Convert yolov5 dataset labels into COCO labels about globox HOT 3 CLOSED

You can read the YOLOv5 predictions with AnnotationSet.from_yolov5() and and then convert them to COCO using the .save_coco() method:

from globox import AnnotationSet

predictions = AnnotationSet.from_yolo_v5("path/to/annotations", image_folder="path/to/images")
predictions.save_coco(
  "coco_preds.json", 
  label_to_id={"person": 0}, 
  imageid_to_id={im: i for i, im in enumerate(sorted(predictions.image_ids))}
)

Conversion to COCO is a little bit tricky as you can see because COCO uses integer ids rather and image names and str class names. In any case you should adapt label_to_id and imageid_to_id to match the id mapping from the DETR dataset, I'm just suggesting an example.

Note that you can also read COCO annotations with AnnotationSet.from_coco(), which could simplify your workflow.

from globox.