python 基于Opencv图像对比

python 基于Opencv图像对比

opencv就不介绍了，直接上代码

# -*- coding: utf-8 -*-
from skimage.metrics import structural_similarity
import imutils
import cv2
# 加载两张图片并将他们转换为灰度
imageA = cv2.imread(r"home.png")
imageB = cv2.imread(r"home1.png")

grayA = cv2.cvtColor(imageA, cv2.COLOR_BGR2GRAY)
grayB = cv2.cvtColor(imageB, cv2.COLOR_BGR2GRAY)

# 计算两个灰度图像之间的结构相似度指数
(score,diff) = structural_similarity(grayA,grayB,full = True)
diff = (diff *255).astype("uint8")
print("SSIM:{}".format(score))

# 找到不同点的轮廓以致于我们可以在被标识为“不同”的区域周围放置矩形
thresh = cv2.threshold(diff,0,255,cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
cnts = cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[1] if imutils.is_cv3() else cnts[0]

# 找到一系列区域，在区域周围放置矩形
for c in cnts:
    (x,y,w,h) = cv2.boundingRect(c)
    cv2.rectangle(imageA,(x,y),(x+w,y+h),(0,255,0),2)
    cv2.rectangle(imageB,(x,y),(x+w,y+h),(0,255,0),2)

# 用cv2.imshow 展现最终对比之后的图片， cv2.imwrite 保存最终的结果图片
cv2.imshow("Modified", imageB)
cv2.imwrite(r"result.png", imageB)
cv2.waitKey(0)