Win10 Labelme标注数据转为YOLOV5 训练的数据集

• 将Labelme标注的数据复制到工程的根目录，并将其命名为LabelmeData。我的工程根目录是yolov5-master，如下图：

• 打开工程，在根目录新建LabelmeToYolov5.py。写入下面的代码

  

   

    

     

    
    

     

      import os
     
    
   

    

     

    
    

     

      import numpy as np
     
    
   

    

     

    
    

     

      import json
     
    
   

    

     

    
    

     

      from glob import glob
     
    
   

    

     

    
    

     

      import cv2
     
    
   

    

     

    
    

     

      from sklearn.model_selection import train_test_split
     
    
   

    

     

    
    

     

      from os import getcwd
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      classes = ["aircraft", "oiltank"]
     
    
   

    

     

    
    

     

      # 1.标签路径
     
    
   

    

     

    
    

     

      labelme_path = "LabelmeData/"
     
    
   

    

     

    
    

     

      isUseTest = True  # 是否创建test集
     
    
   

    

     

    
    

     

      # 3.获取待处理文件
     
    
   

    

     

    
    

     

      files = glob(labelme_path + "*.json")
     
    
   

    

     

    
    

     

      files = [i.replace("\\", "/").split("/")[-1].split(".json")[0] for i in files]
     
    
   

    

     

    
    

     

      print(files)
     
    
   

    

     

    
    

     

      if isUseTest:
     
    
   

    

     

    
    

     

          trainval_files, test_files = train_test_split(files, test_size=0.1, random_state=55)
     
    
   

    

     

    
    

     

      else:
     
    
   

    

     

    
    

     

          trainval_files = files
     
    
   

    

     

    
    

     

      # split
     
    
   

    

     

    
    

     

      train_files, val_files = train_test_split(trainval_files, test_size=0.1, random_state=55)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      def convert(size, box):
     
    
   

    

     

    
    

     

          dw = 1. / (size[0])
     
    
   

    

     

    
    

     

          dh = 1. / (size[1])
     
    
   

    

     

    
    

     

          x = (box[0] + box[1]) / 2.0 - 1
     
    
   

    

     

    
    

     

          y = (box[2] + box[3]) / 2.0 - 1
     
    
   

    

     

    
    

     

          w = box[1] - box[0]
     
    
   

    

     

    
    

     

          h = box[3] - box[2]
     
    
   

    

     

    
    

     

          x = x * dw
     
    
   

    

     

    
    

     

          w = w * dw
     
    
   

    

     

    
    

     

          y = y * dh
     
    
   

    

     

    
    

     

          h = h * dh
     
    
   

    

     

    
    

     
    return (x, y, w, h)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      wd = getcwd()
     
    
   

    

     

    
    

     

      print(wd)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      def ChangeToYolo5(files, txt_Name):
     
    
   

    

     

    
    

     
    if not os.path.exists('tmp/'):
     
    
   

    

     

    
    

     

              os.makedirs('tmp/')
     
    
   

    

     

    
    

     

          list_file = open('tmp/%s.txt' % (txt_Name), 'w')
     
    
   

    

     

    
    

     
    for json_file_ in files:
     
    
   

    

     

    
    

     

              json_filename = labelme_path + json_file_ + ".json"
     
    
   

    

     

    
    

     

              imagePath = labelme_path + json_file_ + ".jpg"
     
    
   

    

     

    
    

     

              list_file.write('%s/%s\n' % (wd, imagePath))
     
    
   

    

     

    
    

     

              out_file = open('%s/%s.txt' % (labelme_path, json_file_), 'w')
     
    
   

    

     

    
    

     

              json_file = json.load(open(json_filename, "r", encoding="utf-8"))
     
    
   

    

     

    
    

     

              height, width, channels = cv2.imread(labelme_path + json_file_ + ".jpg").shape
     
    
   

    

     

    
    

     
        for multi in json_file["shapes"]:
     
    
   

    

     

    
    

     

                  points = np.array(multi["points"])
     
    
   

    

     

    
    

     

                  xmin = min(points[:, 0]) if min(points[:, 0]) > 0 else 0
     
    
   

    

     

    
    

     

                  xmax = max(points[:, 0]) if max(points[:, 0]) > 0 else 0
     
    
   

    

     

