import os import cv2 import torch import trimesh import numpy as np from kiui.op import safe_normalize, dot from kiui.typing import * class Mesh: """ A torch-native trimesh class, with support for ``ply/obj/glb`` formats. Note: This class only supports one mesh with a single texture image (an albedo texture and a metallic-roughness texture). """ def __init__( self, v: Optional[Tensor] = None, f: Optional[Tensor] = None, vn: Optional[Tensor] = None, fn: Optional[Tensor] = None, vt: Optional[Tensor] = None, ft: Optional[Tensor] = None, vc: Optional[Tensor] = None, # vertex color albedo: Optional[Tensor] = None, metallicRoughness: Optional[Tensor] = None, device: Optional[torch.device] = None, ): """Init a mesh directly using all attributes. Args: v (Optional[Tensor]): vertices, float [N, 3]. Defaults to None. f (Optional[Tensor]): faces, int [M, 3]. Defaults to None. vn (Optional[Tensor]): vertex normals, float [N, 3]. Defaults to None. fn (Optional[Tensor]): faces for normals, int [M, 3]. Defaults to None. vt (Optional[Tensor]): vertex uv coordinates, float [N, 2]. Defaults to None. ft (Optional[Tensor]): faces for uvs, int [M, 3]. Defaults to None. vc (Optional[Tensor]): vertex colors, float [N, 3]. Defaults to None. albedo (Optional[Tensor]): albedo texture, float [H, W, 3], RGB format. Defaults to None. metallicRoughness (Optional[Tensor]): metallic-roughness texture, float [H, W, 3], metallic(Blue) = metallicRoughness[..., 2], roughness(Green) = metallicRoughness[..., 1]. Defaults to None. device (Optional[torch.device]): torch device. Defaults to None. """ self.device = device self.v = v self.vn = vn self.vt = vt self.f = f self.fn = fn self.ft = ft # will first see if there is vertex color to use self.vc = vc # only support a single albedo image self.albedo = albedo # pbr extension, metallic(Blue) = metallicRoughness[..., 2], roughness(Green) = metallicRoughness[..., 1] # ref: https://registry.khronos.org/glTF/specs/2.0/glTF-2.0.html self.metallicRoughness = metallicRoughness self.ori_center = 0 self.ori_scale = 1 @classmethod def load(cls, path, resize=True, clean=False, renormal=True, retex=False, bound=0.9, front_dir='+z', **kwargs): """load mesh from path. Args: path (str): path to mesh file, supports ply, obj, glb. clean (bool, optional): perform mesh cleaning at load (e.g., merge close vertices). Defaults to False. resize (bool, optional): auto resize the mesh using ``bound`` into [-bound, bound]^3. Defaults to True. renormal (bool, optional): re-calc the vertex normals. Defaults to True. retex (bool, optional): re-calc the uv coordinates, will overwrite the existing uv coordinates. Defaults to False. bound (float, optional): bound to resize. Defaults to 0.9. front_dir (str, optional): front-view direction of the mesh, should be [+-][xyz][ 123]. Defaults to '+z'. device (torch.device, optional): torch device. Defaults to None. Note: a ``device`` keyword argument can be provided to specify the torch device. If it's not provided, we will try to use ``'cuda'`` as the device if it's available. Returns: Mesh: the loaded Mesh object. """ # obj supports face uv if path.endswith(".obj"): mesh = cls.load_obj(path, **kwargs) # trimesh only supports vertex uv, but can load more formats else: mesh = cls.load_trimesh(path, **kwargs) # clean if clean: from kiui.mesh_utils import clean_mesh vertices = mesh.v.detach().cpu().numpy() triangles = mesh.f.detach().cpu().numpy() vertices, triangles = clean_mesh(vertices, triangles, remesh=False) mesh.v = torch.from_numpy(vertices).contiguous().float().to(mesh.device) mesh.f = torch.from_numpy(triangles).contiguous().int().to(mesh.device) print(f"[Mesh loading] v: {mesh.v.shape}, f: {mesh.f.shape}") # auto-normalize if resize: mesh.auto_size(bound=bound) # auto-fix normal if renormal or mesh.vn is None: mesh.auto_normal() print(f"[Mesh loading] vn: {mesh.vn.shape}, fn: {mesh.fn.shape}") # auto-fix texcoords if retex or (mesh.albedo is not None and mesh.vt is None): mesh.auto_uv(cache_path=path) print(f"[Mesh loading] vt: {mesh.vt.shape}, ft: {mesh.ft.shape}") # rotate front dir to +z if front_dir != "+z": # axis switch if "-z" in front_dir: T = torch.tensor([[1, 0, 0], [0, 1, 0], [0, 0, -1]], device=mesh.device, dtype=torch.float32) elif "+x" in front_dir: T = torch.tensor([[0, 0, 1], [0, 1, 0], [1, 0, 0]], device=mesh.device, dtype=torch.float32) elif "-x" in front_dir: T = torch.tensor([[0, 0, -1], [0, 1, 0], [1, 0, 0]], device=mesh.device, dtype=torch.float32) elif "+y" in front_dir: T = torch.tensor([[1, 0, 0], [0, 0, 1], [0, 1, 0]], device=mesh.device, dtype=torch.float32) elif "-y" in front_dir: T = torch.tensor([[1, 0, 0], [0, 0, -1], [0, 1, 0]], device=mesh.device, dtype=torch.float32) else: T = torch.tensor([[1, 0, 0], [0, 1, 0], [0, 0, 1]], device=mesh.device, dtype=torch.float32) # rotation (how many 90 degrees) if '1' in front_dir: T @= torch.tensor([[0, -1, 0], [1, 0, 0], [0, 0, 1]], device=mesh.device, dtype=torch.float32) elif '2' in front_dir: T @= torch.tensor([[1, 0, 0], [0, -1, 0], [0, 0, 1]], device=mesh.device, dtype=torch.float32) elif '3' in front_dir: T @= torch.tensor([[0, 1, 0], [-1, 0, 0], [0, 0, 1]], device=mesh.device, dtype=torch.float32) mesh.v @= T mesh.vn @= T return mesh # load from obj file @classmethod def load_obj(cls, path, albedo_path=None, device=None): """load an ``obj`` mesh. Args: path (str): path to mesh. albedo_path (str, optional): path to the albedo texture image, will overwrite the existing texture path if specified in mtl. Defaults to None. device (torch.device, optional): torch device. Defaults to None. Note: We will try to read `mtl` path from `obj`, else we assume the file name is the same as `obj` but with `mtl` extension. The `usemtl` statement is ignored, and we only use the last material path in `mtl` file. Returns: Mesh: the loaded Mesh object. """ assert os.path.splitext(path)[-1] == ".obj" mesh = cls() # device if device is None: device = torch.device("cpu" if torch.cuda.is_available() else "cpu") mesh.device = device # load obj with open(path, "r") as f: lines = f.readlines() def parse_f_v(fv): # pass in a vertex term of a face, return {v, vt, vn} (-1 if not provided) # supported forms: # f v1 v2 v3 # f v1/vt1 v2/vt2 v3/vt3 # f v1/vt1/vn1 v2/vt2/vn2 v3/vt3/vn3 # f v1//vn1 v2//vn2 v3//vn3 xs = [int(x) - 1 if x != "" else -1 for x in fv.split("/")] xs.extend([-1] * (3 - len(xs))) return xs[0], xs[1], xs[2] vertices, texcoords, normals = [], [], [] faces, tfaces, nfaces = [], [], [] mtl_path = None for line in lines: split_line = line.split() # empty line if len(split_line) == 0: continue prefix = split_line[0].lower() # mtllib if prefix == "mtllib": mtl_path = split_line[1] # usemtl elif prefix == "usemtl": pass # ignored # v/vn/vt elif prefix == "v": vertices.append([float(v) for v in split_line[1:]]) elif prefix == "vn": normals.append([float(v) for v in split_line[1:]]) elif prefix == "vt": val = [float(v) for v in split_line[1:]] texcoords.append([val[0], 1.0 - val[1]]) elif prefix == "f": vs = split_line[1:] nv = len(vs) v0, t0, n0 = parse_f_v(vs[0]) for i in range(nv - 2): # triangulate (assume vertices are ordered) v1, t1, n1 = parse_f_v(vs[i + 1]) v2, t2, n2 = parse_f_v(vs[i + 2]) faces.append([v0, v1, v2]) tfaces.append([t0, t1, t2]) nfaces.append([n0, n1, n2]) mesh.v = torch.tensor(vertices, dtype=torch.float32, device=device) mesh.vt = ( torch.tensor(texcoords, dtype=torch.float32, device=device) if len(texcoords) > 0 else None ) mesh.vn = ( torch.tensor(normals, dtype=torch.float32, device=device) if len(normals) > 0 else None ) mesh.f = torch.tensor(faces, dtype=torch.int32, device=device) mesh.ft = ( torch.tensor(tfaces, dtype=torch.int32, device=device) if len(texcoords) > 0 else None ) mesh.fn = ( torch.tensor(nfaces, dtype=torch.int32, device=device) if len(normals) > 0 else None ) # see if there is vertex color use_vertex_color = False if mesh.v.shape[1] == 6: use_vertex_color = True mesh.vc = mesh.v[:, 3:] mesh.v = mesh.v[:, :3] print(f"[load_obj] use vertex color: {mesh.vc.shape}") # try to load texture image if not use_vertex_color: # try to retrieve mtl file mtl_path_candidates = [] if mtl_path is not None: mtl_path_candidates.append(mtl_path) mtl_path_candidates.append(os.path.join(os.path.dirname(path), mtl_path)) mtl_path_candidates.append(path.replace(".obj", ".mtl")) mtl_path = None for candidate in mtl_path_candidates: if os.path.exists(candidate): mtl_path = candidate break # if albedo_path is not provided, try retrieve it from mtl metallic_path = None roughness_path = None if mtl_path is not None and albedo_path is None: with open(mtl_path, "r") as f: lines = f.readlines() for line in lines: split_line = line.split() # empty line if len(split_line) == 0: continue prefix = split_line[0] if "map_Kd" in prefix: # assume relative path! albedo_path = os.path.join(os.path.dirname(path), split_line[1]) print(f"[load_obj] use texture from: {albedo_path}") elif "map_Pm" in prefix: metallic_path = os.path.join(os.path.dirname(path), split_line[1]) elif "map_Pr" in prefix: roughness_path = os.path.join(os.path.dirname(path), split_line[1]) # still not found albedo_path, or the path doesn't exist if albedo_path is None or not os.path.exists(albedo_path): # init an empty texture print(f"[load_obj] init empty albedo!") # albedo = np.random.rand(1024, 1024, 3).astype(np.float32) albedo = np.ones((1024, 1024, 3), dtype=np.float32) * np.array([0.5, 0.5, 0.5]) # default color else: albedo = cv2.imread(albedo_path, cv2.IMREAD_UNCHANGED) albedo = cv2.cvtColor(albedo, cv2.COLOR_BGR2RGB) albedo = albedo.astype(np.float32) / 255 print(f"[load_obj] load texture: {albedo.shape}") mesh.albedo = torch.tensor(albedo, dtype=torch.float32, device=device) # try to load metallic and roughness if metallic_path is not None and roughness_path is not None: print(f"[load_obj] load metallicRoughness from: {metallic_path}, {roughness_path}") metallic = cv2.imread(metallic_path, cv2.IMREAD_UNCHANGED) metallic = metallic.astype(np.float32) / 255 roughness = cv2.imread(roughness_path, cv2.IMREAD_UNCHANGED) roughness = roughness.astype(np.float32) / 255 metallicRoughness = np.stack([np.zeros_like(metallic), roughness, metallic], axis=-1) mesh.metallicRoughness = torch.tensor(metallicRoughness, dtype=torch.float32, device=device).contiguous() return mesh @classmethod def load_trimesh(cls, path, device=None): """load a mesh using ``trimesh.load()``. Can load various formats like ``glb`` and serves as a fallback. Note: We will try to merge all meshes if the glb contains more than one, but **this may cause the texture to lose**, since we only support one texture image! Args: path (str): path to the mesh file. device (torch.device, optional): torch device. Defaults to None. Returns: Mesh: the loaded Mesh object. """ mesh = cls() # device if device is None: device = torch.device("cpu" if torch.cuda.is_available() else "cpu") mesh.device = device # use trimesh to load ply/glb _data = trimesh.load(path) if isinstance(_data, trimesh.Scene): if len(_data.geometry) == 