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import os |
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import cv2 |
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import torch |
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import trimesh |
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import numpy as np |
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from kiui.op import safe_normalize, dot |
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from kiui.typing import * |
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class Mesh: |
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""" |
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A torch-native trimesh class, with support for ``ply/obj/glb`` formats. |
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Note: |
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This class only supports one mesh with a single texture image (an albedo texture and a metallic-roughness texture). |
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""" |
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def __init__( |
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self, |
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v: Optional[Tensor] = None, |
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f: Optional[Tensor] = None, |
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vn: Optional[Tensor] = None, |
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fn: Optional[Tensor] = None, |
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vt: Optional[Tensor] = None, |
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ft: Optional[Tensor] = None, |
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vc: Optional[Tensor] = None, |
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albedo: Optional[Tensor] = None, |
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metallicRoughness: Optional[Tensor] = None, |
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device: Optional[torch.device] = None, |
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): |
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"""Init a mesh directly using all attributes. |
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Args: |
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v (Optional[Tensor]): vertices, float [N, 3]. Defaults to None. |
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f (Optional[Tensor]): faces, int [M, 3]. Defaults to None. |
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vn (Optional[Tensor]): vertex normals, float [N, 3]. Defaults to None. |
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fn (Optional[Tensor]): faces for normals, int [M, 3]. Defaults to None. |
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vt (Optional[Tensor]): vertex uv coordinates, float [N, 2]. Defaults to None. |
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ft (Optional[Tensor]): faces for uvs, int [M, 3]. Defaults to None. |
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vc (Optional[Tensor]): vertex colors, float [N, 3]. Defaults to None. |
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albedo (Optional[Tensor]): albedo texture, float [H, W, 3], RGB format. Defaults to None. |
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metallicRoughness (Optional[Tensor]): metallic-roughness texture, float [H, W, 3], metallic(Blue) = metallicRoughness[..., 2], roughness(Green) = metallicRoughness[..., 1]. Defaults to None. |
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device (Optional[torch.device]): torch device. Defaults to None. |
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""" |
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self.device = device |
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self.v = v |
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self.vn = vn |
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self.vt = vt |
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self.f = f |
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self.fn = fn |
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self.ft = ft |
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self.vc = vc |
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self.albedo = albedo |
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self.metallicRoughness = metallicRoughness |
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self.ori_center = 0 |
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self.ori_scale = 1 |
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@classmethod |
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def load(cls, path, resize=True, clean=False, renormal=True, retex=False, bound=0.9, front_dir='+z', **kwargs): |
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"""load mesh from path. |
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Args: |
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path (str): path to mesh file, supports ply, obj, glb. |
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clean (bool, optional): perform mesh cleaning at load (e.g., merge close vertices). Defaults to False. |
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resize (bool, optional): auto resize the mesh using ``bound`` into [-bound, bound]^3. Defaults to True. |
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renormal (bool, optional): re-calc the vertex normals. Defaults to True. |
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retex (bool, optional): re-calc the uv coordinates, will overwrite the existing uv coordinates. Defaults to False. |
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bound (float, optional): bound to resize. Defaults to 0.9. |
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front_dir (str, optional): front-view direction of the mesh, should be [+-][xyz][ 123]. Defaults to '+z'. |
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device (torch.device, optional): torch device. Defaults to None. |
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Note: |
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a ``device`` keyword argument can be provided to specify the torch device. |
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If it's not provided, we will try to use ``'cuda'`` as the device if it's available. |
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Returns: |
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Mesh: the loaded Mesh object. |
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""" |
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if path.endswith(".obj"): |
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mesh = cls.load_obj(path, **kwargs) |
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else: |
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mesh = cls.load_trimesh(path, **kwargs) |
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if clean: |
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from kiui.mesh_utils import clean_mesh |
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vertices = mesh.v.detach().cpu().numpy() |
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triangles = mesh.f.detach().cpu().numpy() |
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vertices, triangles = clean_mesh(vertices, triangles, remesh=False) |
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mesh.v = torch.from_numpy(vertices).contiguous().float().to(mesh.device) |
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mesh.f = torch.from_numpy(triangles).contiguous().int().to(mesh.device) |
