问题描述
我使用 Insta 360 Evo。但是，我将其用作立体相机并想对其进行校准。为此，我想使用 OpenCV 鱼眼。单独校准相机有效，但不适用于 StereoCalibrate 功能。在那里我总是收到以下错误消息：
cv2.error: OpenCV(4.5.1) C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-wvn_it83\opencv\modules\calib3d\src\fisheye.cpp:1051： 错误：（-215：断言失败）abs_max
当我查看 Fisheye.cpp 时，错误只会在我有错误的校准数据时出现，但是我已经多次替换了数据，但它不起作用。 是不是 OpenCV 不能在 180 度的 FOV 下工作？ 如果可以，是否还有其他方法可以校准立体相机？
这是我的代码：
FisheyeCalibration.py -> 用于一台鱼眼相机
import cv2
assert cv2.__version__[0] >= '3','The fisheye module requires opencv version >= 3.0.0'
from VideoReader import VideoReader
import os
import numpy as np
class calibrateFisheye(object):
def __init__(self,videoIn,parameterOut,CHECKERBOARD=(5,7)):
self.video = VideoReader(videoIn)
self.parameterOut = parameterOut
self.CHECKERBOARD = CHECKERBOARD
#self.subpix_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,30,0.1)
self.calibration_flags = cv2.fisheye.CALIB_RECOmpuTE_EXTRINSIC + cv2.fisheye.CALIB_CHECK_COND + cv2.fisheye.CALIB_FIX_SKEW
#objp = np.zeros((1,CHECKERBOARD[0] * CHECKERBOARD[1],3),np.float32)
#objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0],0:CHECKERBOARD[1]].T.reshape(-1,2)
self.subpix_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,0.1)
objp = np.zeros((CHECKERBOARD[0] * CHECKERBOARD[1],1,np.float64)
objp[:,2)
self.objp = objp
self.objpoints = [] # 3d point in real world space
self.imgpoints = [] # 2d points in image plane.
self.computePoints()
self.calibrate()
self.saveNp()
def _skip(self,count):
for i in range(count):
retVideo,_ = self.video.read()
if not retVideo:
return
def computePoints(self):
retVideo,f = self.video.read()
while retVideo:
print("Process-ID: {}\t\tCalibration finished to {:.2f} %".format(os.getpid(),self.video.progress()))
gray = self.video.getGrayFrame()
# Find the chess board corners
ret,corners = cv2.findChessboardCorners(gray,self.CHECKERBOARD,cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_norMALIZE_IMAGE)
if ret == True:
self.objpoints.append(self.objp)
cv2.cornerSubPix(gray,corners,(3,(-1,-1),self.subpix_criteria)
self.imgpoints.append(corners)
self._skip(0)
retVideo,f = self.video.read()
# = False
def calibrate(self):
self.objpoints = np.array(self.objpoints)
self.imgpoints = np.array(self.imgpoints)
N_OK = len(self.objpoints)
self.K = np.zeros((3,3))
self.D = np.zeros((4,1))
self.rvecs = [np.zeros((1,dtype=np.float64) for i in range(N_OK)]
self.tvecs = [np.zeros((1,dtype=np.float64) for i in range(N_OK)]
self.rms,_,_ = \
cv2.fisheye.calibrate(
self.objpoints,self.imgpoints,(self.video.width,self.video.height),self.K,self.D,self.rvecs,self.tvecs,self.calibration_flags,(cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,1e-6)
)
def saveNp(self):
np.save(self.parameterOut + "k",self.K)
np.save(self.parameterOut + "d",self.D)
np.save(self.parameterOut + "rvecs",self.rvecs)
np.save(self.parameterOut + "tvecs",self.tvecs)
np.save(self.parameterOut + "rms",self.rms)
StereoFisheyeCaibration.py -> 用于 StereoCalibration
from VideoReader import VideoReader
import cv2
assert cv2.__version__[0] >= '3','The fisheye module requires opencv version >= 3.0.0'
import numpy as np
class calibrationFisheyeStereo(object):
def __init__(self,paramerterIn,7),skip=0):
print(skip)
self.skip = skip
self.CHECKERBOARD = CHECKERBOARD
self.leftVideo = VideoReader(videoIn[0])
self.rightVideo = VideoReader(videoIn[1])
self.parameterLeft = paramerterIn[0]
self.parameterRight = paramerterIn[1]
self.parameterOut = parameterOut
self.subpix_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,2)
self.objp = objp
self.objpoints = [] # 3d point in real world space
self.imgpointsLeft = [] # 2d points in image plane.
self.imgpointsRight = [] # 2d points in image plane.
