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| # https://github.com/chrise96/image-to-coco-json-converter/tree/master | |
| from PIL import Image | |
| import numpy as np | |
| from skimage import measure | |
| import os | |
| import json | |
| def create_category_annotation(category_dict): | |
| """ | |
| Create category annotations in COCO JSON format. | |
| Args: | |
| category_dict (dict): Dictionary containing category names and IDs. | |
| Returns: | |
| list: List of category annotations. | |
| """ | |
| category_list = [] | |
| for key, value in category_dict.items(): | |
| category = { | |
| "supercategory": key, | |
| "id": value, | |
| "name": key | |
| } | |
| category_list.append(category) | |
| return category_list | |
| def get_coco_json_format(): | |
| """ | |
| Get the standard COCO JSON format. | |
| Returns: | |
| dict: COCO JSON format skeleton. | |
| """ | |
| # Standard COCO format | |
| coco_format = { | |
| "info": {}, | |
| "licenses": [], | |
| "images": [{}], | |
| "categories": [{}], | |
| "annotations": [{}] | |
| } | |
| return coco_format | |