code: # Copyright (c) Facebook, Inc. and its affiliates.
  # All rights reserved.
  #
  # This source code is licensed under the BSD-style license found in the
  # LICENSE file in the root directory of this source tree.
  
  
  """
  This module implements loading meshes from glTF 2 assets stored in a
  GLB container file or a glTF JSON file with embedded binary data.
  It is experimental.
  
  The module provides a MeshFormatInterpreter called
  MeshGlbFormat which must be used explicitly.
  e.g.
  
  .. code-block:: python
  
      from pytorch3d.io import IO
      from pytorch3d.io.experimental_gltf_io import MeshGlbFormat
  
      io = IO()
      io.register_meshes_format(MeshGlbFormat())
      io.load_mesh(...)
  
  This implementation is quite restricted in what it supports.
  
      - It does not try to validate the input against the standard.
      - It loads the default scene only.
      - Only triangulated geometry is supported.
      - The geometry of all meshes of the entire scene is aggregated into a single mesh.
        Use `load_meshes()` instead to get un-aggregated (but transformed) ones.
      - All material properties are ignored except for either vertex color, baseColorTexture
        or baseColorFactor. If available, one of these (in this order) is exclusively
        used which does not match the semantics of the standard.
  """
  
  import json
  import struct
  import warnings
  from base64 import b64decode
  from collections import deque
  from enum import IntEnum
  from io import BytesIO
  from typing import Any, BinaryIO, Dict, List, Optional, Tuple, Union, cast
  
  import numpy as np
  import torch
  from iopath.common.file_io import PathManager
  from PIL import Image
  from pytorch3d.io.utils import PathOrStr, _open_file
  from pytorch3d.renderer.mesh import TexturesBase, TexturesUV, TexturesVertex
  from pytorch3d.structures import Meshes, join_meshes_as_scene
  from pytorch3d.transforms import Transform3d, quaternion_to_matrix
  
  from .pluggable_formats import MeshFormatInterpreter, endswith
  
  
  _GLTF_MAGIC = 0x46546C67
  _JSON_CHUNK_TYPE = 0x4E4F534A
  _BINARY_CHUNK_TYPE = 0x004E4942
  _DATA_URI_PREFIX = "data:application/octet-stream;base64,"
  
  
  class _PrimitiveMode(IntEnum):
      POINTS = 0
      LINES = 1
      LINE_LOOP = 2
      LINE_STRIP = 3
      TRIANGLES = 4
      TRIANGLE_STRIP = 5
      TRIANGLE_FAN = 6
  
  
  class _ComponentType(IntEnum):
      BYTE = 5120
      UNSIGNED_BYTE = 5121
      SHORT = 5122
      UNSIGNED_SHORT = 5123
      UNSIGNED_INT = 5125
      FLOAT = 5126
  
  
  _ITEM_TYPES: Dict[int, Any] = {
      5120: np.int8,
      5121: np.uint8,
      5122: np.int16,
      5123: np.uint16,
      5125: np.uint32,
      5126: np.float32,
  }
  
  
  _ElementShape = Union[Tuple[int], Tuple[int, int]]
  _ELEMENT_SHAPES: Dict[str, _ElementShape] = {
      "SCALAR": (1,),
      "VEC2": (2,),
      "VEC3": (3,),
      "VEC4": (4,),
      "MAT2": (2, 2),
      "MAT3": (3, 3),
      "MAT4": (4, 4),
  }
  
  
  def _read_header(stream: BinaryIO) -> Optional[Tuple[int, int]]:
      header = stream.read(12)
      magic, version, length = struct.unpack("<III", header)
  
      if magic != _GLTF_MAGIC:
          return None
  
      return version, length
  
  
  def _read_chunks(
      stream: BinaryIO, length: int
  ) -> Optional[Tuple[Dict[str, Any], np.ndarray]]:
      """
      Get the json header and the binary data from a
      GLB file.
      """
      json_data = None
      binary_data = None
  
