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Traffic Management System On Streamlit Apps

maven maven maven maven maven maven

This project is jointly completed by Zhao Zhiyuan, Li Yizhang and Wang Yifan

Background

The project is a final work for Applied Computer Vision courses. We try to detect some objetcs and show them in some visible ways. We've already deployed this project in Streamlit Apps.

Application

  1. Detect pedestrians on the highway and give warning.
2. Identify vehicles and pedestrians which are running red lights and save their pictures.

Usage

  1. Go to the app website https://share.streamlit.io/YUA1024/YUA1024/master/streamlit_app.py.
  2. Choose the services you are interested in.
  3. Choose the image you want to detect.
  4. The page will display the recognition results and give feedback.

How to run this project

pip install --upgrade streamlit opencv-python
streamlit run https://share.streamlit.io/YUA1024/YUA1024/master/streamlit_app.py  

Tool Landscape

  1. App Deployment Streamlit
  2. Editor Pycharm
  3. Model YOLOv3
  4. CI/CD Github Actions
  5. Language Python

Questions?Comments?

Email us by [email protected]

yua1024's Projects

demo-self-driving icon demo-self-driving

Streamlit app demonstrating an image browser for the Udacity self-driving-car dataset with realtime object detection using YOLO.

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