问题描述
我正在尝试校准来自 Waveshare IMX219-83 立体相机的图像。 未失真的图像不正确，我无法理解为什么它不起作用。 图像是 3280 × 2464，但我保存的 numpy 地图的长度都是 2464，这对我来说似乎很奇怪。
校准代码：
import cv2
import numpy as np
import glob
from tqdm import tqdm
chessboard_size = (6,9)
obj_points = []
img_points_l = []
img_points_r = []
objp = np.zeros((np.prod(chessboard_size),3),dtype=np.float32)
objp[:,:2] = np.mgrid[0:chessboard_size[0],0:chessboard_size[1]].T.reshape(-1,2)
calib_paths_left = sorted(glob.glob('./calib/left/*'))
calib_paths_right = sorted(glob.glob('./calib/right/*'))
print(calib_paths_left)
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,30,0.001)
for i in tqdm(list(range(len(calib_paths_left)))[0::1]):
image_l = cv2.imread(calib_paths_left[i])
image_r = cv2.imread(calib_paths_right[i])
gray_image_l = cv2.cvtColor(image_l,cv2.COLOR_BGR2GRAY)
gray_image_r = cv2.cvtColor(image_r,cv2.COLOR_BGR2GRAY)
print("Images loaded,Analizying...")
ret_l,corners_l = cv2.findChessboardCorners(gray_image_l,chessboard_size,None)
ret_r,corners_r = cv2.findChessboardCorners(gray_image_r,None)
if ret_l and ret_r:
print("Chessboard detected on both images!")
print(calib_paths_left[i] + " and " + calib_paths_right[i])
obj_points.append(objp)
corners_fine_l = cv2.cornerSubPix(gray_image_l,corners_l,(11,11),(-1,-1),criteria)
corners_fine_r = cv2.cornerSubPix(gray_image_r,corners_r,criteria)
img_points_l.append(corners_fine_l)
img_points_r.append(corners_fine_r)
output_l = image_l.copy()
output_r = image_r.copy()
cv2.drawChessboardCorners(output_l,(6,9),corners_fine_l,ret_l)
cv2.drawChessboardCorners(output_r,corners_fine_r,ret_r)
cv2.imshow('corners_fine_l',output_l)
cv2.imshow('corners_fine_r',output_r)
cv2.waitKey(500)
cv2.destroyAllWindows()
# Calibrate cameras individually (undistort)
ret_l,mtx_l,dist_l,rvecs_l,tvecs_l = cv2.calibrateCamera(
obj_points,img_points_l,gray_image_l.shape[::-1],None,None)
h_l,w_l= gray_image_l.shape[:2]
new_mtx_l,roi_l= cv2.getoptimalNewCameraMatrix(mtx_l,(w_l,h_l),1,h_l))
ret_r,mtx_r,dist_r,rvecs_r,tvecs_r = cv2.calibrateCamera(
obj_points,img_points_r,gray_image_r.shape[::-1],None)
h_r,w_r= gray_image_l.shape[:2]
new_mtx_r,roi_r= cv2.getoptimalNewCameraMatrix(mtx_r,(w_r,h_r),h_r))
# Calibrate cameras as stereocamera
flags = 0
flags |= cv2.CALIB_FIX_INTRINSIC
criteria_stereo= (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,0.001)
retval_stereo,new_mtx_l,new_mtx_r,rot,trans,emat,fmat = cv2.stereoCalibrate(
obj_points,criteria_stereo,flags)
rectify_scale= 1
rect_l,rect_r,proj_mat_l,proj_mat_r,Q,roi_l,roi_r= cv2.stereoRectify(
new_mtx_l,rectify_scale,(0,0))
Left_Stereo_Map= cv2.initUndistortRectifyMap(new_mtx_l,rect_l,cv2.CV_16SC2)
Right_Stereo_Map= cv2.initUndistortRectifyMap(new_mtx_r,cv2.CV_16SC2)
print("Saving parameters ......")
np.save("camera_params/Left_Stereo_Map_x",Left_Stereo_Map[0])
np.save("camera_params/Left_Stereo_Map_y",Left_Stereo_Map[1])
np.save("camera_params/Right_Stereo_Map_x",Right_Stereo_Map[0])
np.save("camera_params/Right_Stereo_Map_y",Right_Stereo_Map[1])
重新映射图像，显示不良结果
import cv2
import numpy as np
Left_Stereo_Map_x = np.load("camera_params/Left_Stereo_Map_x.npy")
Left_Stereo_Map_y = np.load("camera_params/Left_Stereo_Map_y.npy")
Right_Stereo_Map_x = np.load("camera_params/Right_Stereo_Map_x.npy")
Right_Stereo_Map_y = np.load("camera_params/Right_Stereo_Map_y.npy")
image_l = cv2.imread("calib/left/frame_l_30.jpg")
image_r = cv2.imread("calib/right/frame_r_30.jpg")
gray_image_l = cv2.cvtColor(image_l,cv2.COLOR_BGR2GRAY)
gray_image_r = cv2.cvtColor(image_r,cv2.COLOR_BGR2GRAY)
cv2.imshow("Left image before rectification",gray_image_l)
cv2.imshow("Right image before rectification",gray_image_r)
image_l_undist = cv2.remap(image_l,Left_Stereo_Map_x,Left_Stereo_Map_y,cv2.INTER_lanczos4,cv2.BORDER_CONSTANT,0)
image_r_undist = cv2.remap(image_r,Right_Stereo_Map_x,Right_Stereo_Map_y,0)
cv2.imshow("Left image after rectification",image_l_undist)
cv2.imshow("Right image after rectification",image_r_undist)
cv2.waitKey(0)
这些是我校准的图像类型：
example left image for calibration
example right image for calibration
这是我得到的输出：
我现在检查了很多次代码，但无法理解为什么它不起作用。
解决方法
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