npu-yanchi / diff-gaussian-rasterization-for-gsslam Goto Github PK

cam_q_w2c = torch.tensor(Rotation.from_matrix(R).as_quat(), device='cuda:0', requires_grad=True).float()
cam_t_w2c = torch.tensor(T, device='cuda', requires_grad=True).float()
                
cam_info = CameraInfo(uid=i, R=R, T=T, cam_q_w2c=cam_q_w2c, cam_t_w2c=cam_t_w2c , FovY=FovY, FovX=FovX, cx=cx, cy=cy, fx=K_train, fy=K_train, image=image, image_path=image_path, image_name=image_name, width=image.size[0], height=image.size[1])

raster_settings = GaussianRasterizationSettings(
        image_height=int(viewpoint_camera.image_height),
        image_width=int(viewpoint_camera.image_width),
        tanfovx=tanfovx,
        tanfovy=tanfovy,
        bg=bg_color,
        scale_modifier=scaling_modifier,
        viewmatrix=viewmatrix,
        projmatrix=viewpoint_camera.full_proj_transform,
        sh_degree=pc.active_sh_degree,
        campos=viewpoint_camera.camera_center,
        prefiltered=False,
        mapping_mode=False,
        tracking_mode=True,
        debug=False
        )

# Rasterize visible Gaussians to image, obtain their radii (on screen). 
rendered_image, radii, rendered_depth, rendered_alpha, render_depth_var = rasterizer(
        means3D = means3D,
        means2D = means2D,
        shs = shs,
        colors_precomp = colors_precomp, 
        opacities = opacity,
        scales = scales,
        rotations = rotations,
        cov3D_precomp = cov3D_precomp,
        cam_q_w2c = viewpoint_camera.cam_q_w2c,
        cam_t_w2c = viewpoint_camera.cam_t_w2c)