mscoco数据解析--polygen2bbx生成矩形框

mscoco数据解析–polygen2bbx生成矩形框

我们使用paddleseg获取目标的轮廓信息，辅助标注bbox，可以提升标注效率和精度。
coco数据格式如下：

• https://zhuanlan.zhihu.com/p/362049720
• https://tangh.github.io/articles/coco-and-cityscapes-datasets/

annotation.json的格式如下
{ “info”: […] “licenses”: […] “images”: […] “annotations”: [ ] }

解析polygen，提取有用的bbx信息

import os
import shutil
import json
import tqdm
def get_all_files(fold,suffix='.jpg'):
    all_files = []
    for root, dirs, files in os.walk(fold):
        for file in files:
            if suffix in file:
                all_files.append(os.path.join(root, file))
    return all_files
def gen_txt(file,bbx):
    with open(file, 'w') as f:
        f.write('{} {} {} {}'.format(bbx[0],bbx[1],bbx[2],bbx[3],))

def gen_bbx(file):
    with open(file, 'r') as fcc_file:
        fcc_data = json.load(fcc_file)
    images_name=fcc_data['images']
    annotations=fcc_data['annotations']
    for  image_info in tqdm.tqdm(images_name):
        file_name=image_info['file_name']
        img_id=image_info['id']
        for ann in annotations:
            if ann['image_id']==img_id:
                gen_txt(os.path.join(out,file_name.replace('.JPG','.txt')),ann['bbox'])

        
file=r'F:\DATA_SET\B2C拍照\1001-\part1\label\annotations.json'
out=r'F:\DATA_SET\B2C拍照\1001-\part1\label\txt'
if not os.path.exists(out):
    os.mkdir(out)
gen_bbx(file)