Converting COCO annotation (CVAT) to annotation for YOLO-seg (instance segmentation) and YOLO-obb (oriented bounding box detection)

Convert LabelMe Annotation Tool JSON format to YOLO text file format

A CLI tool can create a specific task-dataset you want based on COCO dataset. Given the annotation JSON file, this tool will help you download the data and set the symbolic links from data_dir to task_dir !!

This developed algorithm transforms mask labels used in previous segmentation tasks into a format compatible with YOLO's label requirements. As a result, pre-prepared datasets can be used with YOLO-like detection-focused architectures.

My own version to annotate dataset for YOLO format (Including multi-class labeling on the same image)

Augmentation yolo format txt and images

Dataset prep tool for object detection tasks

COCO dataset to Yolo format annotations and images downloader, also Negatives categories can be downloaded too.

📦 HBB2OBB is a Python library for converting horizontal (axis-aligned) bounding boxes to oriented (rotated) bounding boxes using SAM-based segmentation. Includes tools for visualization, evaluation, format conversion, and hyperparameter tuning.

Create a YOLO-format subset of the COCO dataset

Some useful and common scripts for future use

Object Detection Tools to convert between dataset formats, image splitting and stitching.