      while stream.tell() < length:
          chunk_header = stream.read(8)
          chunk_length, chunk_type = struct.unpack("<II", chunk_header)
          chunk_data = stream.read(chunk_length)
          if chunk_type == _JSON_CHUNK_TYPE:
              json_data = json.loads(chunk_data)
          elif chunk_type == _BINARY_CHUNK_TYPE:
              binary_data = chunk_data
          else:
              warnings.warn("Unsupported chunk type")
              return None
  
      if json_data is None:
          raise ValueError("Missing json header")
  
      if binary_data is not None:
          binary_data = np.frombuffer(binary_data, dtype=np.uint8)
  
      return json_data, binary_data
  
  
  def _make_node_transform(node: Dict[str, Any]) -> Transform3d:
      """
      Convert a transform from the json data in to a PyTorch3D
      Transform3d format.
      """
      array = node.get("matrix")
      if array is not None:  # Stored in column-major order
          M = np.array(array, dtype=np.float32).reshape(4, 4, order="F")
          return Transform3d(matrix=torch.from_numpy(M))
  
      out = Transform3d()
  
      # Given some of (scale/rotation/translation), we do them in that order to
      # get points in to the world space.
      # See https://github.com/KhronosGroup/glTF/issues/743 .
  
      array = node.get("scale", None)
      if array is not None:
          scale_vector = torch.FloatTensor(array)
          out = out.scale(scale_vector[None])
  
      # Rotation quaternion (x, y, z, w) where w is the scalar
      array = node.get("rotation", None)
      if array is not None:
          x, y, z, w = array
          # We negate w. This is equivalent to inverting the rotation.
          # This is needed as quaternion_to_matrix makes a matrix which
          # operates on column vectors, whereas Transform3d wants a
          # matrix which operates on row vectors.
          rotation_quaternion = torch.FloatTensor([-w, x, y, z])
          rotation_matrix = quaternion_to_matrix(rotation_quaternion)
          out = out.rotate(R=rotation_matrix)
  
      array = node.get("translation", None)
      if array is not None:
          translation_vector = torch.FloatTensor(array)
          out = out.translate(x=translation_vector[None])
  
      return out
  
  
  class _GLTFLoader:
      def __init__(self, stream: BinaryIO) -> None:
          self._json_data = None
          # Map from buffer index to (decoded) binary data
          self._binary_data = {}
  
          version_and_length = _read_header(stream)
          if version_and_length is None:  # GLTF
              stream.seek(0)
              json_data = json.load(stream)
          else:  # GLB
              version, length = version_and_length
              if version != 2:
                  warnings.warn("Unsupported version")
                  return
              json_and_binary_data = _read_chunks(stream, length)
              if json_and_binary_data is None:
                  raise ValueError("Data not found")
              json_data, binary_data = json_and_binary_data
              self._binary_data[0] = binary_data
  
          self._json_data = json_data
          self._accessors = json_data.get("accessors", [])
          self._buffer_views = json_data.get("bufferViews", [])
          self._buffers = json_data.get("buffers", [])
          self._texture_map_images = {}
  
      def _access_image(self, image_index: int) -> np.ndarray:
          """
          Get the data for an image from the file. This is only called
          by _get_texture_map_image which caches it.
          """
  
          image_json = self._json_data["images"][image_index]
          buffer_view = self._buffer_views[image_json["bufferView"]]
          if "byteStride" in buffer_view:
              raise NotImplementedError("strided buffer views")
  
          length = buffer_view["byteLength"]
          offset = buffer_view.get("byteOffset", 0)
  
          binary_data = self.get_binary_data(buffer_view["buffer"])
  
          bytesio = BytesIO(binary_data[offset : offset + length].tobytes())
          with Image.open(bytesio) as f:
              array = np.array(f)
              if array.dtype == np.uint8:
                  return array.astype(np.float32) / 255.0
              else:
                  return array
  
