手把手教你通过YOLOv5训练自己的目标检测模型

 # coding:utf-8

    
  
    
 import os
    
 import random
    
 import argparse
    
  
    
 parser = argparse.ArgumentParser()
    
 #xml文件的地址，根据自己的数据进行修改 xml一般存放在Annotations下
    
 parser.add_argument('--xml_path', default='Annotations', type=str, help='input xml label path')
    
 #数据集的划分，地址选择自己数据下的ImageSets/Main
    
 parser.add_argument('--txt_path', default='ImageSets/Main', type=str, help='output txt label path')
    
 opt = parser.parse_args()
    
  
    
 trainval_percent = 1.0
    
 train_percent = 0.9
    
 xmlfilepath = opt.xml_path
    
 txtsavepath = opt.txt_path
    
 total_xml = os.listdir(xmlfilepath)
    
 if not os.path.exists(txtsavepath):
    
     os.makedirs(txtsavepath)
    
  
    
 num = len(total_xml)
    
 list_index = range(num)
    
 tv = int(num * trainval_percent)
    
 tr = int(tv * train_percent)
    
 trainval = random.sample(list_index, tv)
    
 train = random.sample(trainval, tr)
    
  
    
 file_trainval = open(txtsavepath + '/trainval.txt', 'w')
    
 file_test = open(txtsavepath + '/test.txt', 'w')
    
 file_train = open(txtsavepath + '/train.txt', 'w')
    
 file_val = open(txtsavepath + '/val.txt', 'w')
    
  
    
 for i in list_index:
    
     name = total_xml[i][:-4] + '\n'
    
     if i in trainval:
    
     file_trainval.write(name)
    
     if i in train:
    
         file_train.write(name)
    
     else:
    
         file_val.write(name)
    
     else:
    
     file_test.write(name)
    
  
    
 file_trainval.close()
    
 file_train.close()
    
 file_val.close()
    
 file_test.close()
    
    
    
    

 # -*- coding: utf-8 -*-

    
 import xml.etree.ElementTree as ET
    
 import os
    
 from os import getcwd
    
  
    
 sets = ['train', 'val', 'test']
    
 classes = ['黑葡萄', '绿葡萄', '樱桃', '西瓜', '龙眼', '香蕉', '芒果', '菠萝', '柚子', '草莓', '苹果', '柑橘', '火龙果', '梨子',
    
        '花生', '黄瓜', '土豆', '大蒜', '茄子', '白萝卜', '辣椒', '胡萝卜', '花菜', '白菜', '番茄', '西蓝花', '橙子']  # 改成自己的类别
    
 abs_path = os.getcwd()
    
 print(abs_path)
    
  
    
 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
    
  
    
 def convert_annotation(image_id):
    
     in_file = open(r'E:\detect\yolov5\paper_data\Annotations\%s.xml' % (image_id), encoding='UTF-8')
    
     out_file = open(r'E:\detect\yolov5\paper_data\labels\%s.txt' % (image_id), 'w')
    
     tree = ET.parse(in_file)
    
     root = tree.getroot()
    
     size = root.find('size')
    
     w = int(size.find('width').text)
    
     h = int(size.find('height').text)
    
     for obj in root.iter('object'):
    
     difficult = obj.find('difficult').text
    
 #        difficult = obj.find('Difficult').text
    
     cls = obj.find('name').text
    
     if cls not in classes or int(difficult) == 1:
    
         continue
    
     cls_id = classes.index(cls)
    
     xmlbox = obj.find('bndbox')
    
     b = (float(xmlbox.find('xmin').text), float(xmlbox.find('xmax').text), float(xmlbox.find('ymin').text),
    
          float(xmlbox.find('ymax').text))
    
     b1, b2, b3, b4 = b
    
     # 标注越界修正
    
     if b2 > w:
    
         b2 = w
    
     if b4 > h:
    
         b4 = h
    
     b = (b1, b2, b3, b4)
    
     bb = convert((w, h), b)
    
     out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')
    
  
    
 wd = getcwd()
    
 for image_set in sets:
    
     if not os.path.exists(r'E:\detect\yolov5\paper_data\labels'):
    
     os.makedirs(r'E:\detect\yolov5\paper_data\labels')
    
     image_ids = open(r'E:\detect\yolov5\paper_data\ImageSets\Main\%s.txt' % (image_set)).read().strip().split()
    
     list_file = open(r'E:\detect\yolov5\paper_data\%s.txt' % (image_set), 'w')
    
     for image_id in image_ids:
    
     list_file.write(abs_path + '\images\%s.jpg\n' % (image_id))
    
     convert_annotation(image_id)
    
     list_file.close()