lablelme标注的数据转成YOLO v8 格式

1 labelme 转 yolov8 格式

import json
import cv2
import numpy as np
import os
def json2yolo(path):# dic={'N_shaoxi':'0',   'N_qiaoqi':'1',   'N_qiaojie':'2',   'N_pianyi':'3',   'N_yiwu': '4', \#      'NV_shaoxi': '5', 'NV_qiaoqi': '6', 'NV_qiaojie': '7', 'NV_pianyi': '8', 'NV_yiwu': '9',\#      'R_shaoxi': '10',  'R_qiaoqi': '11',  'R_qiaojie': '12',  'R_pianyi': '13',  'R_yiwu': '14',\#      'XS_shaoxi': '15', "XS_qiaoqi": '16', 'XS_qiaojie': '17', 'XS_pianyi': '18', 'XS_yiwu': '19',#      '1': '0'}dic={'N_shaoxi':'0',   'N_qiaoqi':'1',   'N_qiaojie':'2',   'N_pianyi':'3',   'N_yiwu': '4', \'NV_shaoxi': '5', 'NV_qiaoqi': '6', 'NV_qiaojie': '7', 'NV_pianyi': '8', 'NV_yiwu': '9',\'R_shaoxi': '10',  'R_qiaoqi': '11',  'R_qiaojie': '12',  'R_pianyi': '13',  'R_yiwu': '14',\'XS_shaoxi': '15', "XS_qiaoqi": '16', 'XS_qiaojie': '17', 'XS_pianyi': '18', 'XS_yiwu': '19','XP_shaoxi': '15', "XP_qiaoqi": '16', 'XP_qiaojie': '17', 'XP_pianyi': '18', 'XP_yiwu': '19'}#dic = {'N_shaoxi': '0', 'N_shaoxi': '1','N_qiaojie': '2','N_pianyi':'3','N_yiwu:'4'}  # 类别字典if ".json" in path:data = json.load(open(path,encoding="utf-8"))#读取带有中文的文件w=data["imageWidth"]#获取jaon文件里图片的宽高h=data["imageHeight"]all_line=''for i in  data["shapes"]:#归一化坐标点。并得到cx,cy,w,h[[x1,y1],[x2,y2]]=i['points']x1,x2=x1/w,x2/wy1,y2=y1/h,y2/hcx=(x1+x2)/2cy=(y1+y2)/2wi=abs(x2-x1)hi=abs(y2-y1)#将数据组装成yolo格式line="%s %.4f %.4f %.4f %.4f\n"%(dic[i['label']],cx,cy,wi,hi)#生成txt文件里每行的内容all_line+=line# print(all_line)filename = path.replace('json','txt')#将path里的json替换成txt,生成txt里相对应的文件路径fh = open(filename,'w',encoding='utf-8')fh.write(all_line)fh.close()else:filename = path.replace('.jpg', '.txt')  # 将path里的json替换成txt,生成txt里相对应的文件路径fh = open(filename, 'w', encoding='utf-8')fh.close()path= "E:/_0904/"
path_list_sub = os.listdir(path)
print("path_list_sub", path_list_sub)
for path_sub in path_list_sub:json_path_list =os.listdir(path+path_sub)path_list2=[x for x in json_path_list]#获取所有json文件的路径# path_list2 = [x for x in json_path_list if ".json" in x]  # 获取所有json文件的路径print("len of path_list2 ",path_sub,len(path_list2))for p in path_list2:absolute_path= (path+path_sub+'/'+p)print("abs path",absolute_path)json2yolo(path+path_sub+'/'+p)

2 分为训练集&验证集合

import json
import cv2
import numpy as np
import os
import shutil
root_root_path = "。/0904/"
root_paths = os.listdir(root_root_path)
for root_path in root_paths:  # DATE NAMED DATAroot_path = root_root_path+root_path+'/'# root_path = "E:/AOI_DATA/sort/data0705/"class_path_list = os.listdir(root_path)print("path_list_sub", class_path_list)all_file_path=[]index=0for class_path in class_path_list: #N NV R XSall_path_list =os.listdir(root_path+class_path)for file in all_path_list:# print()all_file_path.append((root_path + class_path + '/' + file))# os.path.exists(test_file.txt)print("file len ",len(all_file_path))txt_file_path=[]for file_path in all_file_path:if file_path[-3:]=="txt":print("file_path",file_path)txt_file_path.append(file_path)# print(txt_file_path)print("txt file len ",len(txt_file_path))train_index = 0valid_index = 0split_index = 0for tf in txt_file_path:if os.path.exists(tf[:-3]+'jpg'):if split_index % 5 != 0:#passshutil.copy(tf,fr'.\X_DATA\train\labels')shutil.copy(tf[:-3]+'jpg', fr'.\train\images')train_index += 1else:shutil.copy(tf,fr'.\X_DATA\valid\labels')shutil.copy(tf[:-3]+'jpg', fr'.\X_DATA\valid\images')valid_index += 1split_index += 1print("train_index image num:", train_index)print("valid_index image num:", valid_index)print("split_index image num:", split_index)