Deduplicate texture maps when joining

Summary:
If you join several meshes which have TexturesUV textures using join_meshes_as_scene then we amalgamate all the texture images in to a single one. This now checks if some of the images are equal (i.e. the tensors are the same tensor, in the `is` sense; they have the same `id` in Python) and only uses one copy if they are.

I have an example of a massive scene made of several textured meshes with some shared, where this makes the difference between fitting the data on the GPU and not.

Reviewed By: theschnitz

Differential Revision: D25982364

fbshipit-source-id: a8228805f38475c796302e27328a340d9b56c8ef

pytorch3d/renderer/mesh/textures.py

@@ -10,7 +10,7 @@
 from pytorch3d.structures.utils import list_to_packed, list_to_padded, padded_to_list
 from torch.nn.functional import interpolate
 
-from .utils import pack_rectangles
+from .utils import PackedRectangle, Rectangle, pack_unique_rectangles
 
 
 # This file contains classes and helper functions for texturing.
@@ -1028,14 +1028,13 @@ def join_batch(self, textures: List["TexturesUV"]) -> "TexturesUV":
         maps_list = []
         faces_uvs_list += self.faces_uvs_list()
         verts_uvs_list += self.verts_uvs_list()
-        maps_list += list(self.maps_padded().unbind(0))
+        maps_list += self.maps_list()
         num_faces_per_mesh = self._num_faces_per_mesh
         for tex in textures:
             verts_uvs_list += tex.verts_uvs_list()
             faces_uvs_list += tex.faces_uvs_list()
             num_faces_per_mesh += tex._num_faces_per_mesh
-            tex_map_list = list(tex.maps_padded().unbind(0))
-            maps_list += tex_map_list
+            maps_list += tex.maps_list()
 
         new_tex = self.__class__(
             maps=maps_list,
@@ -1048,10 +1047,7 @@ def join_batch(self, textures: List["TexturesUV"]) -> "TexturesUV":
         return new_tex
 
     def _place_map_into_single_map(
-        self,
-        single_map: torch.Tensor,
-        map_: torch.Tensor,
-        location: Tuple[int, int, bool],  # (x,y) and whether flipped
+        self, single_map: torch.Tensor, map_: torch.Tensor, location: PackedRectangle
     ) -> None:
         """
         Copy map into a larger tensor single_map at the destination specified by location.
@@ -1064,11 +1060,11 @@ def _place_map_into_single_map(
             map_: (H, W, 3) source data
             location: where to place map
         """
-        do_flip = location[2]
+        do_flip = location.flipped
         source = map_.transpose(0, 1) if do_flip else map_
         border_width = 0 if self.align_corners else 1
-        lower_u = location[0] + border_width
-        lower_v = location[1] + border_width
+        lower_u = location.x + border_width
+        lower_v = location.y + border_width
         upper_u = lower_u + source.shape[0]
         upper_v = lower_v + source.shape[1]
         single_map[lower_u:upper_u, lower_v:upper_v] = source
@@ -1102,28 +1098,33 @@ def join_scene(self) -> "TexturesUV":
         If align_corners=False, we need to add an artificial border around
         every map.
 
-        We use the function `pack_rectangles` to provide a layout for the
-        single map. _place_map_into_single_map is used to copy the maps
-        into the single map. The merging of verts_uvs and faces_uvs are
-        handled locally in this function.
+        We use the function `pack_unique_rectangles` to provide a layout for
+        the single map. This means that if self was created with a list of maps,
+        and to() has not been called, and there were two maps which were exactly
+        the same tensor object, then they will become the same data in the unified map.
+        _place_map_into_single_map is used to copy the maps into the single map.
+        The merging of verts_uvs and faces_uvs is handled locally in this function.
         """
         maps = self.maps_list()
         heights_and_widths = []
         extra_border = 0 if self.align_corners else 2
         for map_ in maps:
             heights_and_widths.append(
-                (map_.shape[0] + extra_border, map_.shape[1] + extra_border)
+                Rectangle(
+                    map_.shape[0] + extra_border, map_.shape[1] + extra_border, id(map_)
+                )
             )
-        merging_plan = pack_rectangles(heights_and_widths)
+        merging_plan = pack_unique_rectangles(heights_and_widths)
         # pyre-fixme[16]: `Tensor` has no attribute `new_zeros`.
         single_map = maps[0].new_zeros((*merging_plan.total_size, 3))
         verts_uvs = self.verts_uvs_list()
         verts_uvs_merged = []
 
