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""" |
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The ray sampler is a module that takes in camera matrices and resolution and batches of rays. |
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Expects cam2world matrices that use the OpenCV camera coordinate system conventions. |
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""" |
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import torch |
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class RaySampler(torch.nn.Module): |
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def __init__(self): |
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super().__init__() |
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self.ray_origins_h, self.ray_directions, self.depths, self.image_coords, self.rendering_options = None, None, None, None, None |
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def forward(self, cam2world_matrix, intrinsics, render_size, crop_size, start_x, start_y): |
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""" |
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Create batches of rays and return origins and directions. |
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cam2world_matrix: (N, 4, 4) |
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intrinsics: (N, 3, 3) |
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render_size: int |
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ray_origins: (N, M, 3) |
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ray_dirs: (N, M, 2) |
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""" |
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N, M = cam2world_matrix.shape[0], crop_size**2 |
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cam_locs_world = cam2world_matrix[:, :3, 3] |
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fx = intrinsics[:, 0, 0] |
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fy = intrinsics[:, 1, 1] |
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cx = intrinsics[:, 0, 2] |
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cy = intrinsics[:, 1, 2] |
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sk = intrinsics[:, 0, 1] |
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uv = torch.stack(torch.meshgrid( |
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torch.arange(render_size, dtype=torch.float32, device=cam2world_matrix.device), |
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torch.arange(render_size, dtype=torch.float32, device=cam2world_matrix.device), |
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indexing='ij', |
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)) |
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if crop_size < render_size: |
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patch_uv = [] |
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for i in range(cam2world_matrix.shape[0]): |
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patch_uv.append(uv.clone()[None, :, start_y:start_y+crop_size, start_x:start_x+crop_size]) |
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uv = torch.cat(patch_uv, 0) |
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uv = uv.flip(1).reshape(cam2world_matrix.shape[0], 2, -1).transpose(2, 1) |
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else: |
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uv = uv.flip(0).reshape(2, -1).transpose(1, 0) |
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uv = uv.unsqueeze(0).repeat(cam2world_matrix.shape[0], 1, 1) |
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x_cam = uv[:, :, 0].view(N, -1) * (1./render_size) + (0.5/render_size) |
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y_cam = uv[:, :, 1].view(N, -1) * (1./render_size) + (0.5/render_size) |
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z_cam = torch.ones((N, M), device=cam2world_matrix.device) |
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x_lift = (x_cam - cx.unsqueeze(-1) + cy.unsqueeze(-1)*sk.unsqueeze(-1)/fy.unsqueeze(-1) - sk.unsqueeze(-1)*y_cam/fy.unsqueeze(-1)) / fx.unsqueeze(-1) * z_cam |
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y_lift = (y_cam - cy.unsqueeze(-1)) / fy.unsqueeze(-1) * z_cam |
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cam_rel_points = torch.stack((x_lift, y_lift, z_cam, torch.ones_like(z_cam)), dim=-1).float() |
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_opencv2blender = torch.tensor([ |
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[1, 0, 0, 0], |
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[0, -1, 0, 0], |
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[0, 0, -1, 0], |
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[0, 0, 0, 1], |
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], dtype=torch.float32, device=cam2world_matrix.device).unsqueeze(0).repeat(N, 1, 1) |
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cam2world_matrix = torch.bmm(cam2world_matrix.float(), _opencv2blender.float()) |
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world_rel_points = torch.bmm(cam2world_matrix.float(), cam_rel_points.permute(0, 2, 1)).permute(0, 2, 1)[:, :, :3] |
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ray_dirs = world_rel_points - cam_locs_world[:, None, :] |
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ray_dirs = torch.nn.functional.normalize(ray_dirs, dim=2) |
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ray_origins = cam_locs_world.unsqueeze(1).repeat(1, ray_dirs.shape[1], 1) |
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return ray_origins, ray_dirs |