Draw bounding boxes, polygons, and freehand masks directly in your browser. Prepare clean datasets for YOLO, Mask R-CNN, and similar workflows without uploading source images to the cloud.
Cloud Uploads
Images stay local on your device
Export Formats
JSON, XML, and CSV included
Bulk Uploads
Drop entire image folders at once
Free Forever
No account or subscription required
Annotate covers the full labeling loop in one browser workspace: load folders, draw precise annotations, and export clean files ready for training.
Load entire folders of images at once, then move through them one by one using keyboard shortcuts. Less time managing files, more time actually labeling.
Handle simple and complex objects with rectangles, polygons, and fine-grain mask controls without leaving the browser.
Export annotations as JSON, XML, or CSV and plug the files into PyTorch, TensorFlow, YOLO, or your own training pipeline.
Work is saved in local browser storage so you can recover quickly, undo edits, and continue where you left off.
Ready to start your first labeling project?
Start a ProjectAnnotation Tool
Label and segment your training images directly in the browser. Compare the source image and labeled result below.
Open the app, load your images, and start labeling immediately. Everything runs locally in your browser with no account required.
Start Labeling
Drop in one folder and move through images in sequence with a steady, keyboard-friendly workflow. The process stays simple even on large datasets.
Use rectangles for fast object marks, polygons for irregular edges, and brush tools for detailed masks. Pick the tool that fits each frame and keep moving.
Images stay on your device while you work. Annotate runs in the browser, which makes it a practical fit for private or sensitive datasets.
[{
"content": [
{ "x": 1368.42, "y": 1236.29 },
{ "x": 3036.72, "y": 1236.29 },
{ "x": 3036.72, "y": 2394.45 },
{ "x": 1368.42, "y": 2394.45 }
],
"rectMask": {
"xMin": 1368.42,
"yMin": 1236.29,
"width": 1668.30,
"height": 1158.16
},
"labels": {
"labelName": "meat",
"labelColor": "#ff0000",
"labelColorRGB": "255,0,0",
"visibility": true
}
}]Exports are structured for common training workflows, so you can move from labeling to model training with less cleanup.
If your team works with image datasets regularly, Annotate helps you move faster without adding process overhead.
Build datasets quickly for experiments, baselines, and model iteration without stopping to set up extra tooling.
Keep class definitions consistent across contributors and move through large folders in a predictable workflow.
Prepare and review training samples in the browser while keeping source data on local machines.
Ship labeled data without paying for heavyweight platforms before your pipeline and taxonomy are final.
Run quick correction cycles with local history and undo, then export updated labels for retraining.
Teach annotation fundamentals with a straightforward tool that students can open and use immediately.
Common questions about how Annotate works, what it supports, and how to get started.
Open AnnotateNo account, no installation, and no setup overhead. Open the tool in your browser and begin labeling right away.