CalTrans Project Learning Model Environment

Description:
This is the demo version of the CalTrans Project real-time vehicle detection part
This version can process the video stream from the camera and detect the vehicles
Environment is based on the:

1. opencv-python
2. numpy, and Flask
   Dowload the following files:
3. yolov3 weights
4. yolov3.cfg
5. coco.names
   Place the yolov3.weights, yolov3.cfg, and coco.names in the same folder as the python script
   Install run the following command:
   pip install flask
pip install opencv-python
pip install numpy
   Clone the repository:
   git clone https://github.com/RuitaoWu/CalTransProjLearningModel.git
cd CalTransProjLearningModel
python3 app.py

---

Working Tree update

C:.
│   .gitignore
│   app.py
│   coco.names
│   config.ini
│   config.py
│   framemaker.py
│   GOPR0787.MP4
│   index.html
│   json_load.py
│   objRealTimeDectector.py
│   README.MD
│   result.json
│   test.mp4
│   viewcount.php
│   websocketdemo2.py
│   yolo.ipynb
│
├───data
│       test.csv
│
├───dumps
│       server.sql
│
├───static
│   │   app.js
│   │   chart.js
│   │   content.css
│   │   echarts.min.js
│   │   gallery.css
│   │   home.js
│   │   jQuery_mini.js
│   │   map.js
│   │   socket.io.min.js
│   │   socket.io.min.js.map
│   │   style.css
│   │   styles.css
│   │
│   └───images
│           .DS_Store
│           light gray.jpg
│           pic1.svg
│           point cloud.jpg
│           point cloud.svg
│           realtime-example.jpg
│
├───templates
│       index.html
│       websocketdemo2.html
│
├───YOLO
│       Readme
│       savayolo
│       yolov3.cfg
│       yolov3.weights
│
└───__pycache__
        config.cpython-39.pyc
        model.cpython-39.pyc
        objRealTimeDectector.cpython-39.pyc