Python实现对比两张图片并标记差异

import cv2
import ezdxf
from skimage.metrics import structural_similarity

left_img = cv2.imread("left.png")
right_img = cv2.imread("right.png")
gray_left = cv2.cvtColor(left_img, cv2.COLOR_BGR2GRAY)
gray_right = cv2.cvtColor(right_img, cv2.COLOR_BGR2GRAY)

doc_left = ezdxf.readfile("left.dxf")
doc_right = ezdxf.readfile("right.dxf")

hsv = cv2.cvtColor(right_img, cv2.COLOR_BGR2HSV)
lower_red = np.array([0, 50, 50])
upper_red = np.array([10, 255, 255])
mask = cv2.inRange(hsv, lower_red, upper_red)
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

diff = cv2.absdiff(gray_left, gray_right)
_, thresh = cv2.threshold(diff, 30, 255, cv2.THRESH_BINARY)

right_entities = {entity.dxf.handle for entity in doc_right.modelspace()}
left_entities = {entity.dxf.handle for entity in doc_left.modelspace()}
new_entities = right_entities - left_entities

(height, width) = right_roi.shape[:2]
center = (width // 2, height // 2)
rotation_matrix = cv2.getRotationMatrix2D(center, angle=90, scale=1)
rotated_left = cv2.warpAffine(left_roi, rotation_matrix, (width, height))
ssim_score = structural_similarity(rotated_left, right_roi)
if ssim_score > 0.8:  # 阈值可调整
    cv2.rectangle(right_img, (x, y), (x+w, y+h), (0, 255, 0), 2)  # 标记为旋转后的零件

for (x, y, w, h) in new_contours:
    cv2.rectangle(right_img, (x, y), (x+w, y+h), (0, 0, 255), 2)

from skimage.metrics import structural_similarity as compare_ssim
import imutils
import cv2
import numpy as np

image = "C:/Users/ts/Desktop/img/screenshot.png"
imageCompare = "C:/Users/ts/Desktop/img/screenshot1.png"
image= cv2.imdecode(np.fromfile(image, dtype=np.uint8), -1)
image_compare= cv2.imdecode(np.fromfile(image_compare, dtype=np.uint8), -1)

h1, w1,c1 = image.shape
h2, w2,c2= imageCompare.shape
image_compare = cv2.resize(image_compare ,dsize=(w1,h1))

gray_image= cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
gray_image_ompare = cv2.cvtColor(image_compare ,cv2.COLOR_BGR2GRAY)

(score,diff) = compare_ssim(gray_image,gray_image_ompare ,full = True)
diff = (diff *255).astype("uint8")
retval,thresh = cv2.threshold(diff,200,255,cv2.THRESH_BINARY_INV)
 #参数thresh：阈值，用于确定像素是否应该被视为前景或背景，调测下来200比较合适
cnts=cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[1] if imutils.is_cv3() else cnts[0]
loacation_list =[]
for c in cnts:
      (x,y,w,h) = cv2.boundingRect(c)  
      loacation_list.append((x,y,x+w,y+h))

for index,item in enumerate(loacation_list):
    #圈出不同    
    x,y,x1,y1 = item
    cv2.rectangle(imageA,(x,y),(x1,y1),(0,0,255),2)
    cv2.rectangle(imageB,(x,y),(x1,y1),(0,0,255),2)
    #不同处添加序号
    imageA = cv2.putText(imageA,str(index+1), (x,y+24), cv2.FONT_HERSHEY_DUPLEX, 1, (0, 0, 255))

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfFloat;
import org.opencv.core.MatOfInt;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

import java.util.Arrays;

public class ImageSimilarity {

   static {
        // 设置库路径
        System.setProperty("java.library.path", "D:\\anzhuang\\opencv\\opencv\\build\\java\\x64");
        // 加载 OpenCV 库
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
    }

    /**
     * 比较两张图片的相似度
     * @param imgPath1 图片1的路径
     * @param imgPath2 图片2的路径
     * @return 相似度值（范围：0到1，1表示完全相同）
     */
    public static double compareImages(String imgPath1, String imgPath2) {
        // 加载图片
        Mat img1 = Imgcodecs.imread(imgPath1);
        Mat img2 = Imgcodecs.imread(imgPath2);

        // 转换为灰度图
        Mat grayImg1 = new Mat();
        Mat grayImg2 = new Mat();
        Imgproc.cvtColor(img1, grayImg1, Imgproc.COLOR_BGR2GRAY);
        Imgproc.cvtColor(img2, grayImg2, Imgproc.COLOR_BGR2GRAY);

        // 计算直方图
        Mat hist1 = new Mat();
        Mat hist2 = new Mat();
        MatOfInt histSize = new MatOfInt(256); // 直方图大小
        MatOfFloat ranges = new MatOfFloat(0f, 256f); // 像素值范围
        Imgproc.calcHist(Arrays.asList(grayImg1), new MatOfInt(0), new Mat(), hist1, histSize, ranges);
        Imgproc.calcHist(Arrays.asList(grayImg2), new MatOfInt(0), new Mat(), hist2, histSize, ranges);

        // 比较直方图
        return Imgproc.compareHist(hist1, hist2, Imgproc.CV_COMP_CORREL);
    }

    public static void main(String[] args) {
        String imgPath1 = "path/to/image1.jpg";
        String imgPath2 = "path/to/image2.jpg";

        double similarity = compareImages(imgPath1, imgPath2);
        System.out.println("图片相似度: " + similarity);
    }
}