         for map_, loc, uvs in zip(maps, merging_plan.locations, verts_uvs):
             new_uvs = uvs.clone()
-            self._place_map_into_single_map(single_map, map_, loc)
-            do_flip = loc[2]
+            if loc.is_first:
+                self._place_map_into_single_map(single_map, map_, loc)
+            do_flip = loc.flipped
             x_shape = map_.shape[1] if do_flip else map_.shape[0]
             y_shape = map_.shape[0] if do_flip else map_.shape[1]
 
@@ -1164,9 +1165,9 @@ def join_scene(self) -> "TexturesUV":
             denom_y = merging_plan.total_size[1] - one_if_align
             scale_y = y_shape - one_if_align
             new_uvs[:, 1] *= scale_x / denom_x
-            new_uvs[:, 1] += (loc[0] + one_if_not_align) / denom_x
+            new_uvs[:, 1] += (loc.x + one_if_not_align) / denom_x
             new_uvs[:, 0] *= scale_y / denom_y
-            new_uvs[:, 0] += (loc[1] + one_if_not_align) / denom_y
+            new_uvs[:, 0] += (loc.y + one_if_not_align) / denom_y
 
             verts_uvs_merged.append(new_uvs)
 

pytorch3d/renderer/mesh/utils.py

@@ -64,6 +64,25 @@ def _interpolate_zbuf(
 
 # -----------  Rectangle Packing  -------------------- #
 
+
+class Rectangle(NamedTuple):
+    xsize: int
+    ysize: int
+    identifier: int
+
+
+class PackedRectangle(NamedTuple):
+    x: int
+    y: int
+    flipped: bool
+    is_first: bool
+
+
+class PackedRectangles(NamedTuple):
+    total_size: Tuple[int, int]
+    locations: List[PackedRectangle]
+
+
 # Note the order of members matters here because it determines the queue order.
 # We want to place longer rectangles first.
 class _UnplacedRectangle(NamedTuple):
@@ -74,7 +93,7 @@ class _UnplacedRectangle(NamedTuple):
 
 def _try_place_rectangle(
     rect: _UnplacedRectangle,
-    placed_so_far: List[Tuple[int, int, bool]],
+    placed_so_far: List[PackedRectangle],
     occupied: List[Tuple[int, int]],
 ) -> bool:
     """
@@ -156,10 +175,11 @@ def _try_place_rectangle(
                 current_start_idx = idx
             if currently_packed >= needed_height:
                 current_max_width = max(interval[0], current_max_width)
-                placed_so_far[rect.ind] = (
+                placed_so_far[rect.ind] = PackedRectangle(
                     current_max_width,
                     occupied[current_start_idx - 1][1],
                     rect.flipped,
+                    True,
                 )
                 new_occupied = (
                     current_max_width + rect.size[0],
@@ -182,11 +202,6 @@ def _try_place_rectangle(
     return False
 
 
-class PackedRectangles(NamedTuple):
-    total_size: Tuple[int, int]
-    locations: List[Tuple[int, int, bool]]  # (x,y) and whether flipped
-
-
 def pack_rectangles(sizes: List[Tuple[int, int]]) -> PackedRectangles:
     """
     Naive rectangle packing in to a large rectangle. Flipping (i.e. rotating
@@ -200,7 +215,9 @@ def pack_rectangles(sizes: List[Tuple[int, int]]) -> PackedRectangles:
 
