Fix saving / loading empty OBJ files

Summary:
OBJ files without vertices or faces should be allowed:
- an OBJ with only vertices can represent a point cloud
- an OBJ without any vertex or face is just empty
- an OBJ with faces referencing inexistent vertices has invalid data

Reviewed By: gkioxari

Differential Revision: D20392526

fbshipit-source-id: e72c846ff1e5787fb11d527af3fefa261f9eb0ee

pytorch3d/io/obj_io.py

@@ -15,6 +15,17 @@ from PIL import Image
 from pytorch3d.structures import Meshes, Textures, join_meshes
 
 
+def _make_tensor(data, cols: int, dtype: torch.dtype) -> torch.Tensor:
+    """
+    Return a 2D tensor with the specified cols and dtype filled with data,
+    even when data is empty.
+    """
+    if not data:
+        return torch.zeros((0, cols), dtype=dtype)
+
+    return torch.tensor(data, dtype=dtype)
+
+
 def _read_image(file_name: str, format=None):
     """
     Read an image from a file using Pillow.
@@ -61,7 +72,7 @@ def _format_faces_indices(faces_indices, max_index):
     Raises:
         ValueError if indices are not in a valid range.
     """
-    faces_indices = torch.tensor(faces_indices, dtype=torch.int64)
+    faces_indices = _make_tensor(faces_indices, cols=3, dtype=torch.int64)
 
     # Change to 0 based indexing.
     faces_indices[(faces_indices > 0)] -= 1
@@ -70,10 +81,8 @@ def _format_faces_indices(faces_indices, max_index):
     faces_indices[(faces_indices < 0)] += max_index
 
     # Check indices are valid.
-    if not (
-        torch.all(faces_indices < max_index) and torch.all(faces_indices >= 0)
-    ):
-        raise ValueError("Faces have invalid indices.")
+    if torch.any(faces_indices >= max_index) or torch.any(faces_indices < 0):
+        warnings.warn("Faces have invalid indices")
 
     return faces_indices
 
@@ -333,7 +342,7 @@ def _load(f_obj, data_dir, load_textures=True):
 
     # startswith expects each line to be a string. If the file is read in as
     # bytes then first decode to strings.
-    if isinstance(lines[0], bytes):
+    if lines and isinstance(lines[0], bytes):
         lines = [l.decode("utf-8") for l in lines]
 
     for line in lines:
@@ -380,9 +389,9 @@ def _load(f_obj, data_dir, load_textures=True):
                 faces_materials_idx,
             )
 
-    verts = torch.tensor(verts)  # (V, 3)
-    normals = torch.tensor(normals)  # (N, 3)
-    verts_uvs = torch.tensor(verts_uvs)  # (T, 3)
+    verts = _make_tensor(verts, cols=3, dtype=torch.float32)  # (V, 3)
+    normals = _make_tensor(normals, cols=3, dtype=torch.float32)  # (N, 3)
+    verts_uvs = _make_tensor(verts_uvs, cols=2, dtype=torch.float32)  # (T, 2)
 
     faces_verts_idx = _format_faces_indices(faces_verts_idx, verts.shape[0])
 
@@ -544,23 +553,39 @@ def save_obj(f, verts, faces, decimal_places: Optional[int] = None):
 
 # TODO (nikhilar) Speed up this function.
 def _save(f, verts, faces, decimal_places: Optional[int] = None):
-    if verts.dim() != 2 or verts.size(1) != 3:
-        raise ValueError("Argument 'verts' should be of shape (num_verts, 3).")
-    if faces.dim() != 2 or faces.size(1) != 3:
-        raise ValueError("Argument 'faces' should be of shape (num_faces, 3).")
+    if not (len(verts) or len(faces)):
+        warnings.warn("Empty 'verts' and 'faces' arguments provided")
+        return
+
+    if len(verts) and not (verts.dim() == 2 and verts.size(1) == 3):
+        raise ValueError(
+            "Argument 'verts' should either be empty or of shape (num_verts, 3)."
+        )
+
+    if len(faces) and not (faces.dim() == 2 and faces.size(1) == 3):
+        raise ValueError(
+            "Argument 'faces' should either be empty or of shape (num_faces, 3)."
+        )
+
     verts, faces = verts.cpu(), faces.cpu()
 
