fix add normals 1

app.py

@@ -63,6 +63,51 @@ rmbg_net = BriaRMBG.from_pretrained(rmbg_path).to(device)
 rmbg_net.eval()
 
 # Генерация .glb
+# def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25):
+#     print("[API CALL] image_path received:", image_path)
+#     print("[API CALL] File exists:", os.path.exists(image_path))
+
+#     temp_id = str(uuid.uuid4())
+#     output_path = f"/tmp/{temp_id}.glb"
+#     print("[DEBUG] Generating mesh from:", image_path)
+
+#     try:
+#         mesh = run_triposg(
+#             pipe=pipe,
+#             image_input=image_path,
+#             rmbg_net=rmbg_net,
+#             seed=42,
+#             num_inference_steps=int(num_steps),
+#             guidance_scale=float(guidance_scale),
+#             faces=int(face_number),
+#         )
+
+#         if mesh is None or mesh.vertices.shape[0] == 0 or mesh.faces.shape[0] == 0:
+#             raise ValueError("Mesh generation returned an empty mesh")
+
+#         mesh = trimesh.Trimesh(vertices=mesh.vertices, faces=mesh.faces)
+#         mesh.rezero()
+#         mesh.fix_normals()
+#         mesh.apply_translation(-mesh.center_mass)  
+
+#         # Масштабируем, чтобы модель вписывалась в размер 1x1x1 
+#         # Если нужно будет подгонять под размер в Endless Tools, то можно использовать:
+#         # scale_factor = 1.0 / np.max(np.linalg.norm(mesh.vertices, axis=1))
+#         # mesh.apply_scale(scale_factor)
+
+
+#         glb_data = mesh.export(file_type='glb')
+#         with open(output_path, "wb") as f:
+#             f.write(glb_data)
+
+#         print(f"[DEBUG] Mesh saved to {output_path}")
+#         return output_path if os.path.exists(output_path) else None
+
+#     except Exception as e:
+#         print("[ERROR]", e)
+#         traceback.print_exc()
+#         return f"Error: {e}"
+
 def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25):
     print("[API CALL] image_path received:", image_path)
     print("[API CALL] File exists:", os.path.exists(image_path))
@@ -85,26 +130,22 @@ def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25):
         if mesh is None or mesh.vertices.shape[0] == 0 or mesh.faces.shape[0] == 0:
             raise ValueError("Mesh generation returned an empty mesh")
 
-        mesh = trimesh.Trimesh(vertices=mesh.vertices, faces=mesh.faces)
-        mesh.rezero()
-        mesh.fix_normals()
-        mesh.apply_translation(-mesh.center_mass)  
+        # 🔧 Пересоздаём Trimesh и гарантируем чистоту геометрии
+        mesh = trimesh.Trimesh(vertices=mesh.vertices, faces=mesh.faces, process=True)
 
-        # Безопасная очистка визуала
-        # if hasattr(mesh, "visual") and mesh.visual is not None:
-            # mesh.visual = trimesh.visual.ColorVisuals(mesh=mesh, face_colors=None) ## вот тут последнее изменение
+        # ✅ Центрируем модель
+        mesh.apply_translation(-mesh.center_mass)
 
-            ## можно вернуть это, если нужно
-            # try:
-            #     mesh.visual = None
-            # except Exception:
-            #     print("[WARN] Failed to clear visual, skipping")
+        # ✅ Масштабируем к единичному размеру (все модели ~одинаковые)
+        scale_factor = 1.0 / np.max(np.linalg.norm(mesh.vertices, axis=1))
+        mesh.apply_scale(scale_factor)
 
-        # mesh.metadata.clear()
-        # mesh.name = "endless_tools_mesh"
+        # ✅ Гарантированно пересчитываем нормали
+        mesh.fix_normals()
 
-        # Экспорт .glb
-        # glb_data = export_glb(mesh)
+        print("[DEBUG] Normals present:", mesh.has_vertex_normals)
+
+        # 💾 Сохраняем GLB
         glb_data = mesh.export(file_type='glb')
         with open(output_path, "wb") as f:
             f.write(glb_data)
@@ -117,6 +158,7 @@ def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25):
         traceback.print_exc()
         return f"Error: {e}"
 
+
 # Интерфейс Gradio
 demo = gr.Interface(
     fn=generate,