Intercept the coordinate points (four point coordinates of the face frame) face image from the marked XML file and save it in the specified folder

In target detection , Datasets are often used labelimg mark , Will generate xml file . The purpose of this article is according to xml Label the file to crop the target , In order to remove the background information .
Detailed connection ：
details

import cv2
import xml.etree.ElementTree as ET
import os


img_path = r'Y:\V47\Indoor\BWPhoto\Normal\2203181450_Indoor_Normal'  #  Picture path 
xml_path = r'Y:\V47\Indoor\BWPhoto\Normal\2203181450_Indoor_Normal'  #  Tag path 
obj_img_path = r'D:/cut'  #  Target clipping image storage path 

for img_file in os.listdir(img_path):  #  Traverse the picture folder 
    if img_file[-4:] in ['.bmp', '.jpg', '.png']:  #  Determine whether the file is in picture format 
        img_filename = os.path.join(img_path, img_file)  #  Mosaic the image path with the image name 

        img_cv = cv2.imread(img_filename)  #  Read the picture 
        img_name = (os.path.splitext(img_file)[0])  #  Split the image name 
        img_name_ = img_name.split('_')[1]


        # Find the label xml File pathname 
        xml_name = xml_path + '\\' + '%s.xml' % ('PADRecord_'+ img_name_)  #  Using tag paths 、 Picture name 、xml Complete path name suffix 
        print(xml_name)
        if os.path.exists(xml_name):  #  Determine whether a label with the same name as the picture exists , Because not all the pictures are marked 
            root = ET.parse(xml_name).getroot()  #  utilize ET Read xml file 
            count = 0  #  Statistics of the number of target boxes , Prevent the target file from overwriting 
            for obj in root.iter('LocalizedFaces'):  #  Traverse all target boxes 
                name = obj.find('LocalizedFace').text  #  Get the name of the target box , namely label name 

                xmlbox = obj.find('LocalizedFace')  #  Find the box target 
                x0 = xmlbox.find('JFace').text  #  Take out the four vertex coordinates of the box target 
                y0 = xmlbox.find('IFace').text
                x1 = xmlbox.find('WidthFace').text
                y1 = xmlbox.find('HeightFace').text
                obj_img = img_cv[int(y0):int(y0)+int(y1), int(x0):int(x0)+int(x1)]  # cv2 Crop out the picture in the target box 

                # cv2.imshow("image", obj_img) #  Display images 
                # cv2.waitKey(0)
                # cv2.destroyAllWindows()

                cv2.imwrite(obj_img_path + '\\' + '%s_%s' % (img_name, count) + '.jpg', obj_img)  #  Save cut pictures 
                count += 1  #  The statistical value of the target box increases automatically 1

print(" Crop complete ！")