1: _mesh = list(_data.geometry.values())[0] else: print(f"[load_trimesh] concatenating {len(_data.geometry)} meshes.") _concat = [] # loop the scene graph and apply transform to each mesh scene_graph = _data.graph.to_flattened() # dict {name: {transform: 4x4 mat, geometry: str}} for k, v in scene_graph.items(): name = v['geometry'] if name in _data.geometry and isinstance(_data.geometry[name], trimesh.Trimesh): transform = v['transform'] _concat.append(_data.geometry[name].apply_transform(transform)) _mesh = trimesh.util.concatenate(_concat) else: _mesh = _data if _mesh.visual.kind == 'vertex': vertex_colors = _mesh.visual.vertex_colors vertex_colors = np.array(vertex_colors[..., :3]).astype(np.float32) / 255 mesh.vc = torch.tensor(vertex_colors, dtype=torch.float32, device=device) print(f"[load_trimesh] use vertex color: {mesh.vc.shape}") elif _mesh.visual.kind == 'texture': _material = _mesh.visual.material if isinstance(_material, trimesh.visual.material.PBRMaterial): texture = np.array(_material.baseColorTexture).astype(np.float32) / 255 # load metallicRoughness if present if _material.metallicRoughnessTexture is not None: metallicRoughness = np.array(_material.metallicRoughnessTexture).astype(np.float32) / 255 mesh.metallicRoughness = torch.tensor(metallicRoughness, dtype=torch.float32, device=device).contiguous() elif isinstance(_material, trimesh.visual.material.SimpleMaterial): texture = np.array(_material.to_pbr().baseColorTexture).astype(np.float32) / 255 else: raise NotImplementedError(f"material type {type(_material)} not supported!") mesh.albedo = torch.tensor(texture[..., :3], dtype=torch.float32, device=device).contiguous() print(f"[load_trimesh] load texture: {texture.shape}") else: texture = np.ones((1024, 1024, 3), dtype=np.float32) * np.array([0.5, 0.5, 0.5]) mesh.albedo = torch.tensor(texture, dtype=torch.float32, device=device) print(f"[load_trimesh] failed to load texture.") vertices = _mesh.vertices try: texcoords = _mesh.visual.uv texcoords[:, 1] = 1 - texcoords[:, 1] except Exception as e: texcoords = None try: normals = _mesh.vertex_normals except Exception as e: normals = None # trimesh only support vertex uv... faces = tfaces = nfaces = _mesh.faces mesh.v = torch.tensor(vertices, dtype=torch.float32, device=device) mesh.vt = ( torch.tensor(texcoords, dtype=torch.float32, device=device) if texcoords is not None else None ) mesh.vn = ( torch.tensor(normals, dtype=torch.float32, device=device) if normals is not None else None ) mesh.f = torch.tensor(faces, dtype=torch.int32, device=device) mesh.ft = ( torch.tensor(tfaces, dtype=torch.int32, device=device) if texcoords is not None else None ) mesh.fn = ( torch.tensor(nfaces, dtype=torch.int32, device=device) if normals is not None else None ) return mesh # sample surface (using trimesh) def sample_surface(self, count: int): """sample points on the surface of the mesh. Args: count (int): number of points to sample. Returns: torch.Tensor: the sampled points, float [count, 3]. """ _mesh = trimesh.Trimesh(vertices=self.v.detach().cpu().numpy(), faces=self.f.detach().cpu().numpy()) points, face_idx = trimesh.sample.sample_surface(_mesh, count) points = torch.from_numpy(points).float().to(self.device) return points # aabb def aabb(self): """get the axis-aligned bounding box of the mesh. Returns: Tuple[torch.Tensor]: the min xyz and max xyz of the mesh. """ return torch.min(self.v, dim=0).values, torch.max(self.v, dim=0).values # unit size @torch.no_grad() def auto_size(self, bound=0.9): """auto resize the mesh. Args: bound (float, optional): resizing into ``[-bound, bound]^3``. Defaults to 0.9. """ vmin, vmax = self.aabb() self.ori_center = (vmax + vmin) / 2 self.ori_scale = 2 * bound / torch.max(vmax - vmin).item() self.v = (self.v - self.ori_center) * self.ori_scale def auto_normal(self): """auto calculate the vertex normals. """ i0, i1, i2 = self.f[:, 0].long(), self.f[:, 1].long(), self.f[:, 2].long() v0, v1, v2 = self.v[i0, :], self.v[i1, :], self.v[i2, :] face_normals = torch.cross(v1 - v0, v2 - v0) # Splat face normals to vertices vn = torch.zeros_like(self.v) vn.scatter_add_(0, i0[:, None].repeat(1, 3), face_normals) vn.scatter_add_(0, i1[:, None].repeat(1, 3), face_normals) vn.scatter_add_(0, i2[:, None].repeat(1, 3), face_normals) # Normalize, replace zero (degenerated) normals with some default value vn = torch.where( dot(vn, vn) > 1e-20, vn, torch.tensor([0.0, 0.0, 1.0], dtype=torch.float32, device=vn.device), ) vn = safe_normalize(vn) self.vn = vn self.fn = self.f def auto_uv(self, cache_path=None, vmap=True): """auto calculate the uv coordinates. Args: cache_path (str, optional): path to save/load the uv cache as a npz file, this can avoid calculating uv every time when loading the same mesh, which is time-consuming. Defaults to None. vmap (bool, optional): remap vertices based on uv coordinates, so each v correspond to a unique vt (necessary for formats like gltf). Usually this will duplicate the vertices on the edge of uv atlas. Defaults to True. """ # try to load cache if cache_path is not None: cache_path = os.path.splitext(cache_path)[0] + "_uv.npz" if cache_path is not None and os.path.exists(cache_path): data = np.load(cache_path) vt_np, ft_np, vmapping = data["vt"], data["ft"], data["vmapping"] else: import xatlas v_np = self.v.detach().cpu().numpy() f_np = self.f.detach().int().cpu().numpy() atlas = xatlas.Atlas() atlas.add_mesh(v_np, f_np) chart_options = xatlas.ChartOptions() # chart_options.max_iterations = 4 atlas.generate(chart_options=chart_options) vmapping, ft_np, vt_np = atlas[0] # [N], [M, 3], [N, 2] # save to cache if cache_path is not None: np.savez(cache_path, vt=vt_np, ft=ft_np, vmapping=vmapping) vt = torch.from_numpy(vt_np.astype(np.float32)).to(self.device) ft = torch.from_numpy(ft_np.astype(np.int32)).to(self.device) self.vt = vt self.ft = ft if vmap: vmapping = torch.from_numpy(vmapping.astype(np.int64)).long().to(self.device) self.align_v_to_vt(vmapping) def align_v_to_vt(self, vmapping=None): """ remap v/f and vn/fn to vt/ft. Args: vmapping (np.ndarray, optional): the mapping relationship from f to ft. Defaults to None. """ if vmapping is None: ft = self.ft.view(-1).long() f = self.f.view(-1).long() vmapping = torch.zeros(self.vt.shape[0], dtype=torch.long, device=self.device) vmapping[ft] = f # scatter, randomly choose one if index is not unique self.v = self.v[vmapping] self.f = self.ft if self.vn is not None: self.vn = self.vn[vmapping] self.fn = self.ft def to(self, device): """move all tensor attributes to device. Args: device (torch.device): target device. Returns: Mesh: self. """ self.device = device for name in ["v", "f", "vn", "fn", "vt", "ft", "albedo", "vc", "metallicRoughness"]: tensor = getattr(self, name) if tensor is not None: setattr(self, name, tensor.to(device)) return self def write(self, path): """write the mesh to a path. Args: path (str): path to write, supports ply, obj and glb. """ if path.endswith(".ply"): self.write_ply(path) elif path.endswith(".obj"): self.write_obj(path) elif path.endswith(".glb") or path.endswith(".gltf"): self.write_glb(path) else: raise NotImplementedError(f"format {path} not supported!") def write_ply(self, path): """write the mesh in ply format. Only for geometry! Args: path (str): path to write. """ if self.albedo is not None: print(f'[WARN] ply format does not