1 utility for transforming object detection annotations from JSON format into the YOLO-compatible text format. The tool processes bounding box data and class indices to ensure compatibility with YOLOv5, YOLOv8, and other Darknet-based models.
Use Cases
- Transform COCO-formatted JSON files into YOLO training labels using the class and bbox fields.
- Prepare custom datasets for object detection by converting absolute pixel coordinates into normalized center-based coordinates.
- Standardize diverse JSON annotation outputs into a uniform format for YOLO-based model benchmarking.
Strengths
- Converts structured JSON metadata into individual .txt files per image.
- Normalizes bounding box coordinates to the [0, 1] range required by YOLO.
- Maps class labels from JSON keys to integer indices for model training.