コード例 #1
0
ファイル: textures.py プロジェクト: arielsan99/pytorch3d
 def atlas_packed(self) -> torch.Tensor:
     if self.isempty():
         return torch.zeros(
             (self._N, 0, 0, 3), dtype=torch.float32, device=self.device
         )
     atlas_list = self.atlas_list()
     return list_to_packed(atlas_list)[0]
コード例 #2
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    def test_list_to_packed(self):
        device = torch.device("cuda:0")
        N = 5
        K = 20
        x, x_dims = [], []
        dim2 = torch.randint(K, size=(1, )).item()
        for _ in range(N):
            dim1 = torch.randint(K, size=(1, )).item()
            x_dims.append(dim1)
            x.append(torch.rand([dim1, dim2], device=device))

        out = struct_utils.list_to_packed(x)
        x_packed = out[0]
        num_items = out[1]
        item_packed_first_idx = out[2]
        item_packed_to_list_idx = out[3]

        cur = 0
        for i in range(N):
            self.assertTrue(num_items[i] == x_dims[i])
            self.assertTrue(item_packed_first_idx[i] == cur)
            self.assertTrue(item_packed_to_list_idx[cur:cur +
                                                    x_dims[i]].eq(i).all())
            self.assertClose(x_packed[cur:cur + x_dims[i]], x[i])
            cur += x_dims[i]
コード例 #3
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 def faces_uvs_packed(self) -> torch.Tensor:
     if self.isempty():
         return torch.zeros((self._N, 3),
                            dtype=torch.float32,
                            device=self.device)
     faces_uvs_list = self.faces_uvs_list()
     return list_to_packed(faces_uvs_list)[0]
コード例 #4
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 def verts_uvs_packed(self) -> torch.Tensor:
     if self.isempty():
         return torch.zeros((self._N, 2),
                            dtype=torch.float32,
                            device=self.device)
     verts_uvs_list = self.verts_uvs_list()
     return list_to_packed(verts_uvs_list)[0]
コード例 #5
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def transform_verts_list(verts_list, camera_info):
    """
    input:
    @meshes: verts_list in local frame
    @camera_info: plane params from camera info, type = dict, must contain 'position' and 'rotation' as keys
    output:
    verts_list in global frame.
    """
    tran = camera_info["position"]
    rot = camera_info["rotation"]
    verts_list_to_packed = struct_utils.list_to_packed(verts_list)
    verts_packed = verts_list_to_packed[0]
    num_verts_per_mesh = verts_list_to_packed[1]
    verts_packed = verts_packed * torch.tensor(
        [1.0, -1.0, -1.0], dtype=torch.float32)  # suncg2habitat
    rot_matrix = torch.tensor(quaternion.as_rotation_matrix(rot),
                              dtype=torch.float32)
    verts_packed = torch.mm(rot_matrix, verts_packed.T).T + torch.tensor(
        tran, dtype=torch.float32)
    verts_list = list(verts_packed.split(num_verts_per_mesh.tolist(), dim=0))
    return verts_list