+    lines = ""
+
+    if len(verts):
         if decimal_places is None:
             float_str = "%f"
         else:
             float_str = "%" + ".%df" % decimal_places
 
-    lines = ""
         V, D = verts.shape
         for i in range(V):
             vert = [float_str % verts[i, j] for j in range(D)]
             lines += "v %s\n" % " ".join(vert)
 
+    if torch.any(faces >= verts.shape[0]) or torch.any(faces < 0):
+        warnings.warn("Faces have invalid indices")
+
+    if len(faces):
         F, P = faces.shape
         for i in range(F):
             face = ["%d" % (faces[i, j] + 1) for j in range(P)]

tests/test_obj_io.py

@@ -277,9 +277,8 @@ class TestMeshObjIO(TestCaseMixin, unittest.TestCase):
         )
         obj_file = StringIO(obj_file)
 
-        with self.assertRaises(ValueError) as err:
+        with self.assertWarnsRegex(UserWarning, "Faces have invalid indices"):
             load_obj(obj_file)
-        self.assertTrue("Faces have invalid indices." in str(err.exception))
 
     def test_load_obj_error_invalid_normal_indices(self):
         obj_file = "\n".join(
@@ -295,9 +294,8 @@ class TestMeshObjIO(TestCaseMixin, unittest.TestCase):
         )
         obj_file = StringIO(obj_file)
 
-        with self.assertRaises(ValueError) as err:
+        with self.assertWarnsRegex(UserWarning, "Faces have invalid indices"):
             load_obj(obj_file)
-        self.assertTrue("Faces have invalid indices." in str(err.exception))
 
     def test_load_obj_error_invalid_texture_indices(self):
         obj_file = "\n".join(
@@ -313,9 +311,87 @@ class TestMeshObjIO(TestCaseMixin, unittest.TestCase):
         )
         obj_file = StringIO(obj_file)
 
