主要是查到的可用代码，便于自己使用查询，和有相关需求的提供参考。
代码是MMYOLO下的可视化代码browse_coco_json.py，有json文件和图像文件，可以直接输入执行，输出会把bbox、mask等类型标注展示。
下面直接上代码：
import argparse
import os.path as ospimport cv2
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.collections import PatchCollection
from matplotlib.patches import Polygon
from pycocotools.coco import COCOdef show_coco_json(args):if args.data_root is not None:coco = COCO(osp.join(args.data_root, args.ann_file))else:coco = COCO(args.ann_file)print(f'Total number of images：{len(coco.getImgIds())}')categories = coco.loadCats(coco.getCatIds())category_names = [category['name'] for category in categories]print(f'Total number of Categories : {len(category_names)}')print('Categories: \n{}\n'.format(' '.join(category_names)))if args.category_names is None:category_ids = []else:assert set(category_names) > set(args.category_names)category_ids = coco.getCatIds(args.category_names)image_ids = coco.getImgIds(catIds=category_ids)if args.shuffle:np.random.shuffle(image_ids)for i in range(len(image_ids)):image_data = coco.loadImgs(image_ids[i])[0]if args.data_root is not None:image_path = osp.join(args.data_root, args.img_dir,image_data['file_name'])else:image_path = osp.join(args.img_dir, image_data['file_name'])annotation_ids = coco.getAnnIds(imgIds=image_data['id'], catIds=category_ids, iscrowd=0)annotations = coco.loadAnns(annotation_ids)image = cv2.imread(image_path)image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)plt.figure()plt.imshow(image)if args.disp_all:coco.showAnns(annotations)else:show_bbox_only(coco, annotations)if args.wait_time == 0:plt.show()else:plt.show(block=False)plt.pause(args.wait_time)plt.close()def show_bbox_only(coco, anns, show_label_bbox=True, is_filling=True):"""Show bounding box of annotations Only."""if len(anns) == 0:returnax = plt.gca()ax.set_autoscale_on(False)image2color = dict()for cat in coco.getCatIds():image2color[cat] = (np.random.random((1, 3)) * 0.7 + 0.3).tolist()[0]polygons = []colors = []for ann in anns:color = image2color[ann['category_id']]bbox_x, bbox_y, bbox_w, bbox_h = ann['bbox']poly = [[bbox_x, bbox_y], [bbox_x, bbox_y + bbox_h],[bbox_x + bbox_w, bbox_y + bbox_h], [bbox_x + bbox_w, bbox_y]]polygons.append(Polygon(np.array(poly).reshape((4, 2))))colors.append(color)if show_label_bbox:label_bbox = dict(facecolor=color)else:label_bbox = Noneax.text(bbox_x,bbox_y,'%s' % (coco.loadCats(ann['category_id'])[0]['name']),color='white',bbox=label_bbox)if is_filling:p = PatchCollection(polygons, facecolor=colors, linewidths=0, alpha=0.4)ax.add_collection(p)p = PatchCollection(polygons, facecolor='none', edgecolors=colors, linewidths=2)ax.add_collection(p)def parse_args():parser = argparse.ArgumentParser(description='Show coco json file')parser.add_argument('--data-root', default=None, help='dataset root')parser.add_argument('--img-dir', default='data/coco/train2017', help='image folder path')parser.add_argument('--ann-file',default='data/coco/annotations/instances_train2017.json',help='ann file path')parser.add_argument('--wait-time', type=float, default=2, help='the interval of show (s)')parser.add_argument('--disp-all',action='store_true',help='Whether to display all types of data, ''such as bbox and mask.'' Default is to display only bbox')parser.add_argument('--category-names',type=str,default=None,nargs='+',help='Display category-specific data, e.g., "bicycle", "person"')parser.add_argument('--shuffle',action='store_true',help='Whether to display in disorder')args = parser.parse_args()return argsdef main():args = parse_args()show_coco_json(args)if __name__ == '__main__':main()
用法：
–img-dir 图片文件夹
–ann-file coco标签文件，
–disp-all 显示所所有类别标签
python browse_coco_json.py --img-dir '/dataset/image/coco/train2017' \--ann-file '/label/instances_train2017.json' \--disp-all
查看 COCO 全部类别，同时仅展示 bbox 类型的标注，并打乱显示：
python browse_coco_json.py --data-root './data/coco' \--img-dir 'train2017' \--ann-file 'annotations/instances_train2017.json' \--shuffle
只查看 bicycle 和 person 类别，同时仅展示 bbox 类型的标注：
python browse_coco_json.py --data-root './data/coco' \--img-dir 'train2017' \--ann-file 'annotations/instances_train2017.json' \--category-names 'bicycle' 'person'
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：
python browse_coco_json.py --data-root './data/coco' \--img-dir 'train2017' \--ann-file 'annotations/instances_train2017.json' \--disp-all \--shuffle
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