clean scene 7

app.py

@@ -1,19 +1,5 @@
-
-
 import os
 import subprocess
-
-# Убираем pyenv, если вдруг остался .python-version
-os.environ.pop("PYENV_VERSION", None)
-
-# Установка зависимостей
-subprocess.run(["pip", "install", "torch", "wheel"], check=True)
-subprocess.run([
-    "pip", "install", "--no-build-isolation", 
-    "diso@git+https://github.com/SarahWeiii/diso.git"
-], check=True)
-
-# Импорты
 import gradio as gr
 import uuid
 import torch
@@ -21,13 +7,24 @@ import zipfile
 import requests
 import traceback
 import trimesh
-print("Trimesh version:", trimesh.__version__)
-
+from trimesh.exchange.gltf import export_glb
 
 from inference_triposg import run_triposg
 from triposg.pipelines.pipeline_triposg import TripoSGPipeline
 from briarmbg import BriaRMBG
 
+# Убираем pyenv
+os.environ.pop("PYENV_VERSION", None)
+
+# Установка зависимостей
+subprocess.run(["pip", "install", "torch", "wheel"], stdout=subprocess.DEVNULL)
+subprocess.run([
+    "pip", "install", "--no-build-isolation",
+    "diso@git+https://github.com/SarahWeiii/diso.git"
+], stdout=subprocess.DEVNULL)
+
+print("Trimesh version:", trimesh.__version__)
+
 # Настройки устройства
 device = "cuda" if torch.cuda.is_available() else "cpu"
 dtype = torch.float16 if device == "cuda" else torch.float32
@@ -61,26 +58,15 @@ rmbg_net = BriaRMBG.from_pretrained(rmbg_path).to(device)
 rmbg_net.eval()
 
 # Генерация .glb
-# def generate(image_path):
 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=25,
-        #     guidance_scale=5.0,
-        #     faces=-1,
-        # )
         mesh = run_triposg(
             pipe=pipe,
             image_input=image_path,
@@ -91,59 +77,25 @@ def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25):
             faces=int(face_number),
         )
 
-        # if mesh is None:
-        #     raise ValueError("Mesh generation failed")
-
-        # mesh.export(output_path)
-        # print(f"[DEBUG] Mesh saved to {output_path}")
-
-        # return output_path if os.path.exists(output_path) else "Error: output file not found"
-
-        
-        # if mesh is None:
-        #     raise ValueError("Mesh generation failed")
-
-        # # Убираем визуал, метаданные, обертки
-        # mesh.visual = None
-        # mesh.metadata.clear()
-        # mesh.name = "endless_tools"
-
-        # # Экспорт только геометрии
-        # 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 "Error: output file not found"
-
         if mesh is None:
             raise ValueError("Mesh generation returned None")
 
         # Очистка визуала, метаданных и имени
-        # mesh.visual = None
+        mesh.visual = None
         mesh.metadata.clear()
         mesh.name = "geometry_0"
 
-        glb_data = mesh.export(file_type="glb")
+        # Экспорт в GLB без scene/world
+        glb_data = export_glb(mesh)
         with open(output_path, "wb") as f:
             f.write(glb_data)
 
-        # Экспорт .glb вручную (иначе Trimesh добавляет сцену)
-        # 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)
-    #     return f"Error: {e}"
+
     except Exception as e:
-        # import traceback
         print("[ERROR]", e)
-        traceback.print_exc()  # ← выведет полную трассировку в логи
+        traceback.print_exc()
         return f"Error: {e}"
 
 # Интерфейс Gradio
@@ -157,7 +109,3 @@ demo = gr.Interface(
 
 # Запуск
 demo.launch()
-
-
-
-

app_backlog.py

@@ -0,0 +1,166 @@
+
+
+import os
+import subprocess
+
+# Убираем pyenv, если вдруг остался .python-version
+os.environ.pop("PYENV_VERSION", None)
+
+# Установка зависимостей
+subprocess.run(["pip", "install", "torch", "wheel"], check=True)
+subprocess.run([
+    "pip", "install", "--no-build-isolation", 
+    "diso@git+https://github.com/SarahWeiii/diso.git"
+], check=True)
+
+# Импорты
+import gradio as gr
+import uuid
+import torch
+import zipfile
+import requests
+import traceback
+import trimesh
+from trimesh.exchange.gltf import export_glