用于 COCO、LabelMe、Labelbox、VoTT、INFOLKS 和 ATH 标注的旧版 JSON 转 YOLO 数据集转换器。已被 Ultralytics 包中的 convert_coco() 取代。

dataset-conversion 开源项目推荐(10 个)
dataset-conversion 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 全部 10
GitHub 共 10 个仓库,已全部展示机器人数据工具包 |在机器人数据集格式(RLDS、LeRobot v2/v3、Zarr、HDF5、Rosbag)之间转换。检查、可视化和分析数据集。可配合HuggingFace Hub使用。专为OpenVLA、Octo、LeRobot和扩散策略工作流打造。
A Framework for DDoS Attack Detection Using Hyperparameter Optimization, WGAN-GP–Based Data Augmentation, Feature Extraction via Genetic Algorithms, RFE, and PCA, with Individual and Ensemble Classifiers for Multi-Dataset Evaluation.
该工具旨在简化将分段标签数据转换为YOLO(你只需看一次)分段格式的过程。
A comprehensive toolkit for converting image classification datasets into object detection datasets and training them using YOLOv8. This project streamlines the process of dataset preparation, augmentation, and training, making it easier to leverage YOLOv8 for custom object detection tasks.
A bilingual LeRobot dataset workbench for visualization, annotation, conversion and quality review.
A fast, validated YOLO‑to‑COCO dataset converter with auto‑discovery, strict Pydantic validation, and optional visualization for debugging annotations.
Single YOLO11 detector recognising 20 traffic sign classes and 13 traffic light states, trained on a unified dataset merged from two independent public datasets.
Comprehensive ML dataset transformation toolkit supporting 15+ formats (SQuAD, CoQA, MS MARCO, Natural Questions) with 3-script pipeline architecture, intelligent conversion algorithms, and batch processing capabilities for large-scale dataset workflows.
YOLO11 based object detection and tracking for autonomous driving, with an option to combine detections with lane perception.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 10 个项目;原始页面见 https://github.com/topics/dataset-conversion。
- 该话题在 GitHub 上共有 10 个仓库, 本站收录的是其中最热门的 10 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 10 个项目累计 1433 Star,覆盖 2 种主要语言,数据更新于 2026-11-12。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。