Annotate image online with AI drawn labels, nothing to install
Annotate image online in a browser tab: upload a photo, let the AI model draw boxes, masks or points, fix them and export a labeled dataset. ImageLabeling runs entirely in the browser, so there is no desktop app to install, no local server to maintain and no GPU to set up for the people who label.
Annotate image online in the free demo
The quickest way to see how it works is the free demo on the homepage. Drop one image or pick a sample, choose a task and press Label my image.
The result opens in the real editor layout, with a list of detected objects, their classes and confidence scores. You can drag box corners and rename classes on the first objects right away. Uploaded demo images are deleted after 24 hours.
- Detect objects draws bounding boxes
- Segment draws masks
- Keypoints places pose points on people
- Classify assigns image level classes
Why annotate images online instead of installing a tool
Desktop labeling tools work for one person and one folder. As soon as a second labeler joins, someone has to copy files, merge label files and track who labeled what. A browser based tool keeps images, labels and review history in one workspace.
- Nothing to install on labeler laptops, any modern browser works
- New labelers get a link and a role, not a setup guide
- Images stay in the workspace, never scattered across personal drives
- Every label has a history of who drew it, who reviewed it and what changed
- Labelers in different cities work on the same project at the same time
An online image annotator that feels like a desktop app
The editor is keyboard first, so speed does not depend on a native app. B draws a box, P draws a polygon, K places a keypoint, A accepts an AI proposal and D saves and opens the next image. Zoom, a class picker, attributes per object and undo history are all in the same screen. Brush and polygon tools paint and refine segmentation masks on Team and above.
AI pre-labels before anyone clicks
For each uploaded image the AI model proposes labels for your schema with a confidence per object. Labelers accept the clear ones and correct the rest, which is how auto labeling cuts the clicks per image. The data annotation tools page explains each annotation type in detail.
Upload from anywhere
Drag and drop single images, upload a zip of a whole folder or import from a cloud bucket URL. JPG, PNG and WebP work in the demo. For video, extract frames and upload them as images; there is no native video timeline.
Export in standard formats
When the labels are reviewed, freeze a dataset version and export it as COCO JSON, YOLO txt with data.yaml, Pascal VOC XML or CSV. See the YOLO labeling tool and COCO annotation tool pages for file structure. Existing labels in the same formats can be imported for review.
Work as a team in the browser
Invite labelers, reviewers and viewers with project level access. Reviewers approve images or send them back with a comment, and everyone sees the same queue. Data is encrypted in transit and at rest, and your images are used only to label your dataset, never to train third party models. Plans start with 3 seats on Starter, 49 USD per month or 24 USD per month billed yearly. See the pricing page for every plan.
FAQ
Do I need to install anything?
No. ImageLabeling runs in any modern browser. Labelers sign in, open a project and start labeling.
Is there a free demo?
Yes. The free demo on the homepage labels one image with AI and shows the result in the real editor. Plans start at 24 USD per month billed yearly.
Can several people annotate the same project at once?
Yes. Every plan includes several seats: 3 on Starter, 10 on Team, 30 on Business and as many as you need on Enterprise.
What happens to images I upload to the demo?
Demo images are used only to produce your result and are deleted after 24 hours.
Label your first image in the browser
Upload one image and see AI drawn labels in the real editor.