根据自己的数据制作 coco annotations 类似的json文件

自己的数据标签为txt文件，格式如下：

Scene/Video/video0067/image_2860.png 7 1 368 342 100 91 1 468 355 64 72 1 700 216 43 46 1 712 149 35 38 1 771 115 28 32 1 790 140 21 20 1 643 65 11 13

图片路径 该图中框数(根据框数，后面的数5个一组，依次为：标志位 左上角x点 左上角y点 框宽 框高)

txt to coco annotations json代码如下：

# -*- coding: UTF-8 -*-
import cv2
import json
import sys

# process bar
def process_bar(count, total, status=''):
    bar_len = 60
    filled_len = int(round(bar_len * count / float(total)))

    percents = round(100.0 * count / float(total), 1)
    bar = '=' * filled_len + '-' * (bar_len - filled_len)

    sys.stdout.write('[%s] %s%s ...%s\r' % (bar, percents, '%', status))
    sys.stdout.flush()

root_path = "data_with_box_example/"
images, categories, annotations = [], [], []

category_dict = {"people": 1}

for cat_n in category_dict:
    categories.append({"supercategory": "", "id": category_dict[cat_n], "name": cat_n})

with open("label_example.txt", 'r') as f:
    img_id = 0
    anno_id_count = 0
    count = 1
    total = 100
    for line in f.readlines():
        process_bar(count, total)
        count += 1
        line = line.split(' ')
        img_name = line[0].replace('/', '_')
        bbox_num = int(line[1])
        img_cv2 = cv2.imread(root_path + img_name)
        [height, width, _] = img_cv2.shape

        # images info
        images.append({"file_name": img_name, "height": height, "width": width, "id": img_id})

        """
        annotation info:
        id : anno_id_count
        category_id : category_id
        bbox : bbox
        segmentation : [segment]
        area : area
        iscrowd : 0
        image_id : image_id
        """
        category_id = category_dict["people"]
        for i in range(0, bbox_num):
            x1 = float(line[i * 5 + 3])
            y1 = float(line[i * 5 + 4])
            x2 = float(line[i * 5 + 3]) + float(line[i * 5 + 5])
            y2 = float(line[i * 5 + 4]) + float(line[i * 5 + 6])
            width = float(line[i * 5 + 5])
            height = float(line[i * 5 + 6])

            bbox = [x1, y1, width, height]
            segment = [x1, y1, x2, y1, x2, y2, x1, y2]
            area = width * height

            anno_info = {'id': anno_id_count, 'category_id': category_id, 'bbox': bbox, 'segmentation': [segment],
                         'area': area, 'iscrowd': 0, 'image_id': img_id}
            annotations.append(anno_info)
            anno_id_count += 1

        img_id = img_id + 1

all_json = {"images": images, "annotations": annotations, "categories": categories}

with open("example.json", "w") as outfile:
    json.dump(all_json, outfile)