self.computePoints()
self.calibrate()
self.saveNp()
def _skip(self,count):
for i in range(count):
retVideoL,_ = self.leftVideo.read()
retVideoR,_ = self.rightVideo.read()
if not retVideoR or not retVideoL:
return
def computePoints(self):
retVideoL,f1 = self.leftVideo.read()
retVideoR,f2 = self.rightVideo.read()
i = 0
while retVideoL and retVideoR:
print("Calibration finished to {:.2f} %".format(self.leftVideo.progress()))
grayL = self.leftVideo.getGrayFrame()
grayR = self.rightVideo.getGrayFrame()
retL,cornersL = cv2.findChessboardCorners(grayL,cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_norMALIZE_IMAGE)
retR,cornersR = cv2.findChessboardCorners(grayR,cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_norMALIZE_IMAGE)
if ((retL == True) and (retR == True)):
i += 1
print(i)
#img = cv2.drawChessboardCorners(grayL,cornersL,retL)
#img = cv2.resize(img,(self.leftVideo.width//2,self.leftVideo.height//2),interpolation=cv2.INTER_AREA)
#if cv2.waitKey(1) & 0xFF == ord('q'):
#exit()
#cv2.imshow("windowTxt",img)
self.objpoints.append(self.objp)
cv2.cornerSubPix(grayL,self.subpix_criteria)
self.imgpointsLeft.append(cornersL)
cv2.cornerSubPix(grayR,cornersR,self.subpix_criteria)
self.imgpointsRight.append(cornersR)
self._skip(self.skip)
retVideoL,_ = self.rightVideo.read()
print(i)
def calibrate(self):
self.D_left = np.load(self.parameterLeft + "d.npy")
self.K_left = np.load(self.parameterLeft + "k.npy")
self.D_right = np.load(self.parameterRight + "d.npy")
self.K_right = np.load(self.parameterRight + "k.npy")
self.R = np.zeros((1,dtype=np.float64)
self.T = np.zeros((1,dtype=np.float64)
TERMINATION_CRITERIA = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,0.1)
FLAG = cv2.fisheye.CALIB_FIX_INTRINSIC
N_OK = len(self.imgpointsLeft)
self.objpoints = np.array(self.objpoints,dtype=np.float64)
#self.imgpointsLeft = np.asarray(self.imgpointsLeft,dtype=np.float64)
#self.imgpointsRight = np.asarray(self.imgpointsRight,dtype=np.float64)
self.imgpointsLeft = np.array(self.imgpointsLeft,dtype=np.float64)
self.imgpointsRight = np.array(self.imgpointsRight,dtype=np.float64)
"""self.objpoints = np.reshape(self.objpoints,(N_OK,self.CHECKERBOARD[0] * self.CHECKERBOARD[1],3))
self.imgpointsLeft = np.reshape(self.imgpointsLeft,2))
self.imgpointsRight = np.reshape(self.imgpointsRight,2))"""
self.rms,self.K_left,self.D_left,self.K_right,self.D_right,self.R,self.T = \
cv2.fisheye.stereoCalibrate(
self.objpoints,self.imgpointsLeft,self.imgpointsRight,(self.leftVideo.width,self.leftVideo.height),self.T,FLAG,TERMINATION_CRITERIA)
def saveNp(self):
np.save(self.parameterOut + "K_left",self.K_left)
np.save(self.parameterOut + "K_right",self.K_right)
np.save(self.parameterOut + "D_left",self.D_left)
np.save(self.parameterOut + "D_right",self.D_right)
np.save(self.parameterOut + "R",self.R)
np.save(self.parameterOut + "T",self.T)
np.save(self.parameterOut + "rms",self.rms)
VideoReader.py -> 我的助手类
import cv2
class VideoReader(object):
def __init__(self,path):
self.video = cv2.VideoCapture(path)
self.fps = self.video.get(cv2.CAP_PROP_FPS)
self.total_frames = self.video.get(cv2.CAP_PROP_FRAME_COUNT)
self.current_frames = self.video.get(cv2.CAP_PROP_POS_FRAMES)
self.frame = None
self.ret = False
self.windowNames = {}
self.width = None
self.height = None
def __del__(self):
self.video.release()
for name in self.windowNames:
cv2.destroyWindow(name)
def read(self):
self.ret,self.frame = self.video.read()
self.current_frames = self.video.get(cv2.CAP_PROP_POS_FRAMES)
if self.ret:
self.height,self.width,_ = self.frame.shape
return self.ret,self.frame
def progress(self):
percentage = self.current_frames / self.total_frames * 100
return percentage
def duration(self):
duration = self.fps * self.total_frames
return duration
def display(self,windowTxt):
if self.ret:
self.windowNames[windowTxt]=0
if cv2.waitKey(1) & 0xFF == ord('q'):
exit()
cv2.imshow(windowTxt,self.frame)
def getGrayFrame(self):
return cv2.cvtColor(self.frame,cv2.COLOR_BGR2GRAY)
def __version__(self):
return cv2.__version__
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
如果你已经找到好的解决方法，欢迎将解决方案带上本链接一起发送给小编。
小编邮箱:dio#foxmail.com (将#修改为@）