图片拼接 --全景图合成
开发环境
- python3
- opencv-contrib-python—3.4.2.16
- opencv-python—3.4.2.16
- PyQt5 — 5.15.6
基本思路
- SIFT特征提取
- FLANN 特征匹配
- 单应性矩阵
- 仿射变换
- 图片融合
- 最大内接矩形裁剪
- GUI界面显示
代码程序
完整工程：https://gitee.com/wangchaosun/image_merge
图片融合
merge_pic.py
import numpy as np import cv2 LEFTDIR = 1 RIGHTDIR = 2 # get sift ,flann Machine def getMachine(): FLANN_INDEX_KDTREE = 1 index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5) search_params = dict(checks=50) flann = cv2.FlannBasedMatcher(index_params, search_params) sift = cv2.xfeatures2d_SIFT().create() return sift,flann def imgProcess(img,top,bot,left,right): imgBord = cv2.copyMakeBorder(img,top,bot,left,right,cv2.BORDER_CONSTANT,value=(0,0,0)) imgGray = cv2.cvtColor(imgBord,cv2.COLOR_BGR2GRAY) return imgBord,imgGray def findEdgeDot(img,x1,x2,y1,y2): dotsum = 0 for i in range(x1,x2+1): for j in range(y1,y2+1): if not img.item(j,i): dotsum +=1 return dotsum def getSmallOuterRect(img): gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) thresh,binary=cv2.threshold(gray,1,255,cv2.THRESH_BINARY) image,contours,hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) areaList = [] for contour in contours: area = cv2.contourArea(contour) areaList.append(area) return cv2.boundingRect(contours[np.argmax(areaList)]) def getMaxInnerRect(img,step): # 输入的图像是二进制的 gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) thresh,binary=cv2.threshold(gray,1,255,cv2.THRESH_BINARY) x = 0 y = 0 h,w = binary.shape topdot = findEdgeDot(binary,x,x+w-1,y,y) botdot = findEdgeDot(binary,x,x+w-1,y+h-1,y+h-1) lefdot = findEdgeDot(binary,x,x,y,y+h-1) rigdot = findEdgeDot(binary,x+w-1,x+w-1,y,y+h-1) edgedot = [topdot,botdot,lefdot,rigdot] while topdot or botdot or lefdot or rigdot : maxedge = max(edgedot) if maxedge == topdot: y += step h -= step elif maxedge == botdot: h -= step elif maxedge == lefdot: x += step w -= step else: w -= step topdot = findEdgeDot(binary,x,x+w-1,y,y) botdot = findEdgeDot(binary,x,x+w-1,y+h-1,y+h-1) lefdot = findEdgeDot(binary,x,x,y,y+h-1) rigdot = findEdgeDot(binary,x+w-1,x+w-1,y,y+h-1) edgedot = [topdot,botdot,lefdot,rigdot] return x,y,w,h def mergeImge(img1,img2,sift,flann): srcImg,img1gray = imgProcess(img1,img1.shape[0]//2,img1.shape[0]//2,img1.shape[1]//2,img1.shape[1]//2) testImg,img2gray= imgProcess(img2,img2.shape[0]//2,img2.shape[0]//2,img2.shape[1]//2,img2.shape[1]//2) # find the keypoints and descriptors with SIFT kp1, des1 = sift.detectAndCompute(img1gray, None) kp2, des2 = sift.detectAndCompute(img2gray, None) # FLANN parameters matches = flann.knnMatch(des1, des2, k=2) # Need to draw only good matches, so create a mask matchesMask = [[0, 0] for i in range(len(matches))] good = [] pts1 = [] pts2 = [] # ratio test as per Lowe's paper for i, (m, n) in enumerate(matches): if m.distance < 0.7*n.distance: good.append(m) pts2.append(kp2[m.trainIdx].pt) pts1.append(kp1[m.queryIdx].pt) matchesMask[i] = [1, 0] # draw_params = dict(matchColor=(0, 255, 0), # singlePointColor=(255, 0, 0), # matchesMask=matchesMask, # flags=0) #img3 = cv2.drawMatchesKnn(img1gray, kp1, img2gray, kp2, matches, None, **draw_params) rows, cols = srcImg.shape[:2] MIN_MATCH_COUNT = 10 if len(good) > MIN_MATCH_COUNT: src_pts = np.float32([kp1[m.queryIdx].pt for m in good]).reshape(-1, 1, 2) dst_pts = np.float32([kp2[m.trainIdx].pt for m in good]).reshape(-1, 1, 2) M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0) warpImg = cv2.warpPerspective(testImg, np.array(M), (testImg.shape[0]*2, testImg.shape[1]*2), flags=cv2.WARP_INVERSE_MAP) direction = -1 # overlap region for col in range(0, cols): if srcImg[:, col].any() and warpImg[:, col].any(): left = col break if srcImg[:, left-1].any(): direction = LEFTDIR else: direction = RIGHTDIR for col in range(cols-1, 0, -1): if srcImg[:, col].any() and warpImg[:, col].any(): right = col break # get max region res = np.zeros([rows, cols, 3], np.uint8) for row in range(0, rows): for col in range(0, cols): if not