图片对比

import cv2 as cv
import numpy as np

def display_img(img):
    cv.imshow('image',img)
    cv.waitKey(0)
    cv.destroyAllWindows()
def double_img(file1,file2):
    img1 = cv.imread(file1)
    img2 = cv.imread(file2)
    res = np.hstack((img1,img2))
    display_img(res)

double_img("left_01.png","right_01.png")

全景图片拼接_2d

全景图片拼接

import cv2 
import numpy as np
import matplotlib.pyplot as plt

def display_img(img):
    cv2.imshow('image',img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

def matchKeypoints(kpsA,kpsB,featuresA,featuresB,ratio,reth):
    matcher = cv2.BFMatcher()
    rawMatchers = matcher.knnMatch(featuresA,featuresB,2)
    matchers =[]
    for m in rawMatchers:
        if (len(m)==2 and m[0].distance<m[1].distance*ratio):
            matchers.append((m[0].trainIdx,m[0].queryIdx))
    if len(matchers)>4:
        ptsA = np.float32([kpsA[i] for (_,i) in matchers])
        ptsB = np.float32([kpsB[i] for (i,_) in matchers])

        H,status = cv2.findHomography(ptsA,ptsB,cv2.RANSAC,reth)
        return matchers,H,status
    return None

def detectAndDescribe(img):
    sift = cv2.xfeatures2d.SIFT_create()
    kps,des = sift.detectAndCompute(img,None)
    kps = np.float32([kp.pt for kp in kps])
    return kps,des


def drawMatches(imageA, imageB, kpsA, kpsB, matches, status):
        (hA, wA) = imageA.shape[:2]
        (hB, wB) = imageB.shape[:2]
        vis = np.zeros((max(hA, hB), wA + wB, 3), dtype="uint8")
        vis[0:hA, 0:wA] = imageA
        vis[0:hB, wA:] = imageB
        for ((trainIdx, queryIdx), s) in zip(matches, status):
            if s == 1:
                ptA = (int(kpsA[queryIdx][0]), int(kpsA[queryIdx][1]))
                ptB = (int(kpsB[trainIdx][0]) + wA, int(kpsB[trainIdx][1]))
                cv2.line(vis, ptA, ptB, (0, 255, 0), 1)
        return vis

def stitch(imageA,imageB, ratio=0.75, reprojThresh=4.0,showMatches=False):
        (kpsA, featuresA) = detectAndDescribe(imageA)
        (kpsB, featuresB) = detectAndDescribe(imageB)
        M = matchKeypoints(kpsA, kpsB, featuresA, featuresB, ratio, reprojThresh)
        if M is None:
            return None
        matchers, H, status = M
        result = cv2.warpPerspective(imageA, H, (imageA.shape[1] + imageB.shape[1], imageA.shape[0]))
        result[0:imageB.shape[0], 0:imageB.shape[1]] = imageB  
        if showMatches:
            vis = drawMatches(imageA, imageB, kpsA, kpsB, matchers, status)
            return (result, vis)
        return result
    
def operate_img(file1,file2):
    img1 = cv2.imread(file1)
    img2 = cv2.imread(file2)
    result, vis =stitch(img2,img1, showMatches=True)
    display_img(result)
    display_img(vis)
    
def main():
    f1,f2 ="left_01.png","right_01.png"
    operate_img(f1,f2)
    
main()

效果

全景图片拼接_2d_02

素材

全景图片拼接_2d_03


全景图片拼接_2d_04