1+# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENT
2+# except for the third-party components listed below.
3+# Hunyuan 3D does not impose any additional limitations beyond what is outlined
4+# in the repsective licenses of these third-party components.
5+# Users must comply with all terms and conditions of original licenses of these third-party
6+# components and must ensure that the usage of the third party components adheres to
7+# all relevant laws and regulations.
8+9+# For avoidance of doubts, Hunyuan 3D means the large language models and
10+# their software and algorithms, including trained model weights, parameters (including
11+# optimizer states), machine-learning model code, inference-enabling code, training-enabling code,
12+# fine-tuning enabling code and other elements of the foregoing made publicly available
13+# by Tencent in accordance with TENCENT HUNYUAN COMMUNITY LICENSE AGREEMENT.
14+115"""
216A model worker executes the model.
317"""
2236from fastapi.responses import JSONResponse, FileResponse
23372438from hy3dgen.rembg import BackgroundRemover
25-from hy3dgen.shapegen import Hunyuan3DDiTFlowMatchingPipeline, FloaterRemover, DegenerateFaceRemover, FaceReducer
39+from hy3dgen.shapegen import Hunyuan3DDiTFlowMatchingPipeline, FloaterRemover, DegenerateFaceRemover, FaceReducer, \
40+ MeshSimplifier
2641from hy3dgen.texgen import Hunyuan3DPaintPipeline
2742from hy3dgen.text2image import HunyuanDiTPipeline
2843@@ -129,17 +144,31 @@ def load_image_from_base64(image):
129144130145131146class ModelWorker:
132- def __init__(self, model_path='tencent/Hunyuan3D-2', device='cuda'):
147+ def __init__(self,
148+ model_path='tencent/Hunyuan3D-2mini',
149+ tex_model_path='tencent/Hunyuan3D-2',
150+ subfolder='hunyuan3d-dit-v2-mini-turbo',
151+ device='cuda',
152+ enable_tex=False):
133153 self.model_path = model_path
134154 self.worker_id = worker_id
135155 self.device = device
136156 logger.info(f"Loading the model {model_path} on worker {worker_id} ...")
137157138158 self.rembg = BackgroundRemover()
139- self.pipeline = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained(model_path, device=device)
140- self.pipeline_t2i = HunyuanDiTPipeline('Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers-Distilled',
141- device=device)
142- self.pipeline_tex = Hunyuan3DPaintPipeline.from_pretrained(model_path)
159+ self.pipeline = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained(
160+ model_path,
161+ subfolder=subfolder,
162+ use_safetensors=True,
163+ device=device,
164+ )
165+ self.pipeline.enable_flashvdm()
166+ # self.pipeline_t2i = HunyuanDiTPipeline(
167+ # 'Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers-Distilled',
168+ # device=device
169+ # )
170+ if enable_tex:
171+ self.pipeline_tex = Hunyuan3DPaintPipeline.from_pretrained(tex_model_path)
143172144173 def get_queue_length(self):
145174 if model_semaphore is None:
@@ -174,31 +203,42 @@ def generate(self, uid, params):
174203 else:
175204 seed = params.get("seed", 1234)
176205 params['generator'] = torch.Generator(self.device).manual_seed(seed)
177- params['octree_resolution'] = params.get("octree_resolution", 256)
178- params['num_inference_steps'] = params.get("num_inference_steps", 30)
179- params['guidance_scale'] = params.get('guidance_scale', 7.5)
180- params['mc_algo'] = 'mc'
206+ params['octree_resolution'] = params.get("octree_resolution", 128)
207+ params['num_inference_steps'] = params.get("num_inference_steps", 5)
208+ params['guidance_scale'] = params.get('guidance_scale', 5.0)
209+ params['mc_algo'] = 'dmc'
210+ import time
211+ start_time = time.time()
181212 mesh = self.pipeline(**params)[0]
213+ logger.info("--- %s seconds ---" % (time.time() - start_time))
182214183215 if params.get('texture', False):
184216 mesh = FloaterRemover()(mesh)
185217 mesh = DegenerateFaceRemover()(mesh)
186218 mesh = FaceReducer()(mesh, max_facenum=params.get('face_count', 40000))
187219 mesh = self.pipeline_tex(mesh, image)
188220189- with tempfile.NamedTemporaryFile(suffix='.glb', delete=False) as temp_file:
221+ type = params.get('type', 'glb')
222+ with tempfile.NamedTemporaryFile(suffix=f'.{type}', delete=True) as temp_file:
190223 mesh.export(temp_file.name)
191224 mesh = trimesh.load(temp_file.name)
192- temp_file.close()
193- os.unlink(temp_file.name)
194- save_path = os.path.join(SAVE_DIR, f'{str(uid)}.glb')
225+ save_path = os.path.join(SAVE_DIR, f'{str(uid)}.{type}')
195226 mesh.export(save_path)
196227197228 torch.cuda.empty_cache()
198229 return save_path, uid
199230200231201232app = FastAPI()
233+from fastapi.middleware.cors import CORSMiddleware
234+235+app.add_middleware(
236+ CORSMiddleware,
237+ allow_origins=["*"], # 你可以指定允许的来源
238+ allow_credentials=True,
239+ allow_methods=["*"], # 允许所有方法
240+ allow_headers=["*"], # 允许所有头部
241+)
202242203243204244@app.post("/generate")
@@ -260,14 +300,17 @@ async def status(uid: str):
260300if __name__ == "__main__":
261301 parser = argparse.ArgumentParser()
262302 parser.add_argument("--host", type=str, default="0.0.0.0")
263- parser.add_argument("--port", type=int, default=8081)
264- parser.add_argument("--model_path", type=str, default='tencent/Hunyuan3D-2')
303+ parser.add_argument("--port", type=str, default="8081")
304+ parser.add_argument("--model_path", type=str, default='tencent/Hunyuan3D-2mini')
305+ parser.add_argument("--tex_model_path", type=str, default='tencent/Hunyuan3D-2')
265306 parser.add_argument("--device", type=str, default="cuda")
266307 parser.add_argument("--limit-model-concurrency", type=int, default=5)
308+ parser.add_argument('--enable_tex', action='store_true')
267309 args = parser.parse_args()
268310 logger.info(f"args: {args}")
269311270312 model_semaphore = asyncio.Semaphore(args.limit_model_concurrency)
271313272- worker = ModelWorker(model_path=args.model_path, device=args.device)
314+ worker = ModelWorker(model_path=args.model_path, device=args.device, enable_tex=args.enable_tex,
315+ tex_model_path=args.tex_model_path)
273316 uvicorn.run(app, host=args.host, port=args.port, log_level="info")