- 在 reality capture根目录下calibration.xml文件中添加
<format mask="*.lst" desc="CmpMvs _KRT matrices" writer="cvs" undistortImages="0" undistortPrincipal="0">
<hint type="continue" strId="8351" >Files with the camera matrices will be stored next to the corresponding input file. Do you want to continue?</hint>
<body>$ExportCameras($(imagePath)$(imageName)$(imageExt)
$WriteFile("$(imagePath)$(imageName)_KRT.txt",$(f*scale) 0 $(px*scale+0.5*width) 0
0 $(f*scale) $(py*scale+0.5*height) 0
0 0 1 0
$(R00) $(R01) $(R02) $(tx)
$(R10) $(R11) $(R12) $(ty)
$(R20) $(R21) $(R22) $(tz)))</body>
</format>
- 在RealityCapture中选择
-
alignment
-
export
-
registration
- 下拉框选择CmpMvs _KRT matrices
-
registration
-
export
-
相机参数会保存到
imgname_KRT.txt文件中，每个文件表示一个相机的内参和外参 -
读取示例
class Camera:
def __init__(self, krtfile, name=""):
mat = np.loadtxt(krtfile)
self.K = mat[0:3, 0:3]
self.Rt = mat[3:, :]
self.name = name
@property
def projection(self):
return self.K.dot(self.extrinsics)
@property
def extrinsics(self):
return self.Rt
def project3dpoint(self, point):
point = np.array(point)
assert(point.shape[0] == 3)
projection = np.matmul(self.projection, np.hstack([point, 1]).reshape(4, 1))
projection = projection / projection[-1]
return np.array([int(projection[0]),int(projection[1])])
def readCRKRT(cr_camera_projection):
print("Loading camera projection matrix from " + str(cr_camera_projection))
files = os.listdir(str(cr_camera_projection))
cameras = []
for f in files:
if "_KRT.txt" in f:
cam_proj_file = cr_camera_projection / f
cameras.append(Camera(cam_proj_file, f))
return cameras
from pathlib import *
camerapath = Path("E:\cr_folder")
cameras = readCRKRT(camerapath)
print(cameras[0].K)
print(cameras[0].projection)
点云重投影效果
原图（没有去畸变）
点云重投影
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