Dataset Format Conversions: Scripts for COCO, YOLO, VOC, and XML

This repository provides scripts for converting computer vision annotation formats between COCO, YOLO, VOC, and XML standards. Developed by MrAsimZahid and last updated in June 2022, it serves as a utility for deep learning dataset preparation.

Use Cases

• Converting COCO JSON annotations to YOLO TXT format for training Darknet models
• Transforming Pascal VOC XML files into COCO format for use with Detectron2
• Standardizing custom XML annotation outputs into formats compatible with ImageNet-style pipelines

Strengths

• Supports 4 major computer vision annotation formats: COCO, YOLO, VOC, and XML
• Provides bidirectional conversion logic for deep learning dataset preparation

Limitations

• Contains code scripts rather than a static dataset of images or labels
• Lacks documentation on specific library dependencies or Python version requirements
• No sample annotation files included to verify conversion accuracy

Provenance

Source

GitHub repository by MrAsimZahid

Freshness

Last updated June 2022; no ongoing maintenance indicated.