Python 文件夹中的所有图片进行面部截图显示在一张图中

# coding:utf-8

import os
import cv2
from PIL import Image

#选择分类器模型(下载地址：https://github.com/opencv/opencv/tree/master/data/haarcascades)
classifier = cv2.CascadeClassifier(r'./opencv-master/data/haarcascades/haarcascade_frontalface_default.xml')

#加载文件中的所有图片
def load_images_from_folder(folder):
	imgs = []
	for filename in os.listdir(folder):
		img = cv2.imread(os.path.join(folder,filename))
		if img is not None:
			imgs.append(img)
	return imgs

#将所有图片进行面部截图
def get_images_faces(imglist):
	imgs = []
	for i in range(len(imglist)):
		faces = classifier.detectMultiScale(imglist[i],minNeighbors=5,minSize=(30, 30))
		for (x, y, w, h) in faces:
			imgs.append(imglist[i][y:y+h,x:x+w])
	return imgs

#重置图片大小
def images_resize(imglist,width, height):
	imgs = []
	for i in range(len(imglist)):
		imgs.append(cv2.resize(imglist[i], (width, height)) )
	return imgs

#拼接多图到一张新图片中
def images_joint(imglist,col,width,height):
	imgnum = len(imglist)
	row = col
	if (imgnum%col == 0):
		row = int(imgnum/col)
	else:
		row = int(imgnum/col) + 1
	newimg = Image.new('RGBA',(width*col,height*row),(255,255,255))
	for i in range(row):
		for j in range(col):
			if (col*i+j