Welcome to the Real-Time Human Detection and Speed Estimation project! This project uses YOLOv8 for detecting humans in a live webcam feed and estimates their speed based on their movement. It also features a Gradio web app for real-time interaction and analysis.
This project utilizes several powerful libraries and tools to deliver its functionalities:
- YOLOv8: For human detection
- OpenCV: For handling video capture and frame processing
- Gradio: For creating an interactive web interface
- Google Colab: For running the project in a cloud environment
This project has the following use cases:
- Real-time Human Detection: Detects humans in a live webcam stream using YOLOv8.
- Speed Estimation: Tracks the detected humans and estimates their movement speed.
- Interactive Web Interface: Provides a Gradio-based interface to view the video feed and speed estimates in real time.
- Webcam Support: Works with any webcam connected to your system for capturing live video.
- YOLOv8 identifies humans in each frame of the video stream.
- The program tracks detected people across frames, calculates the distance they travel, and estimates their speed in meters per second.
- The Gradio app allows users to interact with the webcam feed and see the human detection and speed information in real-time.
You can try out this project directly on Google Colab by clicking the button below. It will open the Colab notebook, where you can run the project step-by-step.
git clone https://github.com/your-username/real-time-human-detection-speed-estimation.git
cd real-time-human-detection-speed-estimation