3.数据处理-把labelme标注的关键点转成coco格式.pdf

3.数据处理-把labelme标注的关键点转成coco格式 # *_ * : coding : utf-8 *_ * ##################### #cao datasets process for object detection project. for convert customer dataset format to coco data format, import traceback import argparse import datetime import json import cv2 import os __CLA __ = [__ background__, lpr] # class dictionary, background must be in first index. def argparser() : parser = argparse.ArgumentParser(define argument parser for pycococreator!) #图⽚和标签的路径 parser.add_argument(-r, --project_ path, default=/mnt//, help=path of root directory) parser.add_argument(-l, --label_ path, default=/mn/labels, help=path of root directory) #图⽚所在的⽂件夹，可以⽀持 个⽂件夹 parser.add_argument(-p, --phase_folder, default=[ceme], help=datasets path of [train, val, test]) #关键点个数 parser.add_argument(-joint, --pointNum, default=33,help=point numbers) # 是否开启关键点读取， parser.add_argument(-po, --have_ points, default=True, help=if have points we will deal it !) # 是否开启把点画在图⽚上验证读取， parser.add_argument(-check, --have_check, default=True, help=if you want to check all points !) return parser.parse_args() def MainProcessing(args) : main process source code. annotations = {} # annotations dictionary, which will dump to son format file. project_ path = ject_ path phase_folder = args.phase_folder # coco annotations info. annotations[info] = { description: customer dataset format convert to COCO format, url: , version: 1.0, year: 2020, contributor: andy.wei, date_created: 2020/08/24 } # coco annotations licenses. annotations[licenses] = [{ url: /licenses/ LICEN E-2.0.html, id: 1, name: Apache License 2.0 }] # coco annotations categories. annotations[categories] = [] for cls, clsname in en