AI Image Tagger: Detect Objects in Photos Free

Drop an image here

or paste (Ctrl/Cmd+V) · PNG, JPG, WEBP · stays on your device

Loading the AI model…

Private by design

The AI runs inside this browser tab. Your image is never sent to any server. Check your network tab: zero uploads.

Real object detection

A transformer model (YOLOS) locates and labels common objects and draws a box around each, entirely on your device.

Free, always

Free forever, with no sign-up and no usage limit.

Part of BeginStudio. Powered by Transformers.js (Apache-2.0) and the YOLOS model (Apache-2.0). Detects 80 common object types.

Frequently asked questions

Is it free?

Yes. It is free with no signup, no watermark and no usage limit.

Is my data uploaded?

No. The AI model runs inside your browser, so your photo never leaves your device.

Why is the first run slow?

The first time, your browser downloads the AI model from a public model host (Hugging Face via jsDelivr). After that it is cached and starts much faster.

Does it work on phones?

Yes, in a modern mobile browser, though large inputs run slower than on a laptop.

About the AI Image Tagger

The image tagger looks at a photo and labels the everyday objects it recognises, such as people, cars, bottles, laptops, chairs and dogs. Each label comes with a box drawn around the object and a confidence score. It uses a compact object-detection model that runs in your browser, so the photo is not uploaded.

What people use it for

Alt text and captions. The tags are a quick checklist of what is in an image when writing alt text for a website or blog. Write the final description yourself; tags list objects but not the meaning of the scene.
Sorting product or stock photos. Run a few images to see which contain people, which show a laptop or phone, and file them accordingly.
Checking a photo before posting. A quick scan can show a stray object in the background you had not noticed.
Learning how computer vision works. Students can see bounding boxes and confidence scores in a real model without installing anything.

Reading the results

A high score, say above 80%, means the model is fairly sure. Low scores on small or partly hidden objects are often wrong. The model knows a fixed list of common object types, so it will not name specific brands, people, Indian dishes or local items. It may call a rickshaw a "car" or "motorcycle", for example.

Example

A photo of a home office might return "laptop 96%", "cup 88%", "chair 74%" and "potted plant 61%". From that you could write alt text such as "A laptop and coffee cup on a wooden desk beside a plant".

Tag anything in a photo. In your browser.