-        with self.assertRaises(ValueError) as err:
+        with self.assertWarnsRegex(UserWarning, "Faces have invalid indices"):
             load_obj(obj_file)
-        self.assertTrue("Faces have invalid indices." in str(err.exception))
+
+    def test_save_obj_invalid_shapes(self):
+        # Invalid vertices shape
+        with self.assertRaises(ValueError) as error:
+            verts = torch.FloatTensor([[0.1, 0.2, 0.3, 0.4]])  # (V, 4)
+            faces = torch.LongTensor([[0, 1, 2]])
+            save_obj(StringIO(), verts, faces)
+        expected_message = "Argument 'verts' should either be empty or of shape (num_verts, 3)."
+        self.assertTrue(expected_message, error.exception)
+
+        # Invalid faces shape
+        with self.assertRaises(ValueError) as error:
+            verts = torch.FloatTensor([[0.1, 0.2, 0.3]])
+            faces = torch.LongTensor([[0, 1, 2, 3]])  # (F, 4)
+            save_obj(StringIO(), verts, faces)
+        expected_message = "Argument 'faces' should either be empty or of shape (num_faces, 3)."
+        self.assertTrue(expected_message, error.exception)
+
+    def test_save_obj_invalid_indices(self):
+        message_regex = "Faces have invalid indices"
+        verts = torch.FloatTensor([[0.1, 0.2, 0.3]])
+        faces = torch.LongTensor([[0, 1, 2]])
+        with self.assertWarnsRegex(UserWarning, message_regex):
+            save_obj(StringIO(), verts, faces)
+
+        faces = torch.LongTensor([[-1, 0, 1]])
+        with self.assertWarnsRegex(UserWarning, message_regex):
+            save_obj(StringIO(), verts, faces)
+
+    def _test_save_load(self, verts, faces):
+        f = StringIO()
+        save_obj(f, verts, faces)
+        f.seek(0)
+        expected_verts, expected_faces = verts, faces
+        if not len(expected_verts):  # Always compare with a (V, 3) tensor
+            expected_verts = torch.zeros(size=(0, 3), dtype=torch.float32)
+        if not len(expected_faces):  # Always compare with an (F, 3) tensor
+            expected_faces = torch.zeros(size=(0, 3), dtype=torch.int64)
+        actual_verts, actual_faces, _ = load_obj(f)
+        self.assertClose(expected_verts, actual_verts)
+        self.assertClose(expected_faces, actual_faces.verts_idx)
+
+    def test_empty_save_load_obj(self):
+        # Vertices + empty faces
+        verts = torch.FloatTensor([[0.1, 0.2, 0.3]])
+        faces = torch.LongTensor([])
+        self._test_save_load(verts, faces)
+
+        faces = torch.zeros(size=(0, 3), dtype=torch.int64)
+        self._test_save_load(verts, faces)
+
+        # Faces + empty vertices
+        message_regex = "Faces have invalid indices"
+        verts = torch.FloatTensor([])
+        faces = torch.LongTensor([[0, 1, 2]])
+        with self.assertWarnsRegex(UserWarning, message_regex):
+            self._test_save_load(verts, faces)
+
+        verts = torch.zeros(size=(0, 3), dtype=torch.float32)
+        with self.assertWarnsRegex(UserWarning, message_regex):
+            self._test_save_load(verts, faces)
+
+        # Empty vertices + empty faces
+        message_regex = "Empty 'verts' and 'faces' arguments provided"
+        verts0 = torch.FloatTensor([])
+        faces0 = torch.LongTensor([])
+        with self.assertWarnsRegex(UserWarning, message_regex):
+            self._test_save_load(verts0, faces0)
+
+        faces3 = torch.zeros(size=(0, 3), dtype=torch.int64)
+        with self.assertWarnsRegex(UserWarning, message_regex):
+            self._test_save_load(verts0, faces3)
+
+        verts3 = torch.zeros(size=(0, 3), dtype=torch.float32)
+        with self.assertWarnsRegex(UserWarning, message_regex):
+            self._test_save_load(verts3, faces0)
+
+        with self.assertWarnsRegex(UserWarning, message_regex):
+            self._test_save_load(verts3, faces3)
 
     def test_save_obj(self):
         verts = torch.tensor(
@@ -410,7 +486,7 @@ class TestMeshObjIO(TestCaseMixin, unittest.TestCase):
             ]
         )
         obj_file = StringIO(obj_file)
-        with self.assertWarnsRegex(Warning, "No mtl file provided"):
+        with self.assertWarnsRegex(UserWarning, "No mtl file provided"):
             verts, faces, aux = load_obj(obj_file)
 
         expected_verts = torch.tensor(
@@ -434,7 +510,7 @@ class TestMeshObjIO(TestCaseMixin, unittest.TestCase):
         DATA_DIR = Path(__file__).resolve().parent / "data"
         obj_filename = "missing_files_obj/model.obj"
         filename = os.path.join(DATA_DIR, obj_filename)
-        with self.assertWarnsRegex(Warning, "Texture file does not exist"):
+        with self.assertWarnsRegex(UserWarning, "Texture file does not exist"):
             verts, faces, aux = load_obj(filename)
 
         expected_verts = torch.tensor(
@@ -475,7 +551,7 @@ class TestMeshObjIO(TestCaseMixin, unittest.TestCase):
         DATA_DIR = Path(__file__).resolve().parent / "data"
         obj_filename = "missing_files_obj/model2.obj"
         filename = os.path.join(DATA_DIR, obj_filename)
-        with self.assertWarnsRegex(Warning, "Mtl file does not exist"):
+        with self.assertWarnsRegex(UserWarning, "Mtl file does not exist"):
             verts, faces, aux = load_obj(filename)
 
         expected_verts = torch.tensor(