如何通过图片拼接技术制作全景图合成？

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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 + 图像融合 + 最大内接矩形裁剪

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：​​gitee.com/wangchaosun…​​

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

2. 三张