support exporting texture, will ignore!') v_np = self.v.detach().cpu().numpy() f_np = self.f.detach().cpu().numpy() _mesh = trimesh.Trimesh(vertices=v_np, faces=f_np) _mesh.export(path) def write_glb(self, path): """write the mesh in glb/gltf format. This will create a scene with a single mesh. Args: path (str): path to write. """ # assert self.v.shape[0] == self.vn.shape[0] and self.v.shape[0] == self.vt.shape[0] if self.vt is not None and self.v.shape[0] != self.vt.shape[0]: self.align_v_to_vt() import pygltflib f_np = self.f.detach().cpu().numpy().astype(np.uint32) f_np_blob = f_np.flatten().tobytes() v_np = self.v.detach().cpu().numpy().astype(np.float32) v_np_blob = v_np.tobytes() blob = f_np_blob + v_np_blob byteOffset = len(blob) # base mesh gltf = pygltflib.GLTF2( scene=0, scenes=[pygltflib.Scene(nodes=[0])], nodes=[pygltflib.Node(mesh=0)], meshes=[pygltflib.Mesh(primitives=[pygltflib.Primitive( # indices to accessors (0 is triangles) attributes=pygltflib.Attributes( POSITION=1, ), indices=0, )])], buffers=[ pygltflib.Buffer(byteLength=len(f_np_blob) + len(v_np_blob)) ], # buffer view (based on dtype) bufferViews=[ # triangles; as flatten (element) array pygltflib.BufferView( buffer=0, byteLength=len(f_np_blob), target=pygltflib.ELEMENT_ARRAY_BUFFER, # GL_ELEMENT_ARRAY_BUFFER (34963) ), # positions; as vec3 array pygltflib.BufferView( buffer=0, byteOffset=len(f_np_blob), byteLength=len(v_np_blob), byteStride=12, # vec3 target=pygltflib.ARRAY_BUFFER, # GL_ARRAY_BUFFER (34962) ), ], accessors=[ # 0 = triangles pygltflib.Accessor( bufferView=0, componentType=pygltflib.UNSIGNED_INT, # GL_UNSIGNED_INT (5125) count=f_np.size, type=pygltflib.SCALAR, max=[int(f_np.max())], min=[int(f_np.min())], ), # 1 = positions pygltflib.Accessor( bufferView=1, componentType=pygltflib.FLOAT, # GL_FLOAT (5126) count=len(v_np), type=pygltflib.VEC3, max=v_np.max(axis=0).tolist(), min=v_np.min(axis=0).tolist(), ), ], ) # append texture info if self.vt is not None: vt_np = self.vt.detach().cpu().numpy().astype(np.float32) vt_np_blob = vt_np.tobytes() albedo = self.albedo.detach().cpu().numpy() albedo = (albedo * 255).astype(np.uint8) albedo = cv2.cvtColor(albedo, cv2.COLOR_RGB2BGR) albedo_blob = cv2.imencode('.png', albedo)[1].tobytes() # update primitive gltf.meshes[0].primitives[0].attributes.TEXCOORD_0 = 2 gltf.meshes[0].primitives[0].material = 0 # update materials gltf.materials.append(pygltflib.Material( pbrMetallicRoughness=pygltflib.PbrMetallicRoughness( baseColorTexture=pygltflib.TextureInfo(index=0, texCoord=0), metallicFactor=0.0, roughnessFactor=1.0, ), alphaMode=pygltflib.OPAQUE, alphaCutoff=None, doubleSided=True, )) gltf.textures.append(pygltflib.Texture(sampler=0, source=0)) gltf.samplers.append(pygltflib.Sampler(magFilter=pygltflib.LINEAR, minFilter=pygltflib.LINEAR_MIPMAP_LINEAR, wrapS=pygltflib.REPEAT, wrapT=pygltflib.REPEAT)) gltf.images.append(pygltflib.Image(bufferView=3, mimeType="image/png")) # update buffers gltf.bufferViews.append( # index = 2, texcoords; as vec2 array pygltflib.BufferView( buffer=0, byteOffset=byteOffset, byteLength=len(vt_np_blob), byteStride=8, # vec2 target=pygltflib.ARRAY_BUFFER, ) ) gltf.accessors.append( # 2 = texcoords pygltflib.Accessor( bufferView=2, componentType=pygltflib.FLOAT, count=len(vt_np), type=pygltflib.VEC2, max=vt_np.max(axis=0).tolist(), min=vt_np.min(axis=0).tolist(), ) ) blob += vt_np_blob byteOffset += len(vt_np_blob) gltf.bufferViews.append( # index = 3, albedo texture; as none target pygltflib.BufferView( buffer=0, byteOffset=byteOffset, byteLength=len(albedo_blob), ) ) blob += albedo_blob byteOffset += len(albedo_blob) gltf.buffers[0].byteLength = byteOffset # append