Question for render a scene

[SYSUykLin]

Hello,
I have a mesh. There are floor, wall. However, when my camera ray is parallel with the floor, it can not render floor. For example:

Under the yellow box should be a green floor, but nothing is rendered.
I use the plotly to visual mesh:

Could anyone can help? Thanks

Could it be a problem with the normal vectors? But I have already set cull_backfaces=False in RasterizationSettings.

My code:

        camera = self.set_cameras(width=width, height=height, R=r.unsqueeze(0), T=t.unsqueeze(0), FOV=FOV)
        lights = AmbientLights(device=self.device)

        raster_settings = RasterizationSettings(
            image_size=(height, width),
            blur_radius=0.0,
            cull_backfaces=False,
            faces_per_pixel=100,
        )

        renderer = MeshRenderer(
                                                    rasterizer=MeshRasterizer(
                                                        cameras=camera,
                                                        raster_settings=raster_settings
                                                    ),
                                                    shader=HardGouraudShader(self.device, cameras=camera, lights=lights)
                                                )

        image = renderer(scene_obj_mesh, znear=-10000, zfar=100000.0)

[bottler]

Can you share more code? What is the camera object?

[SYSUykLin]

Thanks for your reply. PerspectiveCameras:

    def set_cameras(self, width, height, R, T, FOV=60):
        # 通过FOV计算相机焦距
       # (width / 2) / x_focal = tan(FOV / 2)
        x_focal = (width / 2) / math.tan(math.radians(FOV / 2))
        y_focal = (height / 2) / math.tan(math.radians(FOV / 2))

        # PerspectiveCamera需要这个参数，我猜应该是相机对应到screen的中心
        principal_point = torch.tensor([height / 2, width / 2], dtype=torch.float32, device=self.device).unsqueeze(0)
        focal_length = torch.tensor([y_focal, x_focal], dtype=torch.float32, device=self.device).unsqueeze(0)
        image_size = torch.tensor([height, width], dtype=torch.float32, device=self.device).unsqueeze(0)

        cameras = PerspectiveCameras(
                                                            device=self.device,
                                                            R=R,
                                                            T=T,
                                                            principal_point=principal_point,
                                                            focal_length=focal_length,
                                                            in_ndc=False,
                                                            image_size=image_size
                                                          )

        return cameras

[SYSUykLin]

Thanks for your reply. PerspectiveCameras:

    def set_cameras(self, width, height, R, T, FOV=60):
        # 通过FOV计算相机焦距
       # (width / 2) / x_focal = tan(FOV / 2)
        x_focal = (width / 2) / math.tan(math.radians(FOV / 2))
        y_focal = (height / 2) / math.tan(math.radians(FOV / 2))

        # PerspectiveCamera需要这个参数，我猜应该是相机对应到screen的中心
        principal_point = torch.tensor([height / 2, width / 2], dtype=torch.float32, device=self.device).unsqueeze(0)
        focal_length = torch.tensor([y_focal, x_focal], dtype=torch.float32, device=self.device).unsqueeze(0)
        image_size = torch.tensor([height, width], dtype=torch.float32, device=self.device).unsqueeze(0)

        cameras = PerspectiveCameras(
                                                            device=self.device,
                                                            R=R,
                                                            T=T,
                                                            principal_point=principal_point,
                                                            focal_length=focal_length,
                                                            in_ndc=False,
                                                            image_size=image_size
                                                          )

        return cameras

1. Additionally, when my cameras is not parallel with the floor, it can render the floor. For example:
   
2. I did not provide the normal, this is the way what I load mesh:

def load_mesh_pytorch3d(file_path):
   verts, faces_idx, aux = load_obj(file_path)
   faces = faces_idx.verts_idx
   vertices_color = load_mesh_vertices_color(file_path)
   vertices_color = vertices_color[None] / 255

   textures = TexturesVertex(verts_features=vertices_color)

   mesh = Meshes(verts=[verts], faces=[faces], textures=textures)
   return mesh

[bottler]

Is the floor made of a few very large faces? Playing with cull_to_frustrum might help. Also might be worth trying with bin_size=0 in the RasterizationSettings.

[SYSUykLin]

Is the floor made of a few very large faces? Playing with cull_to_frustrum might help. Also might be worth trying with bin_size=0 in the RasterizationSettings.

Yes, the floor is a square which made of two big triangles.

[bottler]

I don't think I can help further.

[SYSUykLin]

I don't think I can help further.
Could you explain what 'play with cull_to_frustrum ' means? I noticed that this variable seems to only have True or False values. Thanks.

[SYSUykLin]

I solve this problem!!!!!!!
Share my experience：
1）If you use the PerspectiveCamera and custom rotation matrix and translation matrix, it's different from the blender. In blender, the R is the three basis of camera coordinate, T is the location of the camera. But in pytorch3d, the [R, T] is the w2c，so the R is $R^T$, and T is $-R^T T$.
2）In pytorch3d，the matrix is on the right side, it mean $C = X*M$, M is matrix, so the matrix is raw list. If u use the custom rotation, u should feed the $R$ not $R^T$.
3）If the face can not render, the face is to large. subdevide face follow code:

    mesh = Meshes(verts=[verts], faces=[faces], textures=textures)

    # face太大，渲染不出来的，需要subdivide mesh才能把地面渲染出来。
    subdivide_time = 3
    for t in range(subdivide_time):
        subdivide_mesh = SubdivideMeshes(mesh)
        mesh, vertices_color = subdivide_mesh(mesh, feats=vertices_color)
        textures = TexturesVertex(verts_features=vertices_color)
        mesh.textures = textures

@bottler Thank you for the reminder！！