Video Object Detection is a browser-based app that uses a YOLOv9 model to detect and label objects in real-time from your webcam feed. It draws bounding boxes and labels on detected items, allowing users to observe object recognition live without server-side computation. Ideal for developers and computer vision enthusiasts.
Video Object Detection is a Video generation project. It focuses on detecting and labeling objects in live video streams directly in the browser without server-side processing. It is built as a consumer product for developers and computer vision enthusiasts. Video Object Detection costs nothing to use. It runs on the web.
It is developed by Xenova, and it first shipped in 2024. Among its 5 catalogued features are live object detection, webcam access, and bounding boxes.
Summary written by a language model from the project’s public pages.
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