mirror of https://github.com/open-mmlab/mmyolo.git
[Improvement] Improve browse coco json script args (#309)
* Improve browse coco json script * Improve doc * Improve script * Improve doc * Improve doc * Improve docpull/367/head
HinGwenWoong
GitHub
parent
1773439b83
commit
47bb3ce408
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@ -17,49 +17,60 @@ mim run mmdet print_config [CONFIG]
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`tools/analysis_tools/browse_coco_json.py` is a script that can visualization to display the COCO label in the picture.
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```shell
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python tools/analysis_tools/browse_coco_json.py ${DATA_ROOT} \
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[--ann_file ${ANN_FILE}] \
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[--img_dir ${IMG_DIR}] \
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python tools/analysis_tools/browse_coco_json.py [--data-root ${DATA_ROOT}] \
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[--img-dir ${IMG_DIR}] \
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[--ann-file ${ANN_FILE}] \
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[--wait-time ${WAIT_TIME}] \
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[--disp-all] [--category-names CATEGORY_NAMES [CATEGORY_NAMES ...]] \
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[--shuffle]
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```
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If images and labels are in the same folder, you can specify `--data-root` to the folder, and then `--img-dir` and `--ann-file` to specify the relative path of the folder. The code will be automatically spliced.
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If the image and label files are not in the same folder, you do not need to specify `--data-root`, but directly specify `--img-dir` and `--ann-file` of the absolute path.
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E.g:
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1. Visualize all categories of `COCO` and display all types of annotations such as `bbox` and `mask`:
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```shell
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python tools/analysis_tools/browse_coco_json.py './data/coco/' \
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--ann_file 'annotations/instances_train2017.json' \
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--img_dir 'train2017' \
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python tools/analysis_tools/browse_coco_json.py --data-root './data/coco' \
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--img-dir 'train2017' \
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--ann-file 'annotations/instances_train2017.json' \
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--disp-all
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```
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If images and labels are not in the same folder, you can use a absolutely path:
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```shell
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python tools/analysis_tools/browse_coco_json.py --img-dir '/dataset/image/coco/train2017' \
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--ann-file '/label/instances_train2017.json' \
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--disp-all
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```
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2. Visualize all categories of `COCO`, and display only the `bbox` type labels, and shuffle the image to show:
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```shell
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python tools/analysis_tools/browse_coco_json.py './data/coco/' \
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--ann_file 'annotations/instances_train2017.json' \
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--img_dir 'train2017' \
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python tools/analysis_tools/browse_coco_json.py --data-root './data/coco' \
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--img-dir 'train2017' \
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--ann-file 'annotations/instances_train2017.json' \
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--shuffle
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```
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3. Only visualize the `bicycle` and `person` categories of `COCO` and only the `bbox` type labels are displayed:
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```shell
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python tools/analysis_tools/browse_coco_json.py './data/coco/' \
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--ann_file 'annotations/instances_train2017.json' \
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--img_dir 'train2017' \
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python tools/analysis_tools/browse_coco_json.py --data-root './data/coco' \
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--img-dir 'train2017' \
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--ann-file 'annotations/instances_train2017.json' \
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--category-names 'bicycle' 'person'
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```
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4. Visualize all categories of `COCO`, and display all types of label such as `bbox`, `mask`, and shuffle the image to show:
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```shell
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python tools/analysis_tools/browse_coco_json.py './data/coco/' \
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--ann_file 'annotations/instances_train2017.json' \
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--img_dir 'train2017' \
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python tools/analysis_tools/browse_coco_json.py --data-root './data/coco' \
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--img-dir 'train2017' \
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--ann-file 'annotations/instances_train2017.json' \
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--disp-all \
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--shuffle
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```
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@ -17,49 +17,60 @@ mim run mmdet print_config [CONFIG]
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脚本 `tools/analysis_tools/browse_coco_json.py` 能够使用可视化显示 COCO 标签在图片的情况。
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```shell
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python tools/analysis_tools/browse_coco_json.py ${DATA_ROOT} \
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[--ann_file ${ANN_FILE}] \
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[--img_dir ${IMG_DIR}] \
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python tools/analysis_tools/browse_coco_json.py [--data-root ${DATA_ROOT}] \
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[--img-dir ${IMG_DIR}] \
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[--ann-file ${ANN_FILE}] \
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[--wait-time ${WAIT_TIME}] \
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[--disp-all] [--category-names CATEGORY_NAMES [CATEGORY_NAMES ...]] \
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[--shuffle]
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```
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其中，如果图片、标签都在同一个文件夹下的话，可以指定 `--data-root` 到该文件夹，然后 `--img-dir` 和 `--ann-file` 指定该文件夹的相对路径，代码会自动拼接。
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如果图片、标签文件不在同一个文件夹下的话，则无需指定 `--data-root` ，直接指定绝对路径的 `--img-dir` 和 `--ann-file` 即可。
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例子：
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1. 查看 `COCO` 全部类别，同时展示 `bbox`、`mask` 等所有类型的标注：
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```shell
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python tools/analysis_tools/browse_coco_json.py './data/coco/' \
