# Open Source Model Licensed under the Apache License Version 2.0 # and Other Licenses of the Third-Party Components therein: # The below Model in this distribution may have been modified by THL A29 Limited # ("Tencent Modifications"). All Tencent Modifications are Copyright (C) 2024 THL A29 Limited. # Copyright (C) 2024 THL A29 Limited, a Tencent company. All rights reserved. # The below software and/or models in this distribution may have been # modified by THL A29 Limited ("Tencent Modifications"). # All Tencent Modifications are Copyright (C) THL A29 Limited. # Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENT # except for the third-party components listed below. # Hunyuan 3D does not impose any additional limitations beyond what is outlined # in the repsective licenses of these third-party components. # Users must comply with all terms and conditions of original licenses of these third-party # components and must ensure that the usage of the third party components adheres to # all relevant laws and regulations. # For avoidance of doubts, Hunyuan 3D means the large language models and # their software and algorithms, including trained model weights, parameters (including # optimizer states), machine-learning model code, inference-enabling code, training-enabling code, # fine-tuning enabling code and other elements of the foregoing made publicly available # by Tencent in accordance with TENCENT HUNYUAN COMMUNITY LICENSE AGREEMENT. import logging import os import numpy as np import torch from PIL import Image from .differentiable_renderer.mesh_render import MeshRender from .utils.dehighlight_utils import Light_Shadow_Remover from .utils.multiview_utils import Multiview_Diffusion_Net from .utils.uv_warp_utils import mesh_uv_wrap logger = logging.getLogger(__name__) class Hunyuan3DTexGenConfig: def __init__(self, light_remover_ckpt_path, multiview_ckpt_path): self.device = 'cuda' self.light_remover_ckpt_path = light_remover_ckpt_path self.multiview_ckpt_path = multiview_ckpt_path self.candidate_camera_azims = [0, 90, 180, 270, 0, 180] self.candidate_camera_elevs = [0, 0, 0, 0, 90, -90] self.candidate_view_weights = [1, 0.1, 0.5, 0.1, 0.05, 0.05] self.render_size = 2048 self.texture_size = 1024 self.bake_exp = 4 self.merge_method = 'fast' class Hunyuan3DPaintPipeline: @classmethod def from_pretrained(cls, model_path): original_model_path = model_path if not os.path.exists(model_path): # try local path base_dir = os.environ.get('HY3DGEN_MODELS', '~/.cache/hy3dgen') model_path = os.path.expanduser(os.path.join(base_dir, model_path)) delight_model_path = os.path.join(model_path, 'hunyuan3d-delight-v2-0') multiview_model_path = os.path.join(model_path, 'hunyuan3d-paint-v2-0') if not os.path.exists(delight_model_path) or not os.path.exists(multiview_model_path): try: import huggingface_hub # download from huggingface model_path = huggingface_hub.snapshot_download(repo_id=original_model_path) delight_model_path = os.path.join(model_path, 'hunyuan3d-delight-v2-0') multiview_model_path = os.path.join(model_path, 'hunyuan3d-paint-v2-0') return cls(Hunyuan3DTexGenConfig(delight_model_path, multiview_model_path)) except ImportError: logger.warning( "You need to install HuggingFace Hub to load models from the hub." ) raise RuntimeError(f"Model path {model_path} not found") else: return cls(Hunyuan3DTexGenConfig(delight_model_path, multiview_model_path)) raise FileNotFoundError(f"Model path {original_model_path} not found and we could not find it at huggingface") def __init__(self, config): self.config = config self.models = {} self.render = MeshRender( default_resolution=self.config.render_size, texture_size=self.config.texture_size) self.load_models() def load_models(self): # empty cude cache torch.cuda.empty_cache() # Load model self.models['delight_model'] = Light_Shadow_Remover(self.config) self.models['multiview_model'] = Multiview_Diffusion_Net(self.config) def render_normal_multiview(self, camera_elevs, camera_azims, use_abs_coor=True): normal_maps = [] for elev, azim in zip(camera_elevs, camera_azims): normal_map = self.render.render_normal( elev, azim, use_abs_coor=use_abs_coor, return_type='pl') normal_maps.append(normal_map) return normal_maps def render_position_multiview(self, camera_elevs, camera_azims): position_maps = [] for elev, azim in zip(camera_elevs, camera_azims): position_map = self.render.render_position( elev, azim, return_type='pl') position_maps.append(position_map) return position_maps def bake_from_multiview(self, views, camera_elevs, camera_azims, view_weights, method='graphcut'): project_textures, project_weighted_cos_maps = [], [] project_boundary_maps = [] for view, camera_elev, camera_azim, weight in zip( views, camera_elevs, camera_azims, view_weights): project_texture, project_cos_map, project_boundary_map = self.render.back_project( view, camera_elev, camera_azim) project_cos_map = weight * (project_cos_map ** self.config.bake_exp) project_textures.append(project_texture) project_weighted_cos_maps.append(project_cos_map) project_boundary_maps.append(project_boundary_map) if method == 'fast': texture, ori_trust_map = self.render.fast_bake_texture( project_textures, project_weighted_cos_maps) else: raise f'no method {method}' return texture, ori_trust_map > 1E-8 def texture_inpaint(self, texture, mask): texture_np = self.render.uv_inpaint(texture, mask) texture = torch.tensor(texture_np / 255).float().to(texture.device) return texture @torch.no_grad() def __call__(self, mesh, image): if isinstance(image, str): image_prompt = Image.open(image) else: image_prompt = image image_prompt = self.models['delight_model'](image_prompt) mesh = mesh_uv_wrap(mesh) self.render.load_mesh(mesh) selected_camera_elevs, selected_camera_azims, selected_view_weights = \ self.config.candidate_camera_elevs, self.config.candidate_camera_azims, self.config.candidate_view_weights normal_maps = self.render_normal_multiview( selected_camera_elevs, selected_camera_azims, use_abs_coor=True) position_maps = self.render_position_multiview( selected_camera_elevs, selected_camera_azims) camera_info = [(((azim // 30) + 9) % 12) // {-20: 1, 0: 1, 20: 1, -90: 3, 90: 3}[ elev] + {-20: 0, 0: 12, 20: 24, -90: 36, 90: 40}[elev] for azim, elev in zip(selected_camera_azims, selected_camera_elevs)] multiviews = self.models['multiview_model'](image_prompt, normal_maps + position_maps, camera_info) for i in range(len(multiviews)): multiviews[i] = multiviews[i].resize( (self.config.render_size, self.config.render_size)) texture, mask = self.bake_from_multiview(multiviews, selected_camera_elevs, selected_camera_azims, selected_view_weights, method=self.config.merge_method) mask_np = (mask.squeeze(-1).cpu().numpy() * 255).astype(np.uint8) texture = self.texture_inpaint(texture, mask_np) self.render.set_texture(texture) textured_mesh = self.render.save_mesh() return textured_mesh