Save UV texture with obj mesh

Summary: Add functionality to to save an `.obj` file with associated UV textures: `.png` image and `.mtl` file as well as saving verts_uvs and faces_uvs to the `.obj` file.

Reviewed By: bottler

Differential Revision: D29337562

fbshipit-source-id: 86829b40dae9224088b328e7f5a16eacf8582eb5

pytorch3d/io/obj_io.py

@@ -15,6 +15,7 @@ from typing import List, Optional, Union
 import numpy as np
 import torch
 from iopath.common.file_io import PathManager
+from PIL import Image
 from pytorch3d.common.types import Device
 from pytorch3d.io.mtl_io import load_mtl, make_mesh_texture_atlas
 from pytorch3d.io.utils import _check_faces_indices, _make_tensor, _open_file
@@ -649,42 +650,118 @@ def _load_obj(
 
 
 def save_obj(
-    f,
+    f: Union[str, os.PathLike],
     verts,
     faces,
     decimal_places: Optional[int] = None,
     path_manager: Optional[PathManager] = None,
-):
+    *,
+    verts_uvs: Optional[torch.Tensor] = None,
+    faces_uvs: Optional[torch.Tensor] = None,
+    texture_map: Optional[torch.Tensor] = None,
+) -> None:
     """
     Save a mesh to an .obj file.
 
     Args:
-        f: File (or path) to which the mesh should be written.
+        f: File (str or path) to which the mesh should be written.
         verts: FloatTensor of shape (V, 3) giving vertex coordinates.
         faces: LongTensor of shape (F, 3) giving faces.
         decimal_places: Number of decimal places for saving.
         path_manager: Optional PathManager for interpreting f if
             it is a str.
+        verts_uvs: FloatTensor of shape (V, 2) giving the uv coordinate per vertex.
+        faces_uvs: LongTensor of shape (F, 3) giving the index into verts_uvs for
+            each vertex in the face.
+        texture_map: FloatTensor of shape (H, W, 3) representing the texture map
+            for the mesh which will be saved as an image. The values are expected
+            to be in the range [0, 1],
     """
-    if len(verts) and not (verts.dim() == 2 and verts.size(1) == 3):
-        message = "Argument 'verts' should either be empty or of shape (num_verts, 3)."
+    if len(verts) and (verts.dim() != 2 or verts.size(1) != 3):
+        message = "'verts' should either be empty or of shape (num_verts, 3)."
+        raise ValueError(message)
+
+    if len(faces) and (faces.dim() != 2 or faces.size(1) != 3):
+        message = "'faces' should either be empty or of shape (num_faces, 3)."
+        raise ValueError(message)
+
+    if faces_uvs is not None and (faces_uvs.dim() != 2 or faces_uvs.size(1) != 3):
+        message = "'faces_uvs' should either be empty or of shape (num_faces, 3)."
         raise ValueError(message)
 
-    if len(faces) and not (faces.dim() == 2 and faces.size(1) == 3):
-        message = "Argument 'faces' should either be empty or of shape (num_faces, 3)."
+    if verts_uvs is not None and (verts_uvs.dim() != 2 or verts_uvs.size(1) != 2):
+        message = "'verts_uvs' should either be empty or of shape (num_verts, 2)."
+        raise ValueError(message)
+
+    if texture_map is not None and (texture_map.dim() != 3 or texture_map.size(2) != 3):
+        message = "'texture_map' should either be empty or of shape (H, W, 3)."
         raise ValueError(message)
 
     if path_manager is None:
         path_manager = PathManager()
 
