Update README.md

Author: qbxlvnf11

README.md

@@ -1 +1,139 @@
-# byte-tracker-yolov3
+
+Description
+=============
+
+#### - ByteTrack
+- 
+
+#### - Yolov3
+- You only look once (YOLO) is one of the the powerful and real-time 1-stage object detection systems.
+- Improved features compared to yolov2: FPN,shortcut connection, logistic regression etc.
+- More details: [YOLOv3: An Incremental Improvement](https://arxiv.org/pdf/1804.02767.pdf)
+  
+Contents
+=============
+
+#### - Yolov3 Train/inference
+- Train yolov3 model
+- Detect image
+
+#### - Yolov3 TensorRT Engine
+- Convert yolov3 Pytorch weigths to TensorRT engine
+- Real-time inference with yolov3 TensorRT engine
+
+#### - Config files
+- yolov3_config.ini: yolov3 model parameters
+- train_config.ini: yolov3 train parameters
+- tensorrt_config.ini: yolov3 tensorrt parameters
+
+Yolov3 Run Environments with TensorRT 7.2.2 & Pytorch
+=============
+
+#### - Docker with TensorRT
+- https://docs.nvidia.com/deeplearning/tensorrt/container-release-notes/rel_20-12.html#rel_20-12
+
+#### - Docker pull
+```
+docker pull qbxlvnf11docker/tensorrt_20.12_yolov3:latest
+```
+
+#### - Docker run
+```
+nvidia-docker run -it --name yolov3_tensorrt -v {yolo-v3-tensorrt-repository-path}:/workspace/Yolov3 -w /workspace/Yolov3 qbxlvnf11docker/tensorrt_20.12_yolov3:latest bash
+```
+
+How to use
+=============
+
+#### - Build Yolov3 def cfg
+```
+./create_model_def.sh {class_num} {cfg_name}
+```
+
+#### - Download Pretrained Yolov3 Weights
+```
+./download_weights.sh
+```
+
+#### - Detect image with Yolov3
+- Params: refer to config files and parse_args()
+```
+python main.py --mode yolov3-detection-img
+```
+
+#### - Train Yolov3 Model
+- Params: refer to config files and parse_args()
+```
+python train.py --mode yolov3-train
+```
+
+#### - Build TensorRT engine
+- Params: refer to config files and parse_args()
+```
+python yolov3_convert_onnx_tensorrt.py --yolov3_config_file_path ./config/yolov3_config.ini --tensorrt_config_file_path ./config/tensorrt_config.ini
+```
+
+Build Dataset
+=============
+
+#### - Download COCO2014 dataset
+```
+./get_coco_dataset.sh
+```
+
+#### - Build Data json files
+- Building data json for optimizing yolov3
+- In train process, read builded data json file and get train data
+- Params: refer to parse_args()
+```
+python yolov3_convert_onnx_tensorrt.py --target coco2014 --data_folder_path ./data/train_data/coco --save_folder_path ./data/data_json/coco
+```
+
+#### - Format of data json files
+- parsing_data_dic['class_format'] = type of class ('name' or 'id')
+- parsing_data_dic['label_scale'] = scale of label ('absolute' or 'relative')
+- parsing_data_dic['image_list'] = [{'id'-image id, 'image_file_path'-image file path}, ...]
+- parsing_data_dic['object_boxes_list'] = [{'image_id'-image id, 'object_box_num'-number of the object per image, 'object_box_id_list'-[object box id, ...], 'object_name_list'-[object name, ...], 'object_box_list'-[[center x, center y, box_width, box_height], ...], 'object_box_size_list'-[object box size, ...], }, ...]
+- parsing_data_dic['image_num'] = number of the image
+- parsing_data_dic['object_boxes_num'] = [number of the total objects, ...]
+
+References
+=============
+
+#### - ByteTrack Paper
+```
+@article{ByteTrack,
+  title={ByteTrack: Multi-Object Tracking by Associating Every Detection Box},
+  author={Yifu Zhang et al.},
+  journal = {arXiv},
+  year={2018}
+}
+```
+
+#### - Yolov3 Paper
+```
+@article{yolov3,
+  title={YOLOv3: An Incremental Improvement},
+  author={Redmon, Joseph and Farhadi, Ali},
+  journal = {arXiv},
+  year={2018}
+}
+```
+
+#### - ByteTrack Pytorch
+
+https://github.com/ifzhang/ByteTrack
+
+#### - Yolov3 with TensorRT
+
+https://github.com/qbxlvnf11/yolo-v3-tensorrt
+
+Author
+=============
+
+#### - LinkedIn: https://www.linkedin.com/in/taeyong-kong-016bb2154
+
+#### - Blog URL: https://blog.naver.com/qbxlvnf11
+
+#### - Email: qbxlvnf11@google.com, qbxlvnf11@naver.com
+