     Returns:
         total_size: size of total large rectangle
-        rectangles: location for each of the input rectangles
+        rectangles: location for each of the input rectangles.
+                    This includes whether they are flipped.
+                    The is_first field is always True.
     """
 
     if len(sizes) < 2:
@@ -213,14 +230,14 @@ def pack_rectangles(sizes: List[Tuple[int, int]]) -> PackedRectangles:
         else:
             queue.append(_UnplacedRectangle((size[0], size[1]), i, False))
     queue.sort()
-    placed_so_far = [(-1, -1, False)] * len(sizes)
+    placed_so_far = [PackedRectangle(-1, -1, False, False)] * len(sizes)
 
     biggest = queue.pop()
     total_width, current_height = biggest.size
-    placed_so_far[biggest.ind] = (0, 0, biggest.flipped)
+    placed_so_far[biggest.ind] = PackedRectangle(0, 0, biggest.flipped, True)
 
     second = queue.pop()
-    placed_so_far[second.ind] = (0, current_height, second.flipped)
+    placed_so_far[second.ind] = PackedRectangle(0, current_height, second.flipped, True)
     current_height += second.size[1]
     occupied = [biggest.size, (second.size[0], current_height)]
 
@@ -236,8 +253,63 @@ def pack_rectangles(sizes: List[Tuple[int, int]]) -> PackedRectangles:
 
         # rect wasn't placed in the current bounding box,
         # so we add extra space to fit it in.
-        placed_so_far[rect.ind] = (0, current_height, rect.flipped)
+        placed_so_far[rect.ind] = PackedRectangle(0, current_height, rect.flipped, True)
         current_height += rect.size[1]
         occupied.append((rect.size[0], current_height))
 
     return PackedRectangles((total_width, current_height), placed_so_far)
+
+
+def pack_unique_rectangles(rectangles: List[Rectangle]) -> PackedRectangles:
+    """
+    Naive rectangle packing in to a large rectangle. Flipping (i.e. rotating
+    a rectangle by 90 degrees) is allowed. Inputs are deduplicated by their
+    identifier.
+
+    This is a wrapper around pack_rectangles, where inputs come with an
+    identifier. In particular, it calls pack_rectangles for the deduplicated inputs,
+    then returns the values for all the inputs. The output for all rectangles with
+    the same identifier will be the same, except that only the first one will have
+    the is_first field True.
+
+    This is used to join several uv maps into a single scene, see
+    TexturesUV.join_scene.
+
+    Args:
+        rectangles: List of sizes of rectangles to pack
+
+    Returns:
+        total_size: size of total large rectangle
+        rectangles: location for each of the input rectangles.
+                    This includes whether they are flipped.
+                    The is_first field is true for the first rectangle
+                    with each identifier.
+    """
+
+    if len(rectangles) < 2:
+        raise ValueError("Cannot pack less than two boxes")
+
+    input_map = {}
+    input_indices: List[Tuple[int, bool]] = []
+    unique_input_sizes: List[Tuple[int, int]] = []
+    for rectangle in rectangles:
+        if rectangle.identifier not in input_map:
+            unique_index = len(unique_input_sizes)
+            unique_input_sizes.append((rectangle.xsize, rectangle.ysize))
+            input_map[rectangle.identifier] = unique_index
+            input_indices.append((unique_index, True))
+        else:
+            unique_index = input_map[rectangle.identifier]
+            input_indices.append((unique_index, False))
+
+    if len(unique_input_sizes) == 1:
+        first = [PackedRectangle(0, 0, False, True)]
+        rest = (len(rectangles) - 1) * [PackedRectangle(0, 0, False, False)]
+        return PackedRectangles(unique_input_sizes[0], first + rest)
+
+    total_size, unique_locations = pack_rectangles(unique_input_sizes)
+    full_locations = []
+    for input_index, first in input_indices:
+        full_locations.append(unique_locations[input_index]._replace(is_first=first))
+
+    return PackedRectangles(total_size, full_locations)

tests/test_render_meshes.py

@@ -652,6 +652,9 @@ def test_join_uvs(self):
         verts_shifted2 = verts.clone()
         verts_shifted2 *= 0.5
         verts_shifted2[:, 1] -= 7
+        verts_shifted3 = verts.clone()
+        verts_shifted3 *= 0.5
+        verts_shifted3[:, 1] -= 700
 
