python scripts to convert labelme-generated-jsons to voc/coco style datasets.
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Updated
May 13, 2024 - Python
python scripts to convert labelme-generated-jsons to voc/coco style datasets.
A lightweight package for converting your labelme annotations into COCO object detection format.
A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.
This is a course project for DSCI-6011 - Deep Learning. deals with Drivable Area and lane segmentation for self driving cars
Help converting LabelMe Annotation Tool JSON format to YOLO text file format. If you've already marked your segmentation dataset by LabelMe, it's easy to use this tool to help converting to YOLO format dataset.
Modified for annotation of object detection.
Python scripts for converting json annotations from Anylabeling/LabelMe to YOLO txt files.
Python utility to work with PascalVoc annotation format
A framework for training segmentation models in pytorch on labelme annotations with pretrained examples of skin, cat, and pizza topping segmentation
Conver labelme annotation format to yolov7 annotation format for segmentation.
Convert labelme format to yolo segmentation format
Object detection toolbox for parsing, converting and evaluating bounding box annotations.
tool for data labeling, conversion and augmentation
Tool for working with images annotations. Allows you to convert, modify and analyze annotations to images of such formats as Yolo, COCO, LabelMe, etc.
Convert from YOLO detected polygons to LabelMe json format
Real time emotion recognition from facial expression through live captured video
セマンティックセグメンテーションを実装するためのデモ
Logo Dataset (FlickrLogos, labelme) Handling for YOLOv5
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