      def _get_texture_map_image(self, image_index: int) -> torch.Tensor:
          """
          Return a texture map image as a torch tensor.
          Calling this function repeatedly with the same arguments returns
          the very same tensor, this allows a memory optimization to happen
          later in TexturesUV.join_scene.
          Any alpha channel is ignored.
          """
          im = self._texture_map_images.get(image_index)
          if im is not None:
              return im
  
          im = torch.from_numpy(self._access_image(image_index))[:, :, :3]
          self._texture_map_images[image_index] = im
          return im
  
      def _access_data(self, accessor_index: int) -> np.ndarray:
          """
          Get the raw data from an accessor as a numpy array.
          """
          accessor = self._accessors[accessor_index]
  
          buffer_view_index = accessor.get("bufferView")
          # Undefined buffer view (all zeros) are not (yet) supported
          if buffer_view_index is None:
              raise NotImplementedError("Undefined buffer view")
  
          accessor_byte_offset = accessor.get("byteOffset", 0)
          component_type = accessor["componentType"]
          element_count = accessor["count"]
          element_type = accessor["type"]
  
          # Sparse accessors are not (yet) supported
          if accessor.get("sparse") is not None:
              raise NotImplementedError("Sparse Accessors")
  
          buffer_view = self._buffer_views[buffer_view_index]
          buffer_index = buffer_view["buffer"]
          buffer_byte_length = buffer_view["byteLength"]
          element_byte_offset = buffer_view.get("byteOffset", 0)
          element_byte_stride = buffer_view.get("byteStride", 0)
          if element_byte_stride != 0 and element_byte_stride < 4:
              raise ValueError("Stride is too small.")
          if element_byte_stride > 252:
              raise ValueError("Stride is too big.")
  
          element_shape = _ELEMENT_SHAPES[element_type]
          item_type = _ITEM_TYPES[component_type]
          item_dtype = np.dtype(item_type)
          item_count = np.prod(element_shape)
          item_size = item_dtype.itemsize
          size = element_count * item_count * item_size
          if size > buffer_byte_length:
              raise ValueError("Buffer did not have enough data for the accessor")
  
          buffer_ = self._buffers[buffer_index]
          binary_data = self.get_binary_data(buffer_index)
          if len(binary_data) < buffer_["byteLength"]:
              raise ValueError("Not enough binary data for the buffer")
  
          if element_byte_stride == 0:
              element_byte_stride = item_size * item_count
          # The same buffer can store interleaved elements
          if element_byte_stride < item_size * item_count:
              raise ValueError("Items should not overlap")
  
          dtype = np.dtype(
              {
                  "names": ["element"],
                  "formats": [str(element_shape) + item_dtype.str],
                  "offsets": [0],
                  "itemsize": element_byte_stride,
              }
          )
  
          byte_offset = accessor_byte_offset + element_byte_offset
          if byte_offset % item_size != 0:
              raise ValueError("Misaligned data")
          byte_length = element_count * element_byte_stride
          buffer_view = binary_data[byte_offset : byte_offset + byte_length].view(dtype)[
              "element"
          ]
  
          # Convert matrix data from column-major (OpenGL) to row-major order
          if element_type in ("MAT2", "MAT3", "MAT4"):
              buffer_view = np.transpose(buffer_view, (0, 2, 1))
  
          return buffer_view
  
      def _get_primitive_attribute(
          self, primitive_attributes: Dict[str, Any], key: str, dtype
      ) -> Optional[np.ndarray]:
          accessor_index = primitive_attributes.get(key)
          if accessor_index is None:
              return None
          primitive_attribute = self._access_data(accessor_index)
          if key == "JOINTS_0":
              pass
          elif dtype == np.uint8:
              primitive_attribute /= 255.0
          elif dtype == np.uint16:
              primitive_attribute /= 65535.0
          else:
              if dtype != np.float32:
                  raise ValueError("Unexpected data type")
          primitive_attribute = primitive_attribute.astype(dtype)
          return primitive_attribute
  
