def coco_to_yolo(config):
    import os
    import json
    from pathlib import Path
    from tqdm import tqdm

    
    labels_dir = config["root_labels"]
    annotations_dir = config["root_annotations"]

    def convert_coco_json_to_yolo(coco_json_path, output_dir):
        with open(coco_json_path) as f:
            data = json.load(f)

        images = {img['id']: img for img in data['images']}
        categories = {cat['id']: cat['name'] for cat in data['categories']}
        category_id_map = {cat_id: i for i, cat_id in enumerate(sorted(categories.keys()))}

        os.makedirs(output_dir, exist_ok=True)
        print(len(images))
        for ann in tqdm(data['annotations']):
            img = images[ann['image_id']]
            image_name = Path(img['file_name']).stem
            img_width = img['width']
            img_height = img['height']
            bbox = ann['bbox']  # [x_min, y_min, width, height]
            x_center = (bbox[0] + bbox[2] / 2) / img_width
            y_center = (bbox[1] + bbox[3] / 2) / img_height
            w = bbox[2] / img_width
            h = bbox[3] / img_height

            class_id = category_id_map[ann['category_id']]

            label_path = os.path.join(output_dir, f"{image_name}.txt")
            with open(label_path, "a") as f:
                f.write(f"{class_id} {x_center:.6f} {y_center:.6f} {w:.6f} {h:.6f}\n")

        print(f"Converted labels saved to: {output_dir}")

    # Example usage
    convert_coco_json_to_yolo(
        coco_json_path=annotations_dir+"instances_train.json",
        output_dir=labels_dir+"train/"
    )
    convert_coco_json_to_yolo(
        coco_json_path=annotations_dir+"instances_val.json",
        output_dir=labels_dir+"val/"
    )
    convert_coco_json_to_yolo(
        coco_json_path=annotations_dir+"instances_test.json",
        output_dir=labels_dir+"test/"
    )