Object Detection

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Object detection is a computer vision task that not only identifies what appears in an image but also pinpoints where each object is located. When given an image or a video frame, an object detection model outputs bounding boxes and labels for every detected item, such as people or animals.

This type of computer vision is widely used in situations where knowing the exact location of objects matters, for example, autonomous driving, retail analytics, and medical imaging. To judge performance, teams look at metrics like mean average precision or Intersection over Union, which measure how accurately the model finds and outlines each object. Unlike simple image classification, object detection has to deal with multiple overlapping objects, different sizes, and varying positions within the frame. This makes the task more challenging, but it also provides richer information about the scene.

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