdf/1909.12605v1.pdf). By using this repo, you can simply achieve **MOTA 64%+** on the "private" protocol of [MOT-16 challenge](https://motchallenge.net/tracker/JDE), and with a near real-time speed at **18~24 FPS** (Note this speed is for the entire system, including the detection step! ) . This repo is the a codebase of the Joint Detection and Embedding (JDE) model. JDE is a fast and high-performance multiple-object tracker that learns the object detection task and appearance embedding task simutaneously in a shared neural network. Techical details are described in our [arXiv preprint paper](https://arxiv.org/pdf/1909.12605v1.pdf). By using this repo, you can simply achieve **MOTA 64%+** on the "private" protocol of [MOT-16 challenge](https://motchallenge.net/tracker/JDE), and with a near real-time speed at **18~24 FPS** (Note this speed is for the entire system, including the detection step! ) .
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--output-format video --output-root path/to/output/root --output-format video --output-root path/to/output/root
``` ```
## Dataset zoo ## Dataset zoo
Will be released later. Please see [DATASET_ZOO.MD](https://github.com/Zhongdao/Towards-Realtime-MOT/blob/master/DATASET_ZOO.MD) for detailed description of the training/evaluation datasets.
## Pretrained model and baseline models ## Pretrained model and baseline models
Darknet-53 ImageNet pretrained: [[DarkNet Official]](https://pjreddie.com/media/files/darknet53.conv.74) Darknet-53 ImageNet pretrained: [[DarkNet Official]](https://pjreddie.com/media/files/darknet53.conv.74)
JDE-1088x608-uncertainty: [[Google Drive]](https://drive.google.com/open?id=1nlnuYfGNuHWZztQHXwVZSL_FvfE551pA) [[Baidu NetDisk]](https://pan.baidu.com/s/1Ifgn0Y_JZE65_qSrQM2l-Q) JDE-1088x608-uncertainty: [[Google Drive]](https://drive.google.com/open?id=1nlnuYfGNuHWZztQHXwVZSL_FvfE551pA) [[Baidu NetDisk]](https://pan.baidu.com/s/1Ifgn0Y_JZE65_qSrQM2l-Q)
## Test on MOT-16 Challenge ## Test on MOT-16 Challenge
## Training ## Training instruction
### Train with custom datasets
## Train with custom datasets
## Acknowledgement ## Acknowledgement
A large portion of code is borrowed from [ultralytics/yolov3](https://github.com/ultralytics/yolov3) and [longcw/MOTDT](https://github.com/longcw/MOTDT), many thanks to their wonderful work! A large portion of code is borrowed from [ultralytics/yolov3](https://github.com/ultralytics/yolov3) and [longcw/MOTDT](https://github.com/longcw/MOTDT), many thanks to their wonderful work!