Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import os
 import torch
 import time
@@ -14,7 +15,7 @@ from huggingface_hub import snapshot_download
 from flask_cors import CORS
 import numpy as np
 import trimesh
-from diffusers import DiffusionPipeline
+from diffusers import Hunyuan3DDiTPipeline
 
 os.environ["CUDA_VISIBLE_DEVICES"] = ""
 torch.set_default_device("cpu")
@@ -41,12 +42,12 @@ app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
 app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024
 
 processing_jobs = {}
-zero123_pipeline = None
+hunyuan_pipeline = None
 model_loaded = False
 model_loading = False
 
 TIMEOUT_SECONDS = 300
-MAX_DIMENSION = 256
+MAX_DIMENSION = 512  # Hunyuan3D-1.0 uses 512x512 inputs
 
 class TimeoutError(Exception):
     pass
@@ -87,27 +88,27 @@ def preprocess_image(image_path):
         with Image.open(image_path) as img:
             if img.mode == 'RGBA':
                 img = img.convert('RGB')
-            img = img.resize((256, 256), Image.LANCZOS)
+            img = img.resize((512, 512), Image.LANCZOS)
             return img
     except Exception as e:
         raise Exception(f"Error preprocessing image: {str(e)}")
 
 def load_model():
-    global zero123_pipeline, model_loaded, model_loading
+    global hunyuan_pipeline, model_loaded, model_loading
     
     if model_loaded:
-        return zero123_pipeline
+        return hunyuan_pipeline
     
     if model_loading:
         while model_loading and not model_loaded:
             time.sleep(0.5)
-        return zero123_pipeline
+        return hunyuan_pipeline
     
     try:
         model_loading = True
-        print("Loading Zero123++...")
+        print("Loading Hunyuan3D-1.0 Lite...")
         
-        model_name = "sudo-ai/zero123plus-v1.2"
+        model_name = "tencent/Hunyuan3D-1"
         
         max_retries = 3
         retry_delay = 5
@@ -127,16 +128,17 @@ def load_model():
                 else:
                     raise
         
-        zero123_pipeline = DiffusionPipeline.from_pretrained(
+        hunyuan_pipeline = Hunyuan3DDiTPipeline.from_pretrained(
             model_name,
+            subfolder="lite",
             cache_dir=CACHE_DIR,
             torch_dtype=torch.float32,
         )
-        zero123_pipeline.to("cpu")
+        hunyuan_pipeline.to("cpu")
         
         model_loaded = True
-        print("Zero123++ loaded successfully on CPU")
-        return zero123_pipeline
+        print("Hunyuan3D-1.0 Lite loaded successfully on CPU")
+        return hunyuan_pipeline
     
     except Exception as e:
         print(f"Error loading model: {str(e)}")
@@ -147,13 +149,13 @@ def load_model():
 
 def generate_3d_model(image, detail_level):
     try:
-        num_steps = {'low': 30, 'medium': 50, 'high': 75}
+        num_steps = {'low': 20, 'medium': 30, 'high': 50}
         steps = num_steps[detail_level]
         
         with torch.no_grad():
-            result = zero123_pipeline(image, num_inference_steps=steps)
+            result = hunyuan_pipeline(image, num_inference_steps=steps, max_faces_num=20000)
         
-        mesh = result.meshes[0]
+        mesh = result[0]  # Hunyuan3D returns a trimesh object
         vertices = np.array(mesh.vertices)
         faces = np.array(mesh.faces)
         vertex_colors = np.array(mesh.vertex_colors) if mesh.vertex_colors is not None else None
@@ -174,7 +176,7 @@ def generate_3d_model(image, detail_level):
 def health_check():
     return jsonify({
         "status": "healthy",
-        "model": "Zero123++",
+        "model": "Hunyuan3D-1.0 Lite",
         "device": "cpu"
     }), 200
 
@@ -414,7 +416,7 @@ def model_info(job_id):
 @app.route('/', methods=['GET'])
 def index():
     return jsonify({
-        "message": "Image to 3D API (Zero123++)",
+        "message": "Image to 3D API (Hunyuan3D-1.0 Lite)",
         "endpoints": [
             "/convert",
             "/progress/<job_id>",
@@ -426,10 +428,10 @@ def index():
             "output_format": "glb or obj",
             "detail_level": "low, medium, or high"
         },
-        "description": "Creates 3D models from 2D images using Zero123++."
+        "description": "Creates 3D models from 2D images using Hunyuan3D-1.0 Lite."
     }), 200
 
 if __name__ == '__main__':
     cleanup_old_jobs()
     port = int(os.environ.get('PORT', 7860))
-    app.run(host='0.0.0.0', port=port)
+    app.run(host='0.0.0.0', port=port)