labelme and labelImg
The first tool is an active image annotation project with various shapes and AI assistance, while the second is an inactive, popular image annotation tool whose development has been superseded by a related, more comprehensive open-source data labeling platform (Label Studio).
About labelme
wkentaro/labelme
Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted annotation.
This tool helps data annotators efficiently label objects and regions within images or video frames for machine learning tasks. You input raw images or video, and it outputs detailed annotations saved as JSON files, outlining specific shapes like polygons, rectangles, circles, lines, or points. It's designed for anyone preparing visual datasets for training computer vision models.
About labelImg
HumanSignal/labelImg
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
Built with PyQt for its graphical interface, LabelImg outputs bounding box annotations in multiple formats—PASCAL VOC (ImageNet standard), YOLO, and CreateML—enabling compatibility with diverse computer vision pipelines. The tool supports batch processing via directory loading, predefined class lists, and annotation visualization by loading existing label files alongside images, streamlining workflows for dataset preparation.
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