    
    

     

                  ymin = min(points[:, 1]) if min(points[:, 1]) > 0 else 0
     
    
   

    

     

    
    

     

                  ymax = max(points[:, 1]) if max(points[:, 1]) > 0 else 0
     
    
   

    

     

    
    

     

                  label = multi["label"]
     
    
   

    

     

    
    

     
            if xmax <= xmin:
     
    
   

    

     

    
    

     
                pass
     
    
   

    

     

    
    

     
            elif ymax <= ymin:
     
    
   

    

     

    
    

     
                pass
     
    
   

    

     

    
    

     
            else:
     
    
   

    

     

    
    

     

                      cls_id = classes.index(label)
     
    
   

    

     

    
    

     

                      b = (float(xmin), float(xmax), float(ymin), float(ymax))
     
    
   

    

     

    
    

     

                      bb = convert((width, height), b)
     
    
   

    

     

    
    

     

                      out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')
     
    
   

    

     

    
    

     
                print(json_filename, xmin, ymin, xmax, ymax, cls_id)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      ChangeToYolo5(train_files, "train")
     
    
   

    

     

    
    

     

      ChangeToYolo5(val_files, "val")
     
    
   

    

     

    
    

     

      ChangeToYolo5(test_files, "test")
     
    
   

    

     

    
    

     

      '''
     
    
   

    

     

    
    

     

      file1 = open("tmp/train.txt", "r")
     
    
   

    

     

    
    

     

      file2 = open("tmp/val.txt", "r")
     
    
   

    

     

    
    

     

      file_list1 = file1.readlines() # 将所有变量读入列表file_list1
     
    
   

    

     

    
    

     

      
     
    
   

    

     

    
    

     

      file_list2 = file2.readlines() # 将所有变量读入列表file_list2
     
    
   

    

     

    
    

     

      file3 = open("tmp/trainval.txt", "w")
     
    
   

    

     

    
    

     

      for line in file_list1:
     
    
   

    

     

    
    

     

       print(line)
     
    
   

    

     

    
    

     

       file3.write(line)
     
    
   

    

     

    
    

     

      for line in file_list2:
     
    
   

    

     

    
    

     

       print(line)
     
    
   

    

     

    
    

     

       file3.write(line)
     
    
   

    

     

    
    

     

      '''
     
    
  
 

这段代码执行完成会在LabelmeData生成每个图片的txt标注数据，同时在tmp文件夹下面生成训练集、验证集和测试集的txt，txt记录的是图片的路径，为下一步生成YoloV5训练和测试用的数据集做准备。

• 在tmp文件夹新建makedata.py。执行完成后会在工程的根目录生成VOC数据集。

  

   

    

     

    
    

     

      import shutil
     
    
   

    

     

    
    

     

      import os
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      file_List = ["train", "val", "test"]
     
    
   

    

     

    
    

     

      for file in file_List:
     
    
   

    

     

    
    

     
    if not os.path.exists('../VOC/images/%s' % file):
     
    
   

    

     

    
    

     

              os.makedirs('../VOC/images/%s' % file)
     
    
   

    

     

    
    

     
    if not os.path.exists('../VOC/labels/%s' % file):
     
    
   

    

     

    
    

     

              os.makedirs('../VOC/labels/%s' % file)
     
    
   

    

     

    
    

     
    print(os.path.exists('../tmp/%s.txt' % file))
     
    
   

    

     

    
    

     

          f = open('../tmp/%s.txt' % file, 'r')
     
    
   

    

     

    
    

     

          lines = f.readlines()
     
    
   

    

     

    
    

     
    for line in lines:
     
    
   

    

     

    
    

     
        print(line)
     
    
   

    

     

    
    

     

              line = "/".join(line.split('/')[-5:]).strip()
     
    
   

    

     

    
    

     

              shutil.copy(line, "../VOC/images/%s" % file)
     
    
   

    

     

    
    

     

              line = line.replace('jpg', 'txt')
     
    
   

    

     

    
    

     

              shutil.copy(line, "../VOC/labels/%s/" % file)
     
    
  
 

运行结果如下：

文章来源: wanghao.blog.csdn.net，作者：AI浩，版权归原作者所有，如需转载，请联系作者。

原文链接：wanghao.blog.csdn.net/article/details/108865894