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--ann_file 'annotations/instances_train2017.json' \
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--img_dir 'train2017' \
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python tools/analysis_tools/browse_coco_json.py --data-root './data/coco' \
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--img-dir 'train2017' \
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--ann-file 'annotations/instances_train2017.json' \
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--disp-all
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```
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如果图片、标签不在同一个文件夹下的话，可以使用绝对路径：
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```shell
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python tools/analysis_tools/browse_coco_json.py --img-dir '/dataset/image/coco/train2017' \
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--ann-file '/label/instances_train2017.json' \
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--disp-all
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```
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2. 查看 `COCO` 全部类别，同时仅展示 `bbox` 类型的标注，并打乱显示：
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```shell
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python tools/analysis_tools/browse_coco_json.py './data/coco/' \
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--ann_file 'annotations/instances_train2017.json' \
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--img_dir 'train2017' \
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python tools/analysis_tools/browse_coco_json.py --data-root './data/coco' \
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--img-dir 'train2017' \
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--ann-file 'annotations/instances_train2017.json' \
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--shuffle
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```
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3. 只查看 `bicycle` 和 `person` 类别，同时仅展示 `bbox` 类型的标注：
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```shell
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python tools/analysis_tools/browse_coco_json.py './data/coco/' \
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--ann_file 'annotations/instances_train2017.json' \
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--img_dir 'train2017' \
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python tools/analysis_tools/browse_coco_json.py --data-root './data/coco' \
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--img-dir 'train2017' \
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--ann-file 'annotations/instances_train2017.json' \
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--category-names 'bicycle' 'person'
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```
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4. 查看 `COCO` 全部类别，同时展示 `bbox`、`mask` 等所有类型的标注，并打乱显示：
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```shell
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python tools/analysis_tools/browse_coco_json.py './data/coco/' \
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--ann_file 'annotations/instances_train2017.json' \
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--img_dir 'train2017' \
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python tools/analysis_tools/browse_coco_json.py --data-root './data/coco' \
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--img-dir 'train2017' \
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--ann-file 'annotations/instances_train2017.json' \
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--disp-all \
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--shuffle
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```
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@ -10,7 +10,10 @@ from pycocotools.coco import COCO
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def show_coco_json(args):
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coco = COCO(osp.join(args.data_root, args.ann_file))
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if args.data_root is not None:
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coco = COCO(osp.join(args.data_root, args.ann_file))
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else:
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coco = COCO(args.ann_file)
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print(f'Total number of images：{len(coco.getImgIds())}')
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categories = coco.loadCats(coco.getCatIds())
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category_names = [category['name'] for category in categories]
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@ -30,8 +33,11 @@ def show_coco_json(args):
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for i in range(len(image_ids)):
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image_data = coco.loadImgs(image_ids[i])[0]
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image_path = osp.join(args.data_root, args.img_dir,
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image_data['file_name'])
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if args.data_root is not None:
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image_path = osp.join(args.data_root, args.img_dir,
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image_data['file_name'])
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else:
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image_path = osp.join(args.img_dir, image_data['file_name'])
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annotation_ids = coco.getAnnIds(
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imgIds=image_data['id'], catIds=category_ids, iscrowd=0)
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@ -103,14 +109,13 @@ def show_bbox_only(coco, anns, show_label_bbox=True, is_filling=True):
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def parse_args():
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parser = argparse.ArgumentParser(description='Show coco json file')
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parser.add_argument('--data-root', default=None, help='dataset root')
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parser.add_argument(
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'data_root', default='data/coco/', help='data root path')
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'--img-dir', default='data/coco/train2017', help='image folder path')
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parser.add_argument(
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'--ann_file',
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default='annotations/instances_train2017.json',
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'--ann-file',
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default='data/coco/annotations/instances_train2017.json',
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help='ann file path')
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parser.add_argument(
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'--img_dir', default='train2017', help='image folder path')
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parser.add_argument(
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'--wait-time', type=float, default=2, help='the interval of show (s)')
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parser.add_argument(
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@ -133,6 +138,10 @@ def parse_args():
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return args
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if __name__ == '__main__':
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def main():
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args = parse_args()
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show_coco_json(args)
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if __name__ == '__main__':
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main()
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