metllic roughness if self.metallicRoughness is not None: metallicRoughness = self.metallicRoughness.detach().cpu().numpy() metallicRoughness = (metallicRoughness * 255).astype(np.uint8) metallicRoughness = cv2.cvtColor(metallicRoughness, cv2.COLOR_RGB2BGR) metallicRoughness_blob = cv2.imencode('.png', metallicRoughness)[1].tobytes() # update texture definition gltf.materials[0].pbrMetallicRoughness.metallicFactor = 1.0 gltf.materials[0].pbrMetallicRoughness.roughnessFactor = 1.0 gltf.materials[0].pbrMetallicRoughness.metallicRoughnessTexture = pygltflib.TextureInfo(index=1, texCoord=0) gltf.textures.append(pygltflib.Texture(sampler=1, source=1)) gltf.samplers.append(pygltflib.Sampler(magFilter=pygltflib.LINEAR, minFilter=pygltflib.LINEAR_MIPMAP_LINEAR, wrapS=pygltflib.REPEAT, wrapT=pygltflib.REPEAT)) gltf.images.append(pygltflib.Image(bufferView=4, mimeType="image/png")) # update buffers gltf.bufferViews.append( # index = 4, metallicRoughness texture; as none target pygltflib.BufferView( buffer=0, byteOffset=byteOffset, byteLength=len(metallicRoughness_blob), ) ) blob += metallicRoughness_blob byteOffset += len(metallicRoughness_blob) gltf.buffers[0].byteLength = byteOffset # set actual data gltf.set_binary_blob(blob) # glb = b"".join(gltf.save_to_bytes()) gltf.save(path) def write_obj(self, path): """write the mesh in obj format. Will also write the texture and mtl files. Args: path (str): path to write. """ mtl_path = path.replace(".obj", ".mtl") albedo_path = path.replace(".obj", "_albedo.png") metallic_path = path.replace(".obj", "_metallic.png") roughness_path = path.replace(".obj", "_roughness.png") v_np = self.v.detach().cpu().numpy() vt_np = self.vt.detach().cpu().numpy() if self.vt is not None else None vn_np = self.vn.detach().cpu().numpy() if self.vn is not None else None f_np = self.f.detach().cpu().numpy() ft_np = self.ft.detach().cpu().numpy() if self.ft is not None else None fn_np = self.fn.detach().cpu().numpy() if self.fn is not None else None with open(path, "w") as fp: fp.write(f"mtllib {os.path.basename(mtl_path)} \n") for v in v_np: fp.write(f"v {v[0]} {v[1]} {v[2]} \n") if vt_np is not None: for v in vt_np: fp.write(f"vt {v[0]} {1 - v[1]} \n") if vn_np is not None: for v in vn_np: fp.write(f"vn {v[0]} {v[1]} {v[2]} \n") fp.write(f"usemtl defaultMat \n") for i in range(len(f_np)): fp.write( f'f {f_np[i, 0] + 1}/{ft_np[i, 0] + 1 if ft_np is not None else ""}/{fn_np[i, 0] + 1 if fn_np is not None else ""} \ {f_np[i, 1] + 1}/{ft_np[i, 1] + 1 if ft_np is not None else ""}/{fn_np[i, 1] + 1 if fn_np is not None else ""} \ {f_np[i, 2] + 1}/{ft_np[i, 2] + 1 if ft_np is not None else ""}/{fn_np[i, 2] + 1 if fn_np is not None else ""} \n' ) with open(mtl_path, "w") as fp: fp.write(f"newmtl defaultMat \n") fp.write(f"Ka 1 1 1 \n") fp.write(f"Kd 1 1 1 \n") fp.write(f"Ks 0 0 0 \n") fp.write(f"Tr 1 \n") fp.write(f"illum 1 \n") fp.write(f"Ns 0 \n") if self.albedo is not None: fp.write(f"map_Kd {os.path.basename(albedo_path)} \n") if self.metallicRoughness is not None: # ref: https://en.wikipedia.org/wiki/Wavefront_.obj_file#Physically-based_Rendering fp.write(f"map_Pm {os.path.basename(metallic_path)} \n") fp.write(f"map_Pr {os.path.basename(roughness_path)} \n") if self.albedo is not None: albedo = self.albedo.detach().cpu().numpy() albedo = (albedo * 255).astype(np.uint8) cv2.imwrite(albedo_path, cv2.cvtColor(albedo, cv2.COLOR_RGB2BGR)) if self.metallicRoughness is not None: metallicRoughness = self.metallicRoughness.detach().cpu().numpy() metallicRoughness = (metallicRoughness * 255).astype(np.uint8) cv2.imwrite(metallic_path, metallicRoughness[..., 2]) cv2.imwrite(roughness_path, metallicRoughness[..., 1])