我要评论python两张图片对比得出相似度
import numpy
import cv2
from pil import image
def calculate(image1, image2):
image1 = cv2.cvtcolor(numpy.asarray(image1), cv2.color_rgb2bgr)
image2 = cv2.cvtcolor(numpy.asarray(image2), cv2.color_rgb2bgr)
hist1 = cv2.calchist([image1], [0], none, [256], [0.0, 255.0])
hist2 = cv2.calchist([image2], [0], none, [256], [0.0, 255.0])
# 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)
return degree
def classify_hist_with_split(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)
sub_data = sub_data / 3
return sub_data
if __name__ == '__main__':
img1_path = r"e:\report\camera_pictures\\2.png"
img2_path = r"e:\report\camera_pictures\\3.png"
result1 = classify_hist_with_split(img1_path, img2_path)
print("相似度为：" + "%.2f%%" % (result1 * 100))
运行结果
d:\python3.8.6\python.exe d:/pythonworkspace/chenbang/test_4.py 相似度为：87.70% process finished with exit code 0
注意事项
在自动化测试对比图片时，实际场景可能受时间、设备、摄像头影响，可能不准确。
解决方法是循环对比5次，有一次大于80%就break退出循环，每一次对比睡眠1s，如果5次都对比失败了，则图片对比fail
总结
以上为个人经验，希望能给大家一个参考，也希望大家多多支持代码网。
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