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ForrestPi avatar ForrestPi commented on May 11, 2024

yeah I have similar question. I want camera parameters as input tensor . How to realize it ?

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hzhao1997 avatar hzhao1997 commented on May 11, 2024

the same question.

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ShichenLiu avatar ShichenLiu commented on May 11, 2024

Hi @hzhao1997 , you can use the projection transform module here:

class Projection(Transform):
def __init__(self, P, dist_coeffs=None, orig_size=512):
super().__init__()
'''
Calculate projective transformation of vertices given a projection matrix
P: 3x4 projection matrix
dist_coeffs: vector of distortion coefficients
orig_size: original size of image captured by the camera
'''
self.P = P
self.dist_coeffs = dist_coeffs
self.orig_size = orig_size
if isinstance(self.P, np.ndarray):
self.P = torch.from_numpy(self.P).cuda()
if self.P is None or self.P.ndimension() != 3 or self.P.shape[1] != 3 or self.P.shape[2] != 4:
raise ValueError('You need to provide a valid (batch_size)x3x4 projection matrix')
if dist_coeffs is None:
self.dist_coeffs = torch.cuda.FloatTensor([[0., 0., 0., 0., 0.]]).repeat(self.P.shape[0], 1)

P is the extrinsic parameters and orig_size is the image size.

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