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print(f"[Mesh loading] v: {mesh.v.shape}, f: {mesh.f.shape}") |
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if resize: |
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mesh.auto_size(bound=bound) |
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if renormal or mesh.vn is None: |
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mesh.auto_normal() |
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print(f"[Mesh loading] vn: {mesh.vn.shape}, fn: {mesh.fn.shape}") |
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if retex or (mesh.albedo is not None and mesh.vt is None): |
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mesh.auto_uv(cache_path=path) |
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print(f"[Mesh loading] vt: {mesh.vt.shape}, ft: {mesh.ft.shape}") |
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if front_dir != "+z": |
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if "-z" in front_dir: |
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T = torch.tensor([[1, 0, 0], [0, 1, 0], [0, 0, -1]], device=mesh.device, dtype=torch.float32) |
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elif "+x" in front_dir: |
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T = torch.tensor([[0, 0, 1], [0, 1, 0], [1, 0, 0]], device=mesh.device, dtype=torch.float32) |
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elif "-x" in front_dir: |
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T = torch.tensor([[0, 0, -1], [0, 1, 0], [1, 0, 0]], device=mesh.device, dtype=torch.float32) |
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elif "+y" in front_dir: |
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T = torch.tensor([[1, 0, 0], [0, 0, 1], [0, 1, 0]], device=mesh.device, dtype=torch.float32) |
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elif "-y" in front_dir: |
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T = torch.tensor([[1, 0, 0], [0, 0, -1], [0, 1, 0]], device=mesh.device, dtype=torch.float32) |
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else: |
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T = torch.tensor([[1, 0, 0], [0, 1, 0], [0, 0, 1]], device=mesh.device, dtype=torch.float32) |
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if '1' in front_dir: |
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T @= torch.tensor([[0, -1, 0], [1, 0, 0], [0, 0, 1]], device=mesh.device, dtype=torch.float32) |
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elif '2' in front_dir: |
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T @= torch.tensor([[1, 0, 0], [0, -1, 0], [0, 0, 1]], device=mesh.device, dtype=torch.float32) |
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elif '3' in front_dir: |
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T @= torch.tensor([[0, 1, 0], [-1, 0, 0], [0, 0, 1]], device=mesh.device, dtype=torch.float32) |
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mesh.v @= T |
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mesh.vn @= T |
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return mesh |
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@classmethod |
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def load_obj(cls, path, albedo_path=None, device=None): |
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"""load an ``obj`` mesh. |
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Args: |
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path (str): path to mesh. |
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albedo_path (str, optional): path to the albedo texture image, will overwrite the existing texture path if specified in mtl. Defaults to None. |
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device (torch.device, optional): torch device. Defaults to None. |
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Note: |
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We will try to read `mtl` path from `obj`, else we assume the file name is the same as `obj` but with `mtl` extension. |
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The `usemtl` statement is ignored, and we only use the last material path in `mtl` file. |
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Returns: |
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Mesh: the loaded Mesh object. |
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""" |
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assert os.path.splitext(path)[-1] == ".obj" |
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mesh = cls() |
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if device is None: |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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mesh.device = device |
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with open(path, "r") as f: |
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lines = f.readlines() |
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def parse_f_v(fv): |
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xs = [int(x) - 1 if x != "" else -1 for x in fv.split("/")] |
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xs.extend([-1] * (3 - len(xs))) |
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return xs[0], xs[1], xs[2] |
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vertices, texcoords, normals = [], [], [] |
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faces, tfaces, nfaces = [], [], [] |
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mtl_path = None |
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for line in lines: |
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split_line = line.split() |
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if len(split_line) == 0: |
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continue |
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prefix = split_line[0].lower() |
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if prefix == "mtllib": |
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mtl_path = split_line[1] |
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elif prefix == "usemtl": |
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pass |
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elif prefix == "v": |
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vertices.append([float(v) for v in split_line[1:]]) |
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elif prefix == "vn": |
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normals.append([float(v) for v in split_line[1:]]) |
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elif prefix == "vt": |
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val = [float(v) for v in split_line[1:]] |
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texcoords.append([val[0], 1.0 - val[1]]) |
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elif prefix == "f": |
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vs = split_line[1:] |
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nv = len(vs) |
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v0, t0, n0 = parse_f_v(vs[0]) |
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for i in range(nv - 2): |
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v1, t1, n1 = parse_f_v(vs[i + 1]) |
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v2, t2, n2 = parse_f_v(vs[i + 2]) |
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faces.append([v0, v1, v2]) |
