Update README.md

Author: yehengchen

OneStage/yolo/deep_sort_yolov4/README.md

@@ -1 +1,106 @@
-hello
+# YOLOv4 + Deep_SORT
+
+<img src="https://github.com/yehengchen/video_demo/blob/master/video_demo/output.gif" width="40%" height="40%"> <img src="https://github.com/yehengchen/video_demo/blob/master/video_demo/TownCentreXVID_output.gif" width="40%" height="40%">
+<img src="https://github.com/yehengchen/Object-Detection-and-Tracking/blob/master/OneStage/yolo/yolo_img/output_person_315_1120_s.gif" width="40%" height="40%"> <img src="https://github.com/yehengchen/Object-Detection-and-Tracking/blob/master/img/output_car_143.gif" width="40%" height="40%">
+
+__Object Tracking & Counting Demo - [[YouTube]](https://www.youtube.com/watch?v=ALw3OfrGWGo) [[BiliBili_V1]](https://www.bilibili.com/video/av55778717) [[BiliBili_V2]](https://www.bilibili.com/video/av59547404)  [[Chinese Version]](https://blog.csdn.net/weixin_38107271/article/details/96741706)__
+## Requirement
+__Development Environment: [Deep-Learning-Environment-Setup](https://github.com/yehengchen/Ubuntu-16.04-Deep-Learning-Environment-Setup)__ 
+
+* OpenCV
+* sklean
+* pillow
+* numpy 1.15.0
+* tensorflow-gpu 1.13.1
+* CUDA 10.0
+***
+
+It uses:
+
+* __Detection__: [YOLOv4](https://github.com/yehengchen/ObjectDetection/tree/master/OneStage/yolo/yolov3) to detect objects on each of the video frames. - 用自己的数据训练YOLOv3模型
+
+* __Tracking__: [Deep_SORT](https://github.com/nwojke/deep_sort) to track those objects over different frames.
+
+*This repository contains code for Simple Online and Realtime Tracking with a Deep Association Metric (Deep SORT). We extend the original SORT algorithm to integrate appearance information based on a deep appearance descriptor. See the [arXiv preprint](https://arxiv.org/abs/1703.07402) for more information.*
+
+## Quick Start
+
+__0.Requirements__
+
+    pip install -r requirements.txt
+    
+__1. Download the code to your computer.__
+    
+    git clone https://github.com/yehengchen/Object-Detection-and-Tracking.git
+    
+__2. Download [[yolov4.weights]](https://pjreddie.com/media/files/yolov3.weights)__ and place it in `deep_sort_yolov3/model_data/`
+
+*Here you can download my trained [[yolo-spp.h5]](https://pan.baidu.com/s/1DoiifwXrss1QgSQBp2vv8w&shfl=shareset) - `t13k` weights for detecting person/car/bicycle,etc.*
+
+__3. Convert the Darknet YOLO model to a Keras model:__
+```
+$ python convert.py model_data/yolov3.cfg model_data/yolov3.weights model_data/yolo.h5
+``` 
+__4. Run the YOLO_DEEP_SORT:__
+
+```
+$ python main.py -c [CLASS NAME] -i [INPUT VIDEO PATH]
+
+$ python main.py -c person -i ./test_video/testvideo.avi
+```
+
+__5. Can change [deep_sort_yolov3/yolo.py] `__Line 100__` to your tracking object__
+
+*DeepSORT pre-trained weights using people-ReID datasets only for person*
+```
+    if predicted_class != args["class"]:
+               continue
+    
+    if predicted_class != 'person' and predicted_class != 'car':
+               continue
+```
+
+## Train on Market1501 & MARS
+*People Re-identification model*
+
+[cosine_metric_learning](https://github.com/nwojke/cosine_metric_learning) for training a metric feature representation to be used with the deep_sort tracker.
+
+## Citation
+
+### YOLOv3 :
+
+    @article{yolov3,
+    title={YOLOv3: An Incremental Improvement},
+    author={Redmon, Joseph and Farhadi, Ali},
+    journal = {arXiv},
+    year={2018}
+    }
+
+### Deep_SORT :
+
+    @inproceedings{Wojke2017simple,
+    title={Simple Online and Realtime Tracking with a Deep Association Metric},
+    author={Wojke, Nicolai and Bewley, Alex and Paulus, Dietrich},
+    booktitle={2017 IEEE International Conference on Image Processing (ICIP)},
+    year={2017},
+    pages={3645--3649},
+    organization={IEEE},
+    doi={10.1109/ICIP.2017.8296962}
+    }
+
+    @inproceedings{Wojke2018deep,
+    title={Deep Cosine Metric Learning for Person Re-identification},
+    author={Wojke, Nicolai and Bewley, Alex},
+    booktitle={2018 IEEE Winter Conference on Applications of Computer Vision (WACV)},
+    year={2018},
+    pages={748--756},
+    organization={IEEE},
+    doi={10.1109/WACV.2018.00087}
+    }
+    
+## Reference
+#### Github:deep_sort@[Nicolai Wojke nwojke](https://github.com/nwojke/deep_sort)
+#### Github:deep_sort_yolov3@[Qidian213 ](https://github.com/Qidian213/deep_sort_yolov3)
+
+
+