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import numpy as np | |
def get_intrinsics(H,W): | |
""" | |
Intrinsics for a pinhole camera model. | |
Assume fov of 55 degrees and central principal point. | |
""" | |
f = 0.5 * W / np.tan(0.5 * 55 * np.pi / 180.0) | |
cx = 0.5 * W | |
cy = 0.5 * H | |
return np.array([[f, 0, cx], | |
[0, f, cy], | |
[0, 0, 1]]) | |
def depth_to_points(depth, R=None, t=None): | |
K = get_intrinsics(depth.shape[1], depth.shape[2]) | |
Kinv = np.linalg.inv(K) | |
if R is None: | |
R = np.eye(3) | |
if t is None: | |
t = np.zeros(3) | |
# M converts from your coordinate to PyTorch3D's coordinate system | |
M = np.eye(3) | |
M[0, 0] = -1.0 | |
M[1, 1] = -1.0 | |
height, width = depth.shape[1:3] | |
x = np.arange(width) | |
y = np.arange(height) | |
coord = np.stack(np.meshgrid(x, y), -1) | |
coord = np.concatenate((coord, np.ones_like(coord)[:, :, [0]]), -1) # z=1 | |
coord = coord.astype(np.float32) | |
# coord = torch.as_tensor(coord, dtype=torch.float32, device=device) | |
coord = coord[None] # bs, h, w, 3 | |
D = depth[:, :, :, None, None] | |
# print(D.shape, Kinv[None, None, None, ...].shape, coord[:, :, :, :, None].shape ) | |
pts3D_1 = D * Kinv[None, None, None, ...] @ coord[:, :, :, :, None] | |
# pts3D_1 live in your coordinate system. Convert them to Py3D's | |
pts3D_1 = M[None, None, None, ...] @ pts3D_1 | |
# from reference to targe tviewpoint | |
pts3D_2 = R[None, None, None, ...] @ pts3D_1 + t[None, None, None, :, None] | |
# pts3D_2 = pts3D_1 | |
# depth_2 = pts3D_2[:, :, :, 2, :] # b,1,h,w | |
return pts3D_2[:, :, :, :3, 0][0] | |
def create_triangles(h, w, mask=None): | |
"""Creates mesh triangle indices from a given pixel grid size. | |
This function is not and need not be differentiable as triangle indices are | |
fixed. | |
Args: | |
h: (int) denoting the height of the image. | |
w: (int) denoting the width of the image. | |
Returns: | |
triangles: 2D numpy array of indices (int) with shape (2(W-1)(H-1) x 3) | |
""" | |
x, y = np.meshgrid(range(w - 1), range(h - 1)) | |
tl = y * w + x | |
tr = y * w + x + 1 | |
bl = (y + 1) * w + x | |
br = (y + 1) * w + x + 1 | |
triangles = np.array([tl, bl, tr, br, tr, bl]) | |
triangles = np.transpose(triangles, (1, 2, 0)).reshape( | |
((w - 1) * (h - 1) * 2, 3)) | |
if mask is not None: | |
mask = mask.reshape(-1) | |
triangles = triangles[mask[triangles].all(1)] | |
return triangles | |