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tfaces.append([t0, t1, t2]) |
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nfaces.append([n0, n1, n2]) |
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mesh.v = torch.tensor(vertices, dtype=torch.float32, device=device) |
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mesh.vt = ( |
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torch.tensor(texcoords, dtype=torch.float32, device=device) |
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if len(texcoords) > 0 |
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else None |
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) |
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mesh.vn = ( |
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torch.tensor(normals, dtype=torch.float32, device=device) |
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if len(normals) > 0 |
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else None |
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) |
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mesh.f = torch.tensor(faces, dtype=torch.int32, device=device) |
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mesh.ft = ( |
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torch.tensor(tfaces, dtype=torch.int32, device=device) |
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if len(texcoords) > 0 |
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else None |
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) |
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mesh.fn = ( |
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torch.tensor(nfaces, dtype=torch.int32, device=device) |
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if len(normals) > 0 |
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else None |
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) |
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use_vertex_color = False |
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if mesh.v.shape[1] == 6: |
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use_vertex_color = True |
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mesh.vc = mesh.v[:, 3:] |
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mesh.v = mesh.v[:, :3] |
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print(f"[load_obj] use vertex color: {mesh.vc.shape}") |
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if not use_vertex_color: |
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mtl_path_candidates = [] |
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if mtl_path is not None: |
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mtl_path_candidates.append(mtl_path) |
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mtl_path_candidates.append(os.path.join(os.path.dirname(path), mtl_path)) |
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mtl_path_candidates.append(path.replace(".obj", ".mtl")) |
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mtl_path = None |
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for candidate in mtl_path_candidates: |
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if os.path.exists(candidate): |
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mtl_path = candidate |
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break |
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metallic_path = None |
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roughness_path = None |
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if mtl_path is not None and albedo_path is None: |
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with open(mtl_path, "r") as f: |
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lines = f.readlines() |
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for line in lines: |
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split_line = line.split() |
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if len(split_line) == 0: |
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continue |
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prefix = split_line[0] |
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if "map_Kd" in prefix: |
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albedo_path = os.path.join(os.path.dirname(path), split_line[1]) |
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print(f"[load_obj] use texture from: {albedo_path}") |
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elif "map_Pm" in prefix: |
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metallic_path = os.path.join(os.path.dirname(path), split_line[1]) |
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elif "map_Pr" in prefix: |
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roughness_path = os.path.join(os.path.dirname(path), split_line[1]) |
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if albedo_path is None or not os.path.exists(albedo_path): |
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print(f"[load_obj] init empty albedo!") |
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albedo = np.ones((1024, 1024, 3), dtype=np.float32) * np.array([0.5, 0.5, 0.5]) |
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else: |
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albedo = cv2.imread(albedo_path, cv2.IMREAD_UNCHANGED) |
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albedo = cv2.cvtColor(albedo, cv2.COLOR_BGR2RGB) |
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albedo = albedo.astype(np.float32) / 255 |
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print(f"[load_obj] load texture: {albedo.shape}") |
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mesh.albedo = torch.tensor(albedo, dtype=torch.float32, device=device) |
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if metallic_path is not None and roughness_path is not None: |
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print(f"[load_obj] load metallicRoughness from: {metallic_path}, {roughness_path}") |
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metallic = cv2.imread(metallic_path, cv2.IMREAD_UNCHANGED) |
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metallic = metallic.astype(np.float32) / 255 |
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roughness = cv2.imread(roughness_path, cv2.IMREAD_UNCHANGED) |
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roughness = roughness.astype(np.float32) / 255 |
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metallicRoughness = np.stack([np.zeros_like(metallic), roughness, metallic], axis=-1) |
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mesh.metallicRoughness = torch.tensor(metallicRoughness, dtype=torch.float32, device=device).contiguous() |
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return mesh |
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@classmethod |
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def load_trimesh(cls, path, device=None): |
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"""load a mesh using ``trimesh.load()``. |
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Can load various formats like ``glb`` and serves as a fallback. |
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Note: |
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We will try to merge all meshes if the glb contains more than one, |
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but **this may cause the texture to lose**, since we only support one texture image! |
