python基于selenium所截图片的对比操作

#coding:utf-8 import cv2 import matplotlib.pyplot as plt ''' 新增多个list，将所有不同颜色部分按照一定范围区域划分为多个list，再分别对这多个list画框 1.只对品质、大小一样的图片做对比，（UI自动化截图符合此规格） 2.需要注意的是，当不同点过多，品质过高的图片，可能会出现内存溢出的错误（主要是因为所有像素点均存储于单个list中， 32位python的限制是 536870912 个元素） 3.存在多处不同时，目前以100个像素为基准划分 ——jun ''' img_t1 = cv2.imread("./t2.png") img_t2 = cv2.imread("./t1.png") print img_t1.shape print img_t2.shape if img_t1.shape != img_t2.shape: print "cannot do it" else: img_list = list(img_t1.shape) img_max = max(img_list[0],img_list[1]) img_min = min(img_list[0],img_list[1]) diff,multi_diss_list,name_list = [],[],[] temp_x,temp_y = 0,0 name_i = 0 def make_diff(i,j): temp_diff = [] temp_diff.append(i) temp_diff.append(j) diff.append(temp_diff) def make_list(i,j,flag=0): global multi_diss_list if flag==0: temp = [] temp.append(i) temp.append(j) multi_diss_list[-1].append(temp) else: names = locals() names["diff_list%s"%flag] = [] new_list = names["diff_list%s"%flag] temp = [] temp.append(i) temp.append(j) new_list.append(temp) multi_diss_list.append(new_list) def multi_list(mlist): global temp_y,temp_x,name_i for i in mlist: if i[0]-temp_x>100: name_i+=1 make_list(i[0],i[1], flag=name_i) temp_x = i[0] elif i[1]-temp_y>100: name_i += 1 make_list(i[0],i[1], flag=name_i) temp_y = i[1] else: make_list(i[0],i[1]) def make_rectangle(mlist): temp_x_min,temp_x_max,temp_y_min,temp_y_max = mlist[0][0],mlist[0][0],mlist[0][1],mlist[0][1] for i in mlist: if i[0]>temp_x_max: temp_x_max = i[0] elif i[0]<=temp_x_min: temp_x_min = i[0] for i in mlist: if i[1]>temp_y_max: temp_y_max = i[1] elif i[1]<=temp_y_min: temp_y_min = i[1] return (temp_x_min,temp_y_min,temp_x_max,temp_y_max) for i in xrange(0,img_max): for j in xrange(0,img_min): if img_t1[j][i].all() == img_t2[j][i].all(): pass else: make_diff(i,j) if len(diff) == 0: print "all the same" else: print len(diff) multi_list(mlist=diff) for i in multi_diss_list: if len(i) == 1: pass else: left_x,left_y,right_x,right_y = make_rectangle(i) left_top = (left_x,left_y) right_bottom = (right_x,right_y) cv2.rectangle(img_t2, left_top, right_bottom, (0, 0, 255), thickness=2) cv2.imwrite('diffPIC.jpg', img_t2)