Update README.md

README.md

@@ -1,51 +1,16 @@
-## TransTrack: Multiple Object Tracking with Transformer
+# H-TransTrack
 
-[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+## MODEL ZOO
+### MOT17 Validation
+Model | MOTA% | IDF1% | FN |  
+:---:|:---:|:---:|:---:|
+TransTrack | 67.1 | 70.3 | 15820 | 
+H-TransTrack | 68.7 | 68.3 | 13657 |
 
-![](transtrack.png)
-
-
-## Introduction
-[TransTrack: Multiple Object Tracking with Transformer](https://arxiv.org/abs/2012.15460)
-
-## Updates
-- (22/02/2022) Multi-GPU testing is supported. 
-- (29/10/2021) Automatic Mixed Precision(AMP) training is supported. 
-- (28/04/2021) Higher performance is reported by training on mixture of CrowdHuman and MOT, instead of first CrowdHuman then MOT. 
-- (28/04/2021) Higher performance is reported by pre-training both detection and tracking on CrowdHuman, instead of only detection. 
-- (28/04/2021) Higher performance is reported by increasing the number of queries from 300 to 500. 
-- (08/04/2021) Refactoring the code.  
-
-## MOT challenge
-Dataset | MOTA% | IDF1% | MOTP% | MT% | ML% |  FP | FN | IDS 
-:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:
-MOT17 | 74.5 | 63.9| 80.6 | 46.8 | 11.3 | 28323 | 112137 | 3663
-MOT20 | 64.5 | 59.2 | 80.0 | 49.1 | 13.6 | 28566 | 151377 | 3565
-
-## Validation set
-Training data | Training time | MOTA% | FP% | FN% | IDs% | download
-:---:|:---:|:---:|:---:|:---:|:---:|:---
-[crowdhuman, mot17_half](track_exps/crowdhuman_mot_trainhalf.sh) |  ~45h + 1h  | 67.1 | 3.1  | 29.4 | 0.5 | [671mot17_crowdhuman_mot17.pth](https://drive.google.com/drive/folders/1DjPL8xWoXDASrxgsA3O06EspJRdUXFQ-?usp=sharing)
-[crowdhuman](track_exps/crowdhuman_train.sh)                   |  ~45h       | 56.0 | 11.2 | 32.3 | 0.4 | [560mot17_crowdhuman.pth](https://drive.google.com/drive/folders/1DjPL8xWoXDASrxgsA3O06EspJRdUXFQ-?usp=sharing) 
-[mot17_half](track_exps/mot_trainhalf.sh)                        |  9h        | 61.9 | 3.4  | 34.0   |0.7 |[619mot17_mot17.pth](https://drive.google.com/drive/folders/1DjPL8xWoXDASrxgsA3O06EspJRdUXFQ-?usp=sharing_)
-
-Models are also available in [Baidu Drive](https://pan.baidu.com/s/1dcHuHUZ9y2s7LEmvtVHZZw) by code m4iv.
-
-#### Notes
-- We observe about 1 MOTA noise.
-- If the resulting MOTA of your self-trained model is not desired, playing around with the --track_thresh sometimes gives a better performance.
-- The default track_thresh is 0.4, except for 0.5 in crowdhuman.
-- The training time is on 8 NVIDIA V100 GPUs with batchsize 16.
-- We use the models pre-trained on imagenet.
-- (crowdhuman, mot17_half) is first training on crowdhuman, then fine-tuning on mot17_half.
-
-
-## Demo
-<img src="assets/MOT17-11.gif" width="400"/>  <img src="assets/MOT17-04.gif" width="400"/>
-
-
-## Installation
-The codebases are built on top of [Deformable DETR](https://github.com/fundamentalvision/Deformable-DETR) and [CenterTrack](https://github.com/xingyizhou/CenterTrack).
+Model | MOTA% | IDF1% | FN |
+:---:|:---:|:---:|:---:|
+TransTrack | 74.5 | 63.9| 112137 |
+H-TransTrack | 75.7 | 64.4 | 91155 |
 
 #### Requirements
 - Linux, CUDA>=9.2, GCC>=5.4
@@ -54,18 +19,6 @@ The codebases are built on top of [Deformable DETR](https://github.com/fundament
   You can install them together at [pytorch.org](https://pytorch.org) to make sure of this
 - OpenCV is optional and needed by demo and visualization
 
-
-#### Steps
-1. Install and build libs
-```
-git clone https://github.com/PeizeSun/TransTrack.git
-cd TransTrack
-cd models/ops
-python setup.py build install
-cd ../..
-pip install -r requirements.txt
-```
-
 2. Prepare datasets and annotations
 ```
 mkdir crowdhuman
@@ -91,75 +44,11 @@ python3 track_tools/crowdhuman_model_to_mot.py
 ```
 The pre-trained model is available [crowdhuman_final.pth](https://drive.google.com/drive/folders/1DjPL8xWoXDASrxgsA3O06EspJRdUXFQ-?usp=sharing).
 
-4. Train TransTrack
-```
-sh track_exps/crowdhuman_mot_trainhalf.sh
-```
+4. Train H-TransTrack
 
 5. Evaluate TransTrack
-```
-sh track_exps/mot_val.sh
-sh track_exps/mota.sh
-```
 
 6. Visualize TransTrack
 ```
 python3 track_tools/txt2video.py
 ```
-
-
-## Test set
-Pre-training data | Fine-tuning data | Training time | MOTA% | FP | FN | IDs
-:---:|:---:|:---:|:---:|:---:|:---:|:---:
-crowdhuman | mot17 | ~40h + 2h | 68.4 | 22137  | 152064  | 3942  
-crowdhuman | crowdhuman + mot17 | ~40h + 6h | 74.5 | 28323 | 112137 | 3663 
-
-#### Notes
-- Performance on test set is evaluated by [MOT challenge](https://motchallenge.net/).
-- (crowdhuman + mot17) is training on mixture of crowdhuman and mot17.
-- We won't release trained models for test test. Running as in Steps could reproduce them. 
-
-#### Steps
-1. Train TransTrack
-```
-sh track_exps/crowdhuman_mot_train.sh
-```
-
-or
-
-1. Mix crowdhuman and mot17
-```
-mkdir -p mix/annotations
-cp mot/annotations/val_half.json mix/annotations/val_half.json
-cp mot/annotations/test.json mix/annotations/test.json
-cd mix
-ln -s ../mot/train mot_train
-ln -s ../crowdhuman/CrowdHuman_train crowdhuman_train
-cd ..
-python3 track_tools/mix_data.py
-```
-2. Train TransTrack
-```
-sh track_exps/crowdhuman_plus_mot_train.sh
-```
-
-
-## License
-
-TransTrack is released under MIT License.
-
-
-## Citing
-
-If you use TransTrack in your research or wish to refer to the baseline results published here, please use the following BibTeX entries:
-
-```BibTeX
-
-@article{transtrack,
-  title   =  {TransTrack: Multiple-Object Tracking with Transformer},
-  author  =  {Peize Sun and Jinkun Cao and Yi Jiang and Rufeng Zhang and Enze Xie and Zehuan Yuan and Changhu Wang and Ping Luo},
-  journal =  {arXiv preprint arXiv: 2012.15460},
-  year    =  {2020}
-}
-
-```