相机标定可以说是计算机视觉/机器视觉的基础，也是面试过程中经常出现的问题。相机标定涉及的知识面很广，成像几何、镜头畸变、单应矩阵、非线性优化等。在双目测距系统中，相机标定能消除畸变，进行立体校正，从而提高视差计算的准确性，这样才能得到精确的深度图。
首先需要准备一张棋盘，如下图所示。对于标定不同测距范围相机所用的棋盘方格宽度会有所不同。对于短焦双目相机（测距范围在20m以内），棋盘中方格的宽度达到20mm即可；对于长焦双目相机（测距范围在40m左右），棋盘中方格的宽度需要尽量大，否则会影响标定的精度，一般至少达到60mm。
尽量拍摄多组照片，这样可以提高标定效果，标定效果的好坏直接影响到测距的精度。对于短焦相机通常拍摄40组照片即可；长焦相机通常会需要更多组照片，标定长焦相机时拍摄了60组。
如果使用的是左右图像拼接1个USB接口输出的双目摄像头，在采集图像时需要注意其图像拼接的顺序，例如我使用的双目摄像头拼接顺序从左至右为右目——左目(不知道是不是都是这么拼接的，还是厂家搞错了），这个问题处理不好可能会导致后面的处理结果都不对，所以这里特别说明一下。
import os
import argparse
import cv2
class StereoCamera(object):
"""采集双目标定图片，按键盘【c】或【s】保存图片"""
def __init__(self, chess_width, chess_height, detect=False):
"""
:param chess_width: chessboard width size，即棋盘格宽方向黑白格子相交点个数，
:param chess_height: chessboard height size，即棋盘格长方向黑白格子相交点个数
:param detect: 是否实时检测棋盘格，方便采集数据
"""
self.chess_width = chess_width
self.chess_height = chess_height
self.detect = detect
self.criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
def detect_chessboard(self, image):
"""检测棋盘格并显示"""
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(gray, (self.chess_width, self.chess_height), None)
if ret:
# 角点精检测
corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), self.criteria)
# Draw and display the corners
image = cv2.drawChessboardCorners(image, (self.chess_width, self.chess_height), corners2, ret)
return image
def capture2(self, left_video, right_video, save_dir):
"""
用于采集双USB连接线的双目摄像头
:param left_video:int or str,左路视频路径或者摄像头ID
:param right_video:int or str,右视频路径或者摄像头ID
:param save_dir: str,保存左右图片的路径
:return:
"""
self.create_file(save_dir)
capL = cv2.VideoCapture(left_video)
capR = cv2.VideoCapture(right_video)
widthL, heightL, numFramesL, fpsL = self.get_video_info(capL)
widthR, heightR, numFramesR, fpsR = self.get_video_info(capR)
print("capL:\n", widthL, heightL, numFramesL, fpsL)
print("capR:\n", widthR, heightR, numFramesR, fpsR)
save_videoL = self.create_file(save_dir, "video", "left_video.avi")
save_videoR = self.create_file(save_dir, "video", "right_video.avi")
writerL = self.get_video_writer(save_videoL, widthL, heightL, fpsL)
writerR = self.get_video_writer(save_videoR, widthR, heightR, fpsR)
i = 0
while True:
isuccessL, frameL = capL.read()
isuccessR, frameR = capR.read()
if not (isuccessL and isuccessR):
print("No more frames")
break
if self.detect:
l = self.detect_chessboard(frameL.copy())
r = self.detect_chessboard(frameR.copy())
else:
l = frameL.copy()
r = frameR.copy()
cv2.imshow('left', l)
cv2.imshow('right', r)
key = cv2.waitKey(10)
if key == ord('q'):
break
elif key == ord('c') or key == ord('s'):
print("save image:{:0=3d}".format(i))
cv2.imwrite(os.path.join(save_dir+"/left", "left_{:0=3d}.png".format(i)), frameL)
cv2.imwrite(os.path.join(save_dir+"/right", "right_{:0=3d}.png".format(i)), frameR)
i += 1
writerL.write(frameL)
writerR.write(frameR)
capL.release()
capR.release()
cv2.destroyAllWindows()
def capture1(self, video, save_dir):
"""
用于采集单USB连接线的双目摄像头(左右摄像头被拼接在同一个视频中显示)
:param video:int or str,视频路径或者摄像头ID
:param save_dir: str,保存左右图片的路径
"""
self.create_file(save_dir)
cap = cv2.VideoCapture(video)
width, height, numFrames, fps = self.get_video_info(cap)
print("capL:\n", width, height, numFrames, fps)
save_videoL = self.create_file(save_dir, "video", "left_video.avi")
save_videoR = self.create_file(save_dir, "video", "right_video.avi")
writerL = self.get_video_writer(save_videoL, int(width / 2), height, fps)
writerR = self.get_video_writer(save_videoR, int(width / 2), height, fps)
i = 0
while True:
isuccess, frame = cap.read()
if not isuccess:
print("No more frames")
break
# 分离左右摄像头
# 注意：需要根据摄像头画面分割左右图像
frameL = frame[:, int(width / 2):, :]
frameR = frame[:, :int(width / 2), :]
if self.detect:
l = self.detect_chessboard(frameL.copy())
r = self.detect_chessboard(frameR.copy())
else:
l = frameL.copy()
r = frameR.copy()
cv2.imshow('left', l)
cv2.imshow('right', r)
key = cv2.waitKey(10)
if key == ord('q'):
break
elif key == ord('c') or key == ord('s'):
