def compare(image1, image2): """ 进行比较 :param image1:图片1 :param image2: 图片2 :return: """ left = 0 # 坐标起始位置 right_num = 0 # 记录相同像素点个数 false_num = 0 # 记录不同像素点个数 all_num = 0 # 记录所有像素点个数 for i in range(left, image1.size[0]): fo...
import numpy as np from PIL import Image from skimage.metrics import structural_similarity as ssim def compare_images(img1_path, img2_path): # 加载图片并转换为灰度图 img1 = Image.open(img1_path).convert('L') img2 = Image.open(img2_path).convert('L') # 转换为NumPy数组 img1_np =...
from PIL import Image from numpy import average, linalg, dot def get_thumbnail(image, size=(30, 30), greyscale=False): image = image.resize(size, Image.ANTIALIAS) if greyscale: image = image.convert('L') return image def image_similarity_vectors_via_numpy(image1, image2): image1 = g...
print pil_image_similarity('/Users/apple/Desktop/git/Vimi_API_Test/Compare_image_test/output.jpg','/Users/apple/Desktop/git/Vimi_API_Test/Compare_image_test/0.jpg')
fromimagededup.methodsimportPHashdefcompare_image_similarity(photo_id, photo_path, encoding_map: dict):"""比较图片相似度 :param photo_id: :param photo_path: :param encoding_map: 哈希值map 首次传空 {} :return:"""encoding=""try: phasher=PHash()#生成图像的二值hash编码encoding =phasher.enc...
h1 = image1.histogram()h2 = image2.histogram()rms = math.sqrt(reduce(operator.add, list(map(lambda a,b: (a-b)**2, h1, h2)))/len(h1) )return rms print pil_image_similarity('/Users/apple/Desktop/git/Vimi_API_Test/Compare_image_test/output.jpg','/Users/apple/Desktop/git/Vimi_...
imread("image1.jpg") image2 = cv2.imread("image2.jpg") # 比较图像 compare_images(image1, image2) 这段代码使用OpenCV库中的cv2.cvtColor()函数将图像转换为灰度图像,然后使用structural_similarity()函数计算图像的相似度。最后,使用cv2.imshow()函数显示比较结果。
方法添加到base_page.py中。 def compare_image_with_screenshot(self，image_name: str)：os.chdir(...
二、安装scikit-image环境 cmd输入:pip install scikit-image 安装成功后如下图显示: 三、python计算两张图片的相似率 from skimage.metrics import structural_similarity as sk_cpt_ssim import cv2 def compare_image(): # 传入图片路径,读取图片 image_a = cv2.imread(r'path1') ...
def check_match(self, x, y, similarity=1): targetwidth, targetheight = self.target.size total_count = targetheight*targetwidth not_matched_count = 0 for smally in range(0, targetheight): for smallx in range(0, targetwidth): if not self.compare(self.screendata[x+smallx, y+smally],...