Python YOLO Object Detection App

I want a small, self-contained Python program that opens my webcam, runs a YOLO pre-trained model, and draws labeled bounding boxes around the usual everyday items—person, bottle, mobile phone, etc.—whenever they appear in the frame. Please write it in clear, well-commented code that leans on OpenCV (cv2) for video capture and display. You’re free to pull the model weights from any reliable public source as long as setup remains simple (a short [login to view URL] and one-step download script are perfect). Deliverables • A runnable demo script that starts the webcam and shows real-time detection • All source files, neatly organised, including a brief README explaining environment setup, how to launch the app, and where to place or fetch the YOLO weights • A short note (markdown or inline comments) outlining the key sections of the code—model loading, frame preprocessing, inference, post-processing, and drawing boxes—so I can follow the flow easily If the detection runs smoothly at decent FPS on a typical laptop and correctly tags the specified objects, the job is done.

Project ID: 40420815