68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
'''
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@ Date: 2020-11-19 11:39:45
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@ Author: Qing Shuai
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@ LastEditors: Qing Shuai
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@ LastEditTime: 2020-11-19 11:50:20
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@ FilePath: /EasyMocap/code/pyfitting/operation.py
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'''
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import torch
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def batch_rodrigues(rot_vecs, epsilon=1e-8, dtype=torch.float32):
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''' Calculates the rotation matrices for a batch of rotation vectors
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Parameters
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----------
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rot_vecs: torch.tensor Nx3
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array of N axis-angle vectors
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Returns
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-------
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R: torch.tensor Nx3x3
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The rotation matrices for the given axis-angle parameters
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'''
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batch_size = rot_vecs.shape[0]
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device = rot_vecs.device
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angle = torch.norm(rot_vecs + 1e-8, dim=1, keepdim=True)
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rot_dir = rot_vecs / angle
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cos = torch.unsqueeze(torch.cos(angle), dim=1)
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sin = torch.unsqueeze(torch.sin(angle), dim=1)
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# Bx1 arrays
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rx, ry, rz = torch.split(rot_dir, 1, dim=1)
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K = torch.zeros((batch_size, 3, 3), dtype=dtype, device=device)
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zeros = torch.zeros((batch_size, 1), dtype=dtype, device=device)
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K = torch.cat([zeros, -rz, ry, rz, zeros, -rx, -ry, rx, zeros], dim=1) \
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.view((batch_size, 3, 3))
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ident = torch.eye(3, dtype=dtype, device=device).unsqueeze(dim=0)
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rot_mat = ident + sin * K + (1 - cos) * torch.bmm(K, K)
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return rot_mat
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def projection(points3d, camera_intri, R=None, T=None, distance=None):
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""" project the 3d points to camera coordinate
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Arguments:
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points3d {Tensor} -- (bn, N, 3)
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camera_intri {Tensor} -- (bn, 3, 3)
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distance {Tensor} -- (bn, 1, 1)
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Returns:
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points2d -- (bn, N, 2)
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"""
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if R is not None:
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Rt = torch.transpose(R, 1, 2)
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points3d = torch.matmul(points3d, Rt) + T
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if distance is None:
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img_points = torch.div(points3d[:, :, :2],
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points3d[:, :, 2:3])
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else:
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img_points = torch.div(points3d[:, :, :2],
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distance)
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camera_mat = camera_intri[:, :2, :2]
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center = torch.transpose(camera_intri[:, :2, 2:3], 1, 2)
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img_points = torch.matmul(img_points, camera_mat.transpose(1, 2)) + center
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# img_points = torch.einsum('bki,bji->bjk', [camera_mat, img_points]) \
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# + center
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return img_points |