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Hands-On AI: Computer Vision Projects with Ultralytics and OpenCV
A practical, project-based computer vision course where you build working applications with Ultralytics YOLO and OpenCV. You learn by doing and ship real solutions: object counting, queue management, tracking objects inside zones, analytical graphs from your detections, and a Streamlit app to run inference in the browser.
What you'll learn
- Set up and run Ultralytics YOLO for object detection
- Process images and video with OpenCV
- Detect, track, and count objects in real footage
- Build hands-on projects end to end, not just theory
Projects you'll build
- Object counting in images and live video
- Queue management and waiting-line analysis
- Track and count objects inside custom zones
- Turn detections into analytical graphs and charts
- Run real-time YOLO inference in a Streamlit web app
- Estimate speed and movement of tracked objects