python opencv图像识别（相同大小图片）

简介

由于项目需要对比两张相同图片的相似度，因此采用opencv将图片转为灰阶数组，然后对比相应的数组来取相似度，此方法只适用于大小相同的图片，较为局限

# -*- coding: utf-8 -*-
import cv2
import os
# scikit-image
from skimage.metrics import structural_similarity as ssim

class PictureSimilarity():
    """
    Image cutting and image recognition
    Parameters:
    origin_img: 起始图片
    compare_img: 需要对比的图片
    start_x: 裁切的起始x轴
    start_y: 裁切的起始y轴
    end_x: 裁切的末尾x轴
    end_y: 裁切的末尾y轴
    """
    def __init__(self, origin_img, compare_img, start_y=None, end_y=None, start_x=None, end_x=None):
        self.origin_img = origin_img[0]
        self.compare_img = compare_img[0]
        self.start_x = start_x
        self.start_y = start_y
        self.end_x = end_x
        self.end_y = end_y

    def compute_Similarity(self):
        try:
            print(f"compute acquaintance")
            image1 = cv2.imread(self.origin_img)
            image2 = cv2.imread(self.compare_img)
            if self.start_x is not None:
                image1 = image1[int(self.start_y):int(self.end_y), int(self.start_x):int(self.end_x)]
                cut_img = "{}_cut.png".format(os.path.splitext(self.origin_img)[0])
                cv2.imwrite(cut_img, image1)
            else:
                image1 = image1
            height1, wide1 = image1.shape[0:2]
            if not height1 or not wide1:
                print("Picture coordinate error, screenshot size cannot be zero")
            if image1.shape != image2.shape:
                print("Inconsistent picture size")
                # 会强制拉伸图片
                image2 = cv2.resize(image2, (image1.shape[1],image1.shape[0]))
                resize_img = "{}_resize.png".format(os.path.splitext(self.compare_img)[0])
                cv2.imwrite(resize_img, image2)
            image1 = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
            image2 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
            acquaintance = ssim(image1, image2)
            acquaintance = acquaintance*100
            acquaintance = round(acquaintance, 2)
            print(f"acquaintance  is {acquaintance}")
            return acquaintance
        except Exception as e:
            print(f"compute_Similarity error is {str(e)}")

    def compute_img(self):
        Similarity = None
        try:
            print(f"start compute acquaintance")
            print(self.origin_img)
            if os.path.exists(self.origin_img) and os.path.exists(self.compare_img):
                Similarity = self.compute_Similarity()
            else:
                print("content not exist")
        except Exception as e:
            print(f"compute_img error is {str(e)}")
        finally:
            return Similarity

if __name__ == "__main__":
    image_path1 = "/home/ts/workspace/image2_2.png",
    image_path2 = "/home/ts/workspace/image2.png",
    test = PictureSimilarity(image_path1, image_path2, 12,189,23,400)
    result = test.compute_img()
    print(result)