Object Detection

Object detection is what lets a removal tool understand a photo before you touch it. A detection model scans the image and returns the objects it recognizes — a person, a car, a sign, a power line — each with a location, so the editor can offer to remove them with a single tap instead of requiring you to brush a mask by hand. It's the difference between 'paint over the thing you want gone' and 'tap the thing the AI already found.' Object detection pairs with image segmentation (which traces each object's exact outline) to produce a precise inpainting mask automatically: detection says *what and roughly where*, segmentation says *exactly which pixels*, and AI Fill reconstructs the background. In Magic Eraser this is the auto-detect workflow — the model proposes removable objects so casual users get clean results without learning masking. Detection accuracy is why modern AI removal feels effortless on common subjects (people, vehicles, animals) and why unusual, tiny, transparent, or heavily occluded objects sometimes still need a manual brush. For the best result, use auto-detect first, then refine the mask when the suggested boundary misses shadows, reflections, or fine edges.