      def get_binary_data(self, buffer_index: int):
          """
          Get the binary data from a buffer as a 1D numpy array of bytes.
          This is implemented for explicit uri data buffers or the main GLB data
          segment.
          """
          buffer_ = self._buffers[buffer_index]
          binary_data = self._binary_data.get(buffer_index)
          if binary_data is None:  # Lazily decode binary data
              uri = buffer_.get("uri")
              if not uri.startswith(_DATA_URI_PREFIX):
                  raise NotImplementedError("Unexpected URI type")
              binary_data = b64decode(uri[len(_DATA_URI_PREFIX) :])
              binary_data = np.frombuffer(binary_data, dtype=np.uint8)
              self._binary_data[buffer_index] = binary_data
          return binary_data
  
      def get_texture_for_mesh(
          self, primitive: Dict[str, Any], indices: torch.Tensor
      ) -> Optional[TexturesBase]:
          """
          Get the texture object representing the given mesh primitive.
  
          Args:
              primitive: the mesh primitive being loaded.
              indices: the face indices of the mesh
          """
          attributes = primitive["attributes"]
          vertex_colors = self._get_primitive_attribute(attributes, "COLOR_0", np.float32)
          if vertex_colors is not None:
              return TexturesVertex(torch.from_numpy(vertex_colors))
  
          vertex_texcoords_0 = self._get_primitive_attribute(
              attributes, "TEXCOORD_0", np.float32
          )
          if vertex_texcoords_0 is not None:
              verts_uvs = torch.from_numpy(vertex_texcoords_0)
              verts_uvs[:, 1] = 1 - verts_uvs[:, -1]
              faces_uvs = indices
              material_index = primitive.get("material", 0)
              material = self._json_data["materials"][material_index]
              material_roughness = material["pbrMetallicRoughness"]
              if "baseColorTexture" in material_roughness:
                  texture_index = material_roughness["baseColorTexture"]["index"]
                  texture_json = self._json_data["textures"][texture_index]
                  # Todo - include baseColorFactor when also given
                  # Todo - look at the sampler
                  image_index = texture_json["source"]
                  map = self._get_texture_map_image(image_index)
              elif "baseColorFactor" in material_roughness:
                  # Constant color?
                  map = torch.FloatTensor(material_roughness["baseColorFactor"])[
                      None, None, :3
                  ]
              texture = TexturesUV(
                  # pyre-fixme[61]: `map` may not be initialized here.
                  maps=[map],  # alpha channel ignored
                  faces_uvs=[faces_uvs],
                  verts_uvs=[verts_uvs],
              )
              return texture
  
          return None
  
      def load(self, include_textures: bool) -> List[Tuple[Optional[str], Meshes]]:
          """
          Attempt to load all the meshes making up the default scene from
          the file as a list of possibly-named Meshes objects.
  
          Args:
              include_textures: Whether to try loading textures.
  
          Returns:
              Meshes object containing one mesh.
          """
          if self._json_data is None:
              raise ValueError("Initialization problem")
  
          # This loads the default scene from the file.
          # This is usually the only one.
          # It is possible to have multiple scenes, in which case
          # you could choose another here instead of taking the default.
          scene_index = self._json_data.get("scene")
  
          if scene_index is None:
              raise ValueError("Default scene is not specified.")
  
          scene = self._json_data["scenes"][scene_index]
          nodes = self._json_data.get("nodes", [])
          meshes = self._json_data.get("meshes", [])
          root_node_indices = scene["nodes"]
  
          mesh_transform = Transform3d()
          names_meshes_list: List[Tuple[Optional[str], Meshes]] = []
  