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Args: |
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path (str): path to the mesh file. |
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device (torch.device, optional): torch device. Defaults to None. |
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Returns: |
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Mesh: the loaded Mesh object. |
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""" |
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mesh = cls() |
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if device is None: |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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mesh.device = device |
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_data = trimesh.load(path) |
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if isinstance(_data, trimesh.Scene): |
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if len(_data.geometry) == 1: |
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_mesh = list(_data.geometry.values())[0] |
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else: |
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print(f"[load_trimesh] concatenating {len(_data.geometry)} meshes.") |
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_concat = [] |
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scene_graph = _data.graph.to_flattened() |
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for k, v in scene_graph.items(): |
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name = v['geometry'] |
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if name in _data.geometry and isinstance(_data.geometry[name], trimesh.Trimesh): |
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transform = v['transform'] |
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_concat.append(_data.geometry[name].apply_transform(transform)) |
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_mesh = trimesh.util.concatenate(_concat) |
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else: |
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_mesh = _data |
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|
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if _mesh.visual.kind == 'vertex': |
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vertex_colors = _mesh.visual.vertex_colors |
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vertex_colors = np.array(vertex_colors[..., :3]).astype(np.float32) / 255 |
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mesh.vc = torch.tensor(vertex_colors, dtype=torch.float32, device=device) |
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print(f"[load_trimesh] use vertex color: {mesh.vc.shape}") |
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elif _mesh.visual.kind == 'texture': |
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_material = _mesh.visual.material |
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if isinstance(_material, trimesh.visual.material.PBRMaterial): |
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texture = np.array(_material.baseColorTexture).astype(np.float32) / 255 |
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if _material.metallicRoughnessTexture is not None: |
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metallicRoughness = np.array(_material.metallicRoughnessTexture).astype(np.float32) / 255 |
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mesh.metallicRoughness = torch.tensor(metallicRoughness, dtype=torch.float32, device=device).contiguous() |
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elif isinstance(_material, trimesh.visual.material.SimpleMaterial): |
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texture = np.array(_material.to_pbr().baseColorTexture).astype(np.float32) / 255 |
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else: |
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raise NotImplementedError(f"material type {type(_material)} not supported!") |
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mesh.albedo = torch.tensor(texture[..., :3], dtype=torch.float32, device=device).contiguous() |
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print(f"[load_trimesh] load texture: {texture.shape}") |
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else: |
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texture = np.ones((1024, 1024, 3), dtype=np.float32) * np.array([0.5, 0.5, 0.5]) |
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mesh.albedo = torch.tensor(texture, dtype=torch.float32, device=device) |
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print(f"[load_trimesh] failed to load texture.") |
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vertices = _mesh.vertices |
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try: |
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texcoords = _mesh.visual.uv |
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texcoords[:, 1] = 1 - texcoords[:, 1] |
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except Exception as e: |
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texcoords = None |
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try: |
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normals = _mesh.vertex_normals |
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except Exception as e: |
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normals = None |
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faces = tfaces = nfaces = _mesh.faces |
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mesh.v = torch.tensor(vertices, dtype=torch.float32, device=device) |
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mesh.vt = ( |
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torch.tensor(texcoords, dtype=torch.float32, device=device) |
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if texcoords is not None |
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else None |
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) |
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mesh.vn = ( |
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torch.tensor(normals, dtype=torch.float32, device=device) |
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if normals is not None |
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else None |
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) |
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mesh.f = torch.tensor(faces, dtype=torch.int32, device=device) |
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mesh.ft = ( |
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torch.tensor(tfaces, dtype=torch.int32, device=device) |
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if texcoords is not None |
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else None |
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) |
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mesh.fn = ( |
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torch.tensor(nfaces, dtype=torch.int32, device=device) |
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if normals is not None |
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else None |
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) |
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return mesh |
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|
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def sample_surface(self, count: int): |