srcImg[row, col].any(): res[row, col] = warpImg[row, col] elif not warpImg[row, col].any(): res[row, col] = srcImg[row, col] else: srcImgLen = float(abs(col - left)) testImgLen = float(abs(col - right)) alpha = 1- srcImgLen / (srcImgLen + testImgLen) # 离得越近权重越大 if direction == LEFTDIR: alpha = 1-alpha res[row, col] = np.clip(srcImg[row, col] * (1-alpha) + warpImg[row, col] * alpha, 0, 255) # opencv is bgr, matplotlib is rgb x,y,w,h = getSmallOuterRect(res) resImg = res[y:y+h,x:x+w] x,y,w,h = getMaxInnerRect(resImg,2) outimg = resImg[y:y+h,x:x+w] return (True,resImg,outimg) #res = cv2.cvtColor(res, cv2.COLOR_BGR2RGB) # show the result # plt.figure() # plt.imshow(res) # plt.show() else: return (False) if __name__ == "__main__": img1 = cv2.imread("./img/test1.jpg") img2 = cv2.imread("./img/test2.jpg") sift,flann = getMachine() res = mergeImge(img1,img2,sift,flann) if(res[0]): cv2.imshow("res",res[2]) cv2.waitKey()
GUI界面
gui.py
import sys import cv2 from merge_pic import mergeImge,getMachine from PyQt5.QtWidgets import QApplication,QPushButton,QFileDialog,QMainWindow,QMessageBox,QLabel from PyQt5.QtGui import QIcon,QImage, QPixmap class myGUI(QMainWindow): def __init__(self): super().__init__() self.img1 = None self.img2 = None self.outimg = None self.outimg_state = 0 self.imgNum = 0 self.sift,self.flann = getMachine() self.initUI() def initUI(self): self.setFixedSize(1000,800) self.setWindowTitle('IMAGE MERGE') #self.statusBar() self.setWindowIcon(QIcon('./source/imgsrc/icon.png')) self.imglbl = QLabel(self) #self.imglbl.setScaledContents (True) self.imglbl.resize(900,700) self.imglbl.move(50,50) choiceImg = QPushButton('加载图片', self) choiceImg.setFixedSize(100,50) choiceImg.move((1000//3-100)//2, 30) choiceImg.clicked.connect(self.openFile) mergeImg = QPushButton('拼接图片', self) mergeImg.setFixedSize(100,50) mergeImg.move((1000//3-100)//2+1000//3, 30) mergeImg.clicked.connect(self.merge) saveImg = QPushButton('保存图片', self) saveImg.setFixedSize(100,50) saveImg.move((1000//3-100)//2+1000//3*2, 30) saveImg.clicked.connect(self.saveFile) self.statusBar().showMessage("请加载图片!!!") self.show() def saveFile(self): if self.outimg_state: filter = "Images (*.jpg);;Images (*.bmp);;Images (*.png)" fname = QFileDialog.getSaveFileName(self, 'Save file', './output/',filter) cv2.imwrite(fname[0],self.outimg) else: self.statusBar().showMessage("没有拼接成功的图片!!!") def merge(self): if self.imgNum == 2: self.statusBar().showMessage("正在拼接中，请耐心等待~~~") QApplication.processEvents() res = mergeImge(self.img1,self.img2,self.sift,self.flann) self.img2 = None if not res[0]: self.statusBar().showMessage("没有足够的特征点,拼接失败!!!") self.imgNum = 0 self.img1 = None else: self.imgNum = 1 self.img1 = res[1] self.outimg = res[2] outimg = self.outimg.copy() self.outimg_state=1 if outimg.shape[1] >900: outimg = cv2.resize(outimg,(900,int(900/outimg.shape[1] * outimg.shape[0]))) if outimg.shape[0] >700: outimg = cv2.resize(outimg,(int(700/outimg.shape[0] * outimg.shape[1]),700)) imgrgb = cv2.cvtColor(outimg,cv2.COLOR_BGR2RGB) w = imgrgb.shape[1] # 获取图像大小 h = imgrgb.shape[0] frame = QImage(imgrgb.data, w,h,w*3,QImage.Format_RGB888) pix = QPixmap.fromImage(frame) self.imglbl.setPixmap (pix) self.statusBar().showMessage("继续拼接-->请加载新的图片") else: self.statusBar().showMessage("图片数量不足，请继续添加...") def openFile(self): fname = QFileDialog.getOpenFileName(self, 'Choice Image', './img/') if not self.imgNum: self.img1 = cv2.imread(fname[0]) if self.img1 is None: self.statusBar().showMessage("加载图片失败,请重新选择!!!") QMessageBox.warning(self,'Warning', '无效的图片! ') else: self.imgNum += 1 self.statusBar().showMessage("还需加载一张图片") elif self.imgNum==1: self.img2 = cv2.imread(fname[0]) if self.img2 is None: self.statusBar().showMessage("加载图片失败,请重新选择!!!") QMessageBox.warning(self,'Warning', '无效的图片! ') else: self.imgNum += 1 self.statusBar().showMessage("已加载两张图片，可以拼接!!!") if __name__ == '__main__': app = QApplication(sys.argv) ex = myGUI() sys.exit(app.exec_())
结果展示
原始图片
拼接结果
- 两张
- 三张
