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+# OC_SORT
+
+## Model description
+Observation-Centric SORT (OC-SORT) is a pure motion-model-based multi-object tracker. It aims to improve tracking robustness in crowded scenes and when objects are in non-linear motion. It is designed by recognizing and fixing limitations in Kalman filter and SORT. It is flexible to integrate with different detectors and matching modules, such as appearance similarity. It remains, Simple, Online and Real-time.
+
+## Step 1: Installing
+```bash
+git clone https://github.com/PaddlePaddle/PaddleDetection.git
+```
+
+```bash
+cd PaddleDetection
+yum install mesa-libGL -y
+
+pip3 install -r requirements.txt
+pip3 install protobuf==3.20.1
+pip3 install urllib3==1.26.6
+pip3 install certifi==2018.8.13
+
+```
+
+## Step 2: Prepare Datasets
+
+Download [MOT17](https://motchallenge.net/), [MOT20](https://motchallenge.net/), [CrowdHuman](https://www.crowdhuman.org/), [Cityperson](https://github.com/Zhongdao/Towards-Realtime-MOT/blob/master/DATASET_ZOO.md), [ETHZ](https://github.com/Zhongdao/Towards-Realtime-MOT/blob/master/DATASET_ZOO.md) and put them under <ByteTrack_HOME>/datasets in the following structure:
+
+```bash
+datasets
+   |——————mot
+   |        └——————train
+   |        └——————test
+   └——————crowdhuman
+   |         └——————Crowdhuman_train
+   |         └——————Crowdhuman_val
+   |         └——————annotation_train.odgt
+   |         └——————annotation_val.odgt
+   └——————MOT20
+   |        └——————train
+   |        └——————test
+   └——————Cityscapes
+   |        └——————images
+   |        └——————labels_with_ids
+   └——————ETHZ
+            └——————eth01
+            └——————...
+            └——————eth07
+```
+
+## Step 3: Training
+
+```bash
+cd PaddleDetection
+
+python3 -m paddle.distributed.launch --log_dir=ppyoloe --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/mot/bytetrack/detector/yolox_x_24e_800x1440_mix_mot_ch.yml --eval --amp
+```
+
+## Step 4: result
+
+## Reference
+- [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)