Object Detection

About Object Detection

Last updated: June 2026

OptiPix Object Detection uses a YOLO-based AI model running in your browser to detect and label objects in your images. The model identifies common objects including people, vehicles, animals, furniture, electronics, and many more categories with bounding boxes and confidence scores. Each detected object is outlined with a colored bounding box and labeled with its category name and confidence percentage. This is useful for image analysis, content moderation, accessibility (describing image content), educational purposes, and understanding what objects are present in complex scenes. The AI model runs entirely in your browser using ONNX Runtime WebAssembly - no server uploads, complete privacy. The model downloads once and is cached for offline use. You can toggle label display on and off, and download the annotated image as a PNG file.

How It Works

The tool uses a YOLO (You Only Look Once) model running in your browser via ONNX Runtime WebAssembly. The image is preprocessed, fed through the neural network, and the output is decoded to produce bounding boxes with class labels and confidence scores.

Use Cases

• •Analyze images for content cataloging and tagging
• •Educational tool for learning about computer vision
• •Accessibility: describe image contents for visually impaired users
• •Content moderation to identify specific object types
• •Research and data analysis of image datasets

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If you find Object Detection useful, check out these related tools: Image Classifier, Depth Estimation, and Image Captioner. All tools run entirely in your browser with no uploads or signups required.