Labelme Python Packages

globox

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

dataflow-cv

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

labelme2coco

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

cv-suite

Computer vision CLI for dataset work: convert annotations, auto-label, caption, classify, OCR, generate images and clean datasets.

pascal-voc

Python utility to work with PascalVoc annotation 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.

labelmev2

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.

image-dataset-converter-labelme

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

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

Tool for working with images annotations. Allows you to convert, modify and analyze annotations to images of such formats as Yolo, COCO, LabelMe, etc.