AI Object Detector
Upload any photo and let AI identify every object in it. See bounding boxes, labels, and confidence scores drawn directly on your image. Everything runs locally in your browser.
Drop a photo here or click to upload
Supports JPG, PNG, WebP
Detected Objects
How AI Object Detection Works
This tool uses DETR (DEtection TRansformer), a state-of-the-art object detection model developed by Facebook Research. It combines a convolutional neural network backbone (ResNet-50) with a Transformer encoder-decoder to locate and classify objects in images. The model can detect 91 different object categories from the COCO dataset.
The model runs entirely in your browser using Transformers.js, which converts the PyTorch model into a format that runs on WebAssembly and WebGPU. The model is downloaded once (about 100 MB) and cached for offline use.
What Objects Can Be Detected
- People — Persons, faces in group photos, crowds
- Vehicles — Cars, trucks, buses, motorcycles, bicycles, airplanes, boats
- Animals — Dogs, cats, birds, horses, cows, sheep, elephants, bears
- Food — Bananas, apples, pizza, sandwiches, cakes, bottles
- Furniture — Chairs, couches, beds, dining tables, desks
- Electronics — TVs, laptops, cell phones, keyboards, remotes
Fun and Educational Uses
Object detection is one of the most visual and intuitive AI tasks. Try uploading photos from your camera roll and see what the AI finds. It is great for learning how computer vision works — you can see exactly where the model places bounding boxes and how confident it is about each detection.
Teachers can use this to demonstrate AI concepts in classrooms. Photographers can analyze scene composition. Developers can prototype vision features without writing backend code. Since everything runs locally, there is no API cost and no rate limit.
Tips for Better Detection
Use clear, well-lit photos where objects are reasonably sized. The model works best when objects are not heavily occluded. Outdoor scenes, room interiors, street scenes, and nature photos tend to produce the most interesting results with multiple detections.
How to Interpret Your Results
Review all sections of the analysis, not just the overall score. Focus on actionable items — findings you can actually change or improve. Run the check multiple times with different inputs if you want to compare scenarios. Keep in mind that automated analysis provides a useful starting point, but may not capture every nuance of your specific situation. Use the results as guidance for improvement rather than a definitive verdict.
Frequently Asked Questions
Is my photo uploaded to any server?
No. The object detection model runs entirely in your browser. Your photos never leave your device. Nothing is sent to any server.
What objects can the AI detect?
The DETR model can detect 91 categories from the COCO dataset including people, vehicles (cars, trucks, buses), animals (dogs, cats, birds), food items, furniture, electronics, sports equipment, and more.
Does it work offline?
Yes. After the first use, the AI model is cached in your browser. Subsequent uses work completely offline without an internet connection.
How accurate is the detection?
DETR achieves high accuracy on common objects. Results depend on image quality, object size, and occlusion. Objects that are clearly visible and well-lit produce the best results.
Why are some objects not detected?
The model uses a 50% confidence threshold. Objects that are partially hidden, very small, or unusual angles may score below this threshold. The model only detects the 91 COCO categories, so uncommon objects may not be recognized.
What browsers are supported?
This tool works in all modern browsers: Chrome, Firefox, Safari, and Edge. It uses WebAssembly which is supported everywhere.