Labelme Python Packages

dataflow-cv

🌊 Everything your model doesn't do. Convert, visualize, evaluate, and more — a single CLI for all CV data.

globox

A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.

labelme2coco

A lightweight package for converting your labelme annotations into COCO object detection format.

labelme2yolov7segmentation

Conver labelme annotation format to yolov7 annotation format for segmentation.

labelme2datasets

python scripts to convert labelme-generated-jsons to voc/coco style datasets.

labelme-to-yolo

Python library to convert LabelMe JSON annotations into YOLO (YOLOv5/YOLOv7) format, including automatic dataset splitting and structure generation for computer vision workflows.

image-dataset-converter-labelme

image-dataset-converter plugins for the labelme annotation tool (https://github.com/wkentaro/labelme).

labelmev2

Image Polygonal Annotation with Python - V2 with 45x Faster Performance

pascal-voc

Python utility to work with PascalVoc annotation format

annotation-parser

AnnotationParser is a universal Python library that parses annotation files from different formats (LabelMe, COCO, VOC, etc.) into a single unified Shape data structure. This allows you to work with annotations using a consistent interface, regardless of the original format.

rubetools

Rubetek dataset tools.

labelme-enhanced

Image annotation tool with 45x faster loading, enhanced zoom (5000%), multiple point addition, polygon merge, and dark mode. Enhanced fork of wkentaro/labelme optimized for large image annotation workflows.