+    save_texture = all([t is not None for t in [faces_uvs, verts_uvs, texture_map]])
+    output_path = Path(f)
+
+    # Save the .obj file
     with _open_file(f, path_manager, "w") as f:
-        return _save(f, verts, faces, decimal_places)
+        if save_texture:
+            # Add the header required for the texture info to be loaded correctly
+            obj_header = "\nmtllib {0}.mtl\nusemtl mesh\n\n".format(output_path.stem)
+            f.write(obj_header)
+        _save(
+            f,
+            verts,
+            faces,
+            decimal_places,
+            verts_uvs=verts_uvs,
+            faces_uvs=faces_uvs,
+            save_texture=save_texture,
+        )
+
+    # Save the .mtl and .png files associated with the texture
+    if save_texture:
+        image_path = output_path.with_suffix(".png")
+        mtl_path = output_path.with_suffix(".mtl")
+        if isinstance(f, str):
+            # Back to str for iopath interpretation.
+            image_path = str(image_path)
+            mtl_path = str(mtl_path)
+
+        # Save texture map to output folder
+        # pyre-fixme[16] # undefined attribute cpu
+        texture_map = texture_map.detach().cpu() * 255.0
+        image = Image.fromarray(texture_map.numpy().astype(np.uint8))
+        with _open_file(image_path, path_manager, "wb") as im_f:
+            # pyre-fixme[6] # incompatible parameter type
+            image.save(im_f)
+
+        # Create .mtl file with the material name and texture map filename
+        # TODO: enable material properties to also be saved.
+        with _open_file(mtl_path, path_manager, "w") as f_mtl:
+            lines = f"newmtl mesh\n" f"map_Kd {output_path.stem}.png\n"
+            f_mtl.write(lines)
 
 
 # TODO (nikhilar) Speed up this function.
-def _save(f, verts, faces, decimal_places: Optional[int] = None) -> None:
-    assert not len(verts) or (verts.dim() == 2 and verts.size(1) == 3)
-    assert not len(faces) or (faces.dim() == 2 and faces.size(1) == 3)
+def _save(
+    f,
+    verts,
+    faces,
+    decimal_places: Optional[int] = None,
+    *,
+    verts_uvs: Optional[torch.Tensor] = None,
+    faces_uvs: Optional[torch.Tensor] = None,
+    save_texture: bool = False,
+) -> None:
+
+    if len(verts) and (verts.dim() != 2 or verts.size(1) != 3):
+        message = "'verts' should either be empty or of shape (num_verts, 3)."
+        raise ValueError(message)
+
+    if len(faces) and (faces.dim() != 2 or faces.size(1) != 3):
+        message = "'faces' should either be empty or of shape (num_faces, 3)."
+        raise ValueError(message)
 
     if not (len(verts) or len(faces)):
         warnings.warn("Empty 'verts' and 'faces' arguments provided")
@@ -705,15 +782,42 @@ def _save(f, verts, faces, decimal_places: Optional[int] = None) -> None:
             vert = [float_str % verts[i, j] for j in range(D)]
             lines += "v %s\n" % " ".join(vert)
 
+    if save_texture:
+        if faces_uvs is not None and (faces_uvs.dim() != 2 or faces_uvs.size(1) != 3):
+            message = "'faces_uvs' should either be empty or of shape (num_faces, 3)."
+            raise ValueError(message)
+
+        if verts_uvs is not None and (verts_uvs.dim() != 2 or verts_uvs.size(1) != 2):
+            message = "'verts_uvs' should either be empty or of shape (num_verts, 2)."
+            raise ValueError(message)
+
+        # pyre-fixme[16] # undefined attribute cpu
+        verts_uvs, faces_uvs = verts_uvs.cpu(), faces_uvs.cpu()
+
+        # Save verts uvs after verts
+        if len(verts_uvs):
+            uV, uD = verts_uvs.shape
+            for i in range(uV):
+                uv = [float_str % verts_uvs[i, j] for j in range(uD)]
+                lines += "vt %s\n" % " ".join(uv)
+
     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)]
+            if save_texture:
+                # Format faces as {verts_idx}/{verts_uvs_idx}
+                face = [
+                    "%d/%d" % (faces[i, j] + 1, faces_uvs[i, j] + 1) for j in range(P)
+                ]
+            else:
+                face = ["%d" % (faces[i, j] + 1) for j in range(P)]
+
             if i + 1 < F:
                 lines += "f %s\n" % " ".join(face)
+
             elif i + 1 == F:
                 # No newline at the end of the file.
                 lines += "f %s" % " ".join(face)

tests/common_testing.py

@@ -34,7 +34,7 @@ def get_pytorch3d_dir() -> Path:
 
 
 def load_rgb_image(filename: str, data_dir: Union[str, Path]):
-    filepath = data_dir / filename
+    filepath = os.path.join(data_dir, filename)
     with Image.open(filepath) as raw_image:
         image = torch.from_numpy(np.array(raw_image) / 255.0)
     image = image.to(dtype=torch.float32)