# coding: utf-8 # @Author: 一棵柚子树 # @time: 2022/3/26 0:28 import time import numpy import cv2 from PIL import Image def calculate(image1, image2): hist1 = cv2.calcHist([image1], [0], None, [256], [0, 256]) hist2 = cv2.calcHist([image2], [0], None, [256], [0, 256]) # 计算直方图的重合度 degree = 0 for i in range(len(hist1)): if hist1[i] != hist2[i]: degree = degree + (1 - abs(hist1[i] - hist2[i]) / max(hist1[i], hist2[i])) else: degree = degree + 1 degree = degree / len(hist1) print(degree) return degree def picture_similarity(image1, image2, size=(256, 256)): image1 = Image.open(image1) image2 = Image.open(image2) # 将图像resize后,分离为RGB三个通道,再计算每个通道的相似值 image1 = cv2.cvtColor(numpy.asarray(image1), cv2.COLOR_RGB2BGR) image2 = cv2.cvtColor(numpy.asarray(image2), cv2.COLOR_RGB2BGR) image1 = cv2.resize(image1, size) image2 = cv2.resize(image2, size) sub_image1 = cv2.split(image1) sub_image2 = cv2.split(image2) sub_data = 0 for im1, im2 in zip(sub_image1, sub_image2): sub_data += calculate(im1, im2) print(f"长度:{len(sub_image1)}") sub_data = sub_data / len(sub_image1) return int(sub_data*100) if __name__ == '__main__': img1_path = "desktop.png" img2_path = "desktop2.png" result1 = picture_similarity(img1_path, img2_path) print(f"相似度为:{result1}")
python opencv 图片对比度
原文作者:一棵柚子树996
原文地址: https://blog.csdn.net/m0_47138897/article/details/123783726
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原文地址: https://blog.csdn.net/m0_47138897/article/details/123783726
本文转自网络文章,转载此文章仅为分享知识,如有侵权,请联系博主进行删除。