print("save image:{:0=3d}".format(i))
cv2.imwrite(os.path.join(save_dir+"/left", "left_{:0=3d}.png".format(i)), frameL)
cv2.imwrite(os.path.join(save_dir+"/right", "right_{:0=3d}.png".format(i)), frameR)
i += 1
writerL.write(frameL)
writerR.write(frameR)
cap.release()
cv2.destroyAllWindows()
@staticmethod
def get_video_info(video_cap):
width = int(video_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(video_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
numFrames = int(video_cap.get(cv2.CAP_PROP_FRAME_COUNT))
fps = int(video_cap.get(cv2.CAP_PROP_FPS))
return width, height, numFrames, fps
@staticmethod
def get_video_writer(save_path, width, height, fps):
if not os.path.exists(os.path.dirname(save_path)):
os.makedirs(os.path.dirname(save_path))
fourcc = cv2.VideoWriter_fourcc(*'XVID')
frameSize = (int(width), int(height))
video_writer = cv2.VideoWriter(save_path, fourcc, fps, frameSize)
print("video:width:{},height:{},fps:{}".format(width, height, fps))
return video_writer
@staticmethod
def create_file(parent_dir, dir1=None, filename=None):
out_path = parent_dir
if dir1:
out_path = os.path.join(parent_dir, dir1)
if not os.path.exists(out_path):
os.makedirs(out_path)
if filename:
out_path = os.path.join(out_path, filename)
return out_path
def get_parser():
width = 12
height = 8
left_video = 0
right_video = -1
save_dir = "data/"
parser = argparse.ArgumentParser(description='Camera calibration')
parser.add_argument('--detect', type=bool, default=True, help='detect corner')
parser.add_argument('--width', type=int, default=width, help='chessboard width size')
parser.add_argument('--height', type=int, default=height, help='chessboard height size')
parser.add_argument('--left_video', type=int, default=left_video, help='left video file or camera ID')
parser.add_argument('--right_video', type=int, default=right_video, help='right video file or camera ID')
parser.add_argument('--save_dir', type=str, default=save_dir, help='YML file to save calibrate matrices')
return parser
if __name__ == '__main__':
args = get_parser().parse_args()
stereo = StereoCamera(args.width, args.height, detect=args.detect)
if args.left_video > -1 and args.right_video > -1:
# 双USB连接线的双目摄像头
stereo.capture2(left_video=args.left_video, right_video=args.right_video, save_dir=args.save_dir)
elif args.left_video > -1:
# 单USB连接线的双目摄像头(左右摄像头被拼接在同一个视频中显示)
stereo.capture1(video=args.left_video, save_dir=args.save_dir)
else:
raise Exception("Error: Check your camera{}".format(args.left_video, args.right_video))
尽量让棋盘占据照片中最多的画面（不小于1\3）
尽量让棋盘格出现在图像中的各个位置（尤其图像的四个角）
拍摄的棋盘图是具有多个角度的（前倾，后倾，左倾，右倾，斜倾等）
拍摄的棋盘图要清晰可辩，最好是在最清晰的范围内拍摄
拍摄照片数量要多一点，推荐20张以上
https://blog.csdn.net/leonardohaig/article/details/81254179
双目标定的目的是获取左右目相机的内参矩阵、畸变向量、旋转矩阵和平移矩阵。除了Matlab的标定工具箱之外，OpenCV同样也实现了张友正标定法，而我们只需要调用相关的函数即可对相机进行标定。
双目相机标定步骤：
retL, cornersL = cv2.findChessboardCorners(ChessImaL,(self.width, self.height), cv2.CALIB_CB_ADAPTIVE_THRESH | cv2.CALIB_CB_FILTER_QUADS) # 提取左图每一张图片的角点
retR, cornersR = cv2.findChessboardCorners(ChessImaR,(self.width, self.height), cv2.CALIB_CB_ADAPTIVE_THRESH | cv2.CALIB_CB_FILTER_QUADS) # 提取右图每一张图片的角点
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
cv2.cornerSubPix(ChessImaL, cornersL, (11, 11), (-1, -1), criteria) # 亚像素精确化，对粗提取的角点进行精确化
cv2.cornerSubPix(ChessImaR, cornersR, (11, 11), (-1, -1), criteria) # 亚像素精确化，对粗提取的角点进行精确化
# 左侧相机单独标定
retL, K1, D1, rvecsL, tvecsL = cv2.calibrateCamera(objpoints,imgpointsL,ChessImaL.shape[::-1], None, None)
# 右侧相机单独标定
retR, K2, D2, rvecsR, tvecsR = cv2.calibrateCamera(objpoints,imgpointsR,ChessImaR.shape[::-1], None, None)
criteria_stereo = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 1e-5)
flags = 0
flags |= cv2.CALIB_FIX_INTRINSIC
# 内参、畸变系数、平移向量、旋转矩阵
retS, K1, D1, K2, D2, R, T, E, F = cv2.stereoCalibrate(objpoints,imgpointsL,imgpointsR,K1,D1,K2,D2,ChessImaR.shape[::-1], criteria_stereo,flags)
我们要注意函数中的flags
CV_CALIB_FIX_INTRINSIC:固定K和D矩阵。这是默认标志。如果你校准好你的相机，那就只求解