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"""sample points on the surface of the mesh. |
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Args: |
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count (int): number of points to sample. |
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Returns: |
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torch.Tensor: the sampled points, float [count, 3]. |
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""" |
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_mesh = trimesh.Trimesh(vertices=self.v.detach().cpu().numpy(), faces=self.f.detach().cpu().numpy()) |
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points, face_idx = trimesh.sample.sample_surface(_mesh, count) |
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points = torch.from_numpy(points).float().to(self.device) |
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return points |
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|
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def aabb(self): |
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"""get the axis-aligned bounding box of the mesh. |
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|
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Returns: |
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Tuple[torch.Tensor]: the min xyz and max xyz of the mesh. |
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""" |
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return torch.min(self.v, dim=0).values, torch.max(self.v, dim=0).values |
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@torch.no_grad() |
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def auto_size(self, bound=0.9): |
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"""auto resize the mesh. |
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|
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Args: |
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bound (float, optional): resizing into ``[-bound, bound]^3``. Defaults to 0.9. |
|
""" |
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vmin, vmax = self.aabb() |
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self.ori_center = (vmax + vmin) / 2 |
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self.ori_scale = 2 * bound / torch.max(vmax - vmin).item() |
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self.v = (self.v - self.ori_center) * self.ori_scale |
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|
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def auto_normal(self): |
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"""auto calculate the vertex normals. |
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""" |
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i0, i1, i2 = self.f[:, 0].long(), self.f[:, 1].long(), self.f[:, 2].long() |
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v0, v1, v2 = self.v[i0, :], self.v[i1, :], self.v[i2, :] |
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|
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face_normals = torch.cross(v1 - v0, v2 - v0) |
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|
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vn = torch.zeros_like(self.v) |
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vn.scatter_add_(0, i0[:, None].repeat(1, 3), face_normals) |
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vn.scatter_add_(0, i1[:, None].repeat(1, 3), face_normals) |
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vn.scatter_add_(0, i2[:, None].repeat(1, 3), face_normals) |
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|
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|
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vn = torch.where( |
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dot(vn, vn) > 1e-20, |
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vn, |
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torch.tensor([0.0, 0.0, 1.0], dtype=torch.float32, device=vn.device), |
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) |
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vn = safe_normalize(vn) |
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|
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self.vn = vn |
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self.fn = self.f |
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|
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def auto_uv(self, cache_path=None, vmap=True): |
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"""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. |
|
""" |
|
|
|
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() |
|
|
|
atlas.generate(chart_options=chart_options) |
|
vmapping, ft_np, vt_np = atlas[0] |
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|
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|
|
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 |
|
|
|
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. |
|
""" |
|
|
|
|
|
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) |
|
|
|
|
|
gltf = pygltflib.GLTF2( |
|
scene=0, |
|
scenes=[pygltflib.Scene(nodes=[0])], |
|
nodes=[pygltflib.Node(mesh=0)], |
|
meshes=[pygltflib.Mesh(primitives=[pygltflib.Primitive( |
|
|
|
attributes=pygltflib.Attributes( |
|
POSITION=1, |
|
), |
|
indices=0, |
|
)])], |
|
buffers=[ |
|
pygltflib.Buffer(byteLength=len(f_np_blob) + len(v_np_blob)) |
|
], |
|
|
|
bufferViews=[ |
|
|
|
pygltflib.BufferView( |
|
buffer=0, |
|
byteLength=len(f_np_blob), |
|
target=pygltflib.ELEMENT_ARRAY_BUFFER, |
|
), |
|
|
|
pygltflib.BufferView( |
|
buffer=0, |
|
byteOffset=len(f_np_blob), |
|
byteLength=len(v_np_blob), |
|
byteStride=12, |
|
target=pygltflib.ARRAY_BUFFER, |
|
), |
|
], |
|
accessors=[ |
|
|
|
pygltflib.Accessor( |
|
bufferView=0, |
|
componentType=pygltflib.UNSIGNED_INT, |
|
count=f_np.size, |
|
type=pygltflib.SCALAR, |
|
max=[int(f_np.max())], |
|
min=[int(f_np.min())], |
|
), |
|
|
|
pygltflib.Accessor( |
|
bufferView=1, |
|
componentType=pygltflib.FLOAT, |
|
count=len(v_np), |
|
type=pygltflib.VEC3, |
|
max=v_np.max(axis=0).tolist(), |
|
min=v_np.min(axis=0).tolist(), |
|
), |
|
], |
|
) |
|
|
|
|
|
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() |
|
|
|
|
|
gltf.meshes[0].primitives[0].attributes.TEXCOORD_0 = 2 |
|
gltf.meshes[0].primitives[0].material = 0 |
|
|
|
|
|
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")) |
|
|
|
|
|
gltf.bufferViews.append( |
|
|
|
pygltflib.BufferView( |
|
buffer=0, |
|
byteOffset=byteOffset, |
|
byteLength=len(vt_np_blob), |
|
byteStride=8, |
|
target=pygltflib.ARRAY_BUFFER, |
|
) |
|
) |
|
|
|
gltf.accessors.append( |
|
|
|
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( |
|
|
|
pygltflib.BufferView( |
|
buffer=0, |
|
byteOffset=byteOffset, |
|
byteLength=len(albedo_blob), |
|
) |
|
) |
|
|
|
blob += albedo_blob |
|
byteOffset += len(albedo_blob) |
|
|
|
gltf.buffers[0].byteLength = byteOffset |
|
|
|
|
|
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() |
|
|
|
|
|
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")) |
|
|
|
|
|
gltf.bufferViews.append( |
|
|
|
pygltflib.BufferView( |
|
buffer=0, |
|
byteOffset=byteOffset, |
|
byteLength=len(metallicRoughness_blob), |
|
) |
|
) |
|
|
|
blob += metallicRoughness_blob |
|
byteOffset += len(metallicRoughness_blob) |
|
|
|
gltf.buffers[0].byteLength = byteOffset |
|
|
|
|
|
|
|
gltf.set_binary_blob(blob) |
|
|
|
|
|
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: |
|
|
|
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]) |
|
|
|
|