Features, guides, and ideas from the LabelMe team.
Two suppression passes in LabelMe v6.3 stop AI-Box, AI-Points, and AI-Text from stacking redundant predictions on the same object, whether they came from nested SAM granularities or from regions you've already labeled.
Read articlePick the output shape for AI-Points and AI-Box: polygon, mask, rectangle, oriented rectangle, or circle. Fitted to the SAM mask, no post-export conversion.
Select many annotations at once and apply the same edit to all of them. Ctrl/Cmd+A grabs every shape on the image, range-select works in the label list, and hide/show propagates across the whole selection as one undoable step.
A new shape type in LabelMe v6.2. Three clicks to draw, corner drag to resize, edge midpoint to rotate, with an arrow on the canvas so the heading is never ambiguous.
A podcast with Robin Cole on annotating satellite imagery in LabelMe, plus an end-to-end NAIP to QGIS demo.
The first AI click of a fresh install used to freeze the app for minutes while the model downloaded in silence. v6.1 shows a progress bar with bytes, ETA, and a cancel button.
LabelMe v6.1 collapses four near-identical AI buttons into AI-Points and AI-Box, each with a polygon-or-mask output toggle. A separator between manual and AI tools makes the right button easier to find when you haven't opened the app in a week.
Drag a single bounding box around a cluster and SAM3 returns one shape per instance inside it. Built for parking lots, shelves, microscopy, and anything else where every visible object is the same kind of thing.
LabelMe v6 stops base64-embedding the image inside every annotation JSON by default. Files get an order of magnitude smaller, diffs become readable, and version control stops choking on the binary blob.
LabelMe v6 saves annotations as you work. The most common way to lose hours of labeling — forgetting to Ctrl+S before closing — is gone for new installs.
LabelMe v6 opens multi-gigapixel images and float32 GeoTIFFs that v5 refused to load. Pan, zoom, and annotate a 26,000 x 22,000 px aerial tile without the app locking up.
Annotate a custom dataset with LabelMe, export to YOLO format with labelmetk, and train with Ultralytics. All offline.
AI tools can propose annotations automatically. Here's how to review them fast with LabelMe: fix what's wrong, skip what's right.
Cloud annotation tools upload your images to their servers. For medical AI teams, that's a HIPAA problem. LabelMe runs entirely offline, so your images never leave your machine.
Cloud annotation tools send your training data to third-party servers. Here's why that's a growing problem, and how offline-first tools like LabelMe solve it.