labelme转YOLO格式脚本

啥都不多说，直接上代码，多线程操作，转换很快。我的labelme是自己改过的，如果报 label_file.imageWidth错误，请自己读一下图片的宽高。用法：直接改一下dirpath,dstpath路径即可,dirpath里面可以有子文件夹，最后dstpath里面的标定内容是从0开始顺序编号的文件。

import os
import io
from io import BytesIO
import uuid
import PIL.Image
import codecs
import threadpool
import numpy as np
import cv2
import base64
from math import radians,fabs,sin,cos
from labelme.label_file import *
from labelme import utils
import shutil

dirpath = r'xxxxx'
dst_path_dir = r'xxxxx'


files = [os.path.join(y, file) for y, z, x in os.walk(dirpath)
         for file in x if os.path.splitext(file)[1] == '.json']

if not os.path.exists(dst_path_dir):
    os.makedirs(dst_path_dir)

index_files = []
for i in range(len(files)):
    index_files.append([i, files[i]])

def ThreadFun_c1(file):
    index = file[0]
    file = file[1]
    print(file)
    txtname = os.path.join(dst_path_dir, '{}.txt'.format(index))
    label_file = LabelFile()
    label_file.load(file)
    shutil.copy(file.replace('.json','.jpg'), txtname.replace('.txt','.jpg'))
    with codecs.open(txtname,'w','GBK') as f:
        for shape in label_file.shapes:
            x1 = shape['points'][0][0]/label_file.imageWidth
            y1 = shape['points'][0][1]/label_file.imageHeight
            x2 = shape['points'][1][0]/label_file.imageWidth
            y2 = shape['points'][1][1]/label_file.imageHeight
            f.write('{} {} {} {} {}\n'.format(shape['label'],(x1+x2)/2,(y1+y2)/2,abs(x1-x2),abs(y1-y2)))


# 定义了一个线程池，最多创建8个线程
pool = threadpool.ThreadPool(16)
# 创建要开启多线程的函数，以及函数相关参数和回调函数，其中回调数可以不写，default是none
requests = threadpool.makeRequests(ThreadFun_c1, index_files)
# 将所有要运行多线程的请求扔进线程池
[pool.putRequest(req) for req in requests]
# 所有的线程完成工作后退出
pool.wait()

'''
检查标注文件对不对
'''
for file in index_files:
    index = file[0]
    file = file[1]
    txtname = os.path.join(dst_path_dir, '{}.txt'.format(index))
    imgfile = txtname.replace('.txt','.jpg')
    img = cv2.imread(imgfile)
    h, w= img.shape[:2]
    with codecs.open(txtname,'r','GBK') as f:
        liness = f.readlines()
        for line in liness:
            lines = line.strip('\n').split(' ')
            for i in range(1,5):
                lines[i] = float(lines[i])
            x1 = (lines[1] - lines[3] /2) * w
            x2 = (lines[1] + lines[3]/2)*w
            y1 = (lines[2] - lines[4]/2)*h
            y2 = (lines[2] + lines[4]/2)*h

            x1 = int(x1)
            x2 = int(x2)
            y1 = int(y1)
            y2 = int(y2)

            if lines[0] == '0':
                color = (0,255,0)
            else:
                color = (0,0,255)

            cv2.rectangle(img,(x1,y1),(x2,y2),color)
    cv2.imshow('1',img)
    cv2.waitKey()