         [faces] = plain_torus.faces_list()
         nocolor = torch.zeros((100, 100), device=device)
@@ -697,7 +700,11 @@ def test_join_uvs(self):
             mesh1 = Meshes(verts=[verts], faces=[faces], textures=textures1)
             mesh2 = Meshes(verts=[verts_shifted1], faces=[faces], textures=textures2)
             mesh3 = Meshes(verts=[verts_shifted2], faces=[faces], textures=textures3)
-            mesh = join_meshes_as_scene([mesh1, mesh2, mesh3])
+            # mesh4 is like mesh1 but outside the field of view. It is here to test
+            # that having another texture with the same map doesn't produce
+            # two copies in the joined map.
+            mesh4 = Meshes(verts=[verts_shifted3], faces=[faces], textures=textures1)
+            mesh = join_meshes_as_scene([mesh1, mesh2, mesh3, mesh4])
 
             output = renderer(mesh)[0, ..., :3].cpu()
             output1 = renderer(mesh1)[0, ..., :3].cpu()

tests/test_texturing.py

@@ -12,7 +12,11 @@
     TexturesUV,
     TexturesVertex,
     _list_to_padded_wrapper,
+)
+from pytorch3d.renderer.mesh.utils import (
+    Rectangle,
     pack_rectangles,
+    pack_unique_rectangles,
 )
 from pytorch3d.structures import Meshes, list_to_packed, packed_to_list
 from test_meshes import init_mesh
@@ -873,21 +877,24 @@ def wrap_pack(self, sizes):
         mask = torch.zeros(total, dtype=torch.bool)
         seen_x_bound = False
         seen_y_bound = False
-        for (in_x, in_y), loc in zip(sizes, res.locations):
-            self.assertGreaterEqual(loc[0], 0)
-            self.assertGreaterEqual(loc[1], 0)
-            placed_x, placed_y = (in_y, in_x) if loc[2] else (in_x, in_y)
-            upper_x = placed_x + loc[0]
-            upper_y = placed_y + loc[1]
+        for (in_x, in_y), (out_x, out_y, flipped, is_first) in zip(
+            sizes, res.locations
+        ):
+            self.assertTrue(is_first)
+            self.assertGreaterEqual(out_x, 0)
+            self.assertGreaterEqual(out_y, 0)
+            placed_x, placed_y = (in_y, in_x) if flipped else (in_x, in_y)
+            upper_x = placed_x + out_x
+            upper_y = placed_y + out_y
             self.assertGreaterEqual(total[0], upper_x)
             if total[0] == upper_x:
                 seen_x_bound = True
             self.assertGreaterEqual(total[1], upper_y)
             if total[1] == upper_y:
                 seen_y_bound = True
-            already_taken = torch.sum(mask[loc[0] : upper_x, loc[1] : upper_y])
+            already_taken = torch.sum(mask[out_x:upper_x, out_y:upper_y])
             self.assertEqual(already_taken, 0)
-            mask[loc[0] : upper_x, loc[1] : upper_y] = 1
+            mask[out_x:upper_x, out_y:upper_y] = 1
         self.assertTrue(seen_x_bound)
         self.assertTrue(seen_y_bound)
 
@@ -930,3 +937,29 @@ def test_random(self):
             for j in range(vals.shape[0]):
                 sizes.append((int(vals[j, 0]), int(vals[j, 1])))
             self.wrap_pack(sizes)
+
+    def test_all_identical(self):
+        sizes = [Rectangle(xsize=61, ysize=82, identifier=1729)] * 3
+        total_size, locations = pack_unique_rectangles(sizes)
+        self.assertEqual(total_size, (61, 82))
+        self.assertEqual(len(locations), 3)
+        for i, (x, y, is_flipped, is_first) in enumerate(locations):
+            self.assertEqual(x, 0)
+            self.assertEqual(y, 0)
+            self.assertFalse(is_flipped)
+            self.assertEqual(is_first, i == 0)
+
+    def test_one_different_id(self):
+        sizes = [Rectangle(xsize=61, ysize=82, identifier=220)] * 3
+        sizes.extend([Rectangle(xsize=61, ysize=82, identifier=284)] * 3)
+        total_size, locations = pack_unique_rectangles(sizes)
+        self.assertEqual(total_size, (82, 122))
+        self.assertEqual(len(locations), 6)
+        for i, (x, y, is_flipped, is_first) in enumerate(locations):
+            self.assertTrue(is_flipped)
+            self.assertEqual(is_first, i % 3 == 0)
+            self.assertEqual(x, 0)
+            if i < 3:
+                self.assertEqual(y, 61)
+            else:
+                self.assertEqual(y, 0)