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import torch |
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import math |
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import numpy as np |
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from typing import NamedTuple |
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class BasicPointCloud(NamedTuple): |
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points : np.array |
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colors : np.array |
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normals : np.array |
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def geom_transform_points(points, transf_matrix): |
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P, _ = points.shape |
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ones = torch.ones(P, 1, dtype=points.dtype, device=points.device) |
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points_hom = torch.cat([points, ones], dim=1) |
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points_out = torch.matmul(points_hom, transf_matrix.unsqueeze(0)) |
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denom = points_out[..., 3:] + 0.0000001 |
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return (points_out[..., :3] / denom).squeeze(dim=0) |
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def getWorld2View(R, t): |
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Rt = np.zeros((4, 4)) |
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Rt[:3, :3] = R.transpose() |
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Rt[:3, 3] = t |
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Rt[3, 3] = 1.0 |
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return np.float32(Rt) |
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def getWorld2View2(R, t, translate=np.array([.0, .0, .0]), scale=1.0): |
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Rt = np.zeros((4, 4)) |
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Rt[:3, :3] = R.transpose() |
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Rt[:3, 3] = t |
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Rt[3, 3] = 1.0 |
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C2W = np.linalg.inv(Rt) |
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cam_center = C2W[:3, 3] |
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cam_center = (cam_center + translate) * scale |
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C2W[:3, 3] = cam_center |
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Rt = np.linalg.inv(C2W) |
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return np.float32(Rt) |
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def getView2World(R, t, translate=np.array([.0, .0, .0]), scale=1.0): |
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Rt = np.zeros((4, 4)) |
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Rt[:3, :3] = R.transpose() |
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Rt[:3, 3] = t |
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Rt[3, 3] = 1.0 |
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C2W = np.linalg.inv(Rt) |
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cam_center = C2W[:3, 3] |
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cam_center = (cam_center + translate) * scale |
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C2W[:3, 3] = cam_center |
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Rt = C2W |
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return np.float32(Rt) |
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def getProjectionMatrix(znear, zfar, fovX, fovY): |
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tanHalfFovY = math.tan((fovY / 2)) |
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tanHalfFovX = math.tan((fovX / 2)) |
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top = tanHalfFovY * znear |
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bottom = -top |
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right = tanHalfFovX * znear |
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left = -right |
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P = torch.zeros(4, 4) |
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z_sign = 1.0 |
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P[0, 0] = 2.0 * znear / (right - left) |
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P[1, 1] = 2.0 * znear / (top - bottom) |
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P[0, 2] = (right + left) / (right - left) |
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P[1, 2] = (top + bottom) / (top - bottom) |
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P[3, 2] = z_sign |
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P[2, 2] = z_sign * zfar / (zfar - znear) |
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P[2, 3] = -(zfar * znear) / (zfar - znear) |
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return P |
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def fov2focal(fov, pixels): |
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return pixels / (2 * math.tan(fov / 2)) |
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def focal2fov(focal, pixels): |
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return 2*math.atan(pixels/(2*focal)) |