          # Keep track and apply the transform of the scene node to mesh vertices
          Q = deque([(Transform3d(), node_index) for node_index in root_node_indices])
  
          while Q:
              parent_transform, current_node_index = Q.popleft()
  
              current_node = nodes[current_node_index]
  
              transform = _make_node_transform(current_node)
              current_transform = transform.compose(parent_transform)
  
              if "mesh" in current_node:
                  mesh_index = current_node["mesh"]
                  mesh = meshes[mesh_index]
                  mesh_name = mesh.get("name", None)
                  mesh_transform = current_transform
  
                  for primitive in mesh["primitives"]:
                      attributes = primitive["attributes"]
                      accessor_index = attributes["POSITION"]
                      positions = torch.from_numpy(
                          self._access_data(accessor_index).copy()
                      )
                      positions = mesh_transform.transform_points(positions)
  
                      mode = primitive.get("mode", _PrimitiveMode.TRIANGLES)
                      if mode != _PrimitiveMode.TRIANGLES:
                          raise NotImplementedError("Non triangular meshes")
  
                      if "indices" in primitive:
                          accessor_index = primitive["indices"]
                          indices = self._access_data(accessor_index).astype(np.int64)
                      else:
                          indices = np.arange(0, len(positions), dtype=np.int64)
                      indices = torch.from_numpy(indices.reshape(-1, 3))
  
                      texture = None
                      if include_textures:
                          texture = self.get_texture_for_mesh(primitive, indices)
  
                      mesh_obj = Meshes(
                          verts=[positions], faces=[indices], textures=texture
                      )
                      names_meshes_list.append((mesh_name, mesh_obj))
  
              if "children" in current_node:
                  children_node_indices = current_node["children"]
                  Q.extend(
                      [
                          (current_transform, node_index)
                          for node_index in children_node_indices
                      ]
                  )
  
          return names_meshes_list
  
  
  def load_meshes(
      path: PathOrStr,
      path_manager: PathManager,
      include_textures: bool = True,
  ) -> List[Tuple[Optional[str], Meshes]]:
      """
      Loads all the meshes from the default scene in the given GLB file.
      and returns them separately.
  
      Args:
          path: path to read from
          path_manager: PathManager object for interpreting the path
          include_textures: whether to load textures
  
      Returns:
          List of (name, mesh) pairs, where the name is the optional name property
              from the GLB file, or None if it is absent, and the mesh is a Meshes
              object containing one mesh.
      """
      with _open_file(path, path_manager, "rb") as f:
          loader = _GLTFLoader(cast(BinaryIO, f))
      names_meshes_list = loader.load(include_textures=include_textures)
      return names_meshes_list
  
  
  class MeshGlbFormat(MeshFormatInterpreter):
      """
      Implements loading meshes from glTF 2 assets stored in a
      GLB container file or a glTF JSON file with embedded binary data.
  
      This implementation is quite restricted in what it supports.
  
          - It does not try to validate the input against the standard.
          - It loads the default scene only.
          - Only triangulated geometry is supported.
          - The geometry of all meshes of the entire scene is aggregated into a single mesh.
          Use `load_meshes()` instead to get un-aggregated (but transformed) ones.
          - All material properties are ignored except for either vertex color, baseColorTexture
          or baseColorFactor. If available, one of these (in this order) is exclusively
          used which does not match the semantics of the standard.
      """
  
      def __init__(self) -> None:
          self.known_suffixes = (".glb",)
  
      def read(
          self,
          path: PathOrStr,
          include_textures: bool,
          device,
          path_manager: PathManager,
          **kwargs,
      ) -> Optional[Meshes]:
          if not endswith(path, self.known_suffixes):
              return None
  
          names_meshes_list = load_meshes(
              path=path,
              path_manager=path_manager,
              include_textures=include_textures,
          )
  
          meshes_list = [mesh for name, mesh in names_meshes_list]
          mesh = join_meshes_as_scene(meshes_list)
          return mesh.to(device)
  
      def save(
          self,
          data: Meshes,
          path: PathOrStr,
          path_manager: PathManager,
          binary: Optional[bool],
          **kwargs,
      ) -> bool:
          return False
  
apis: torch.FloatTensor numpy.transpose numpy.dtype torch.from_numpy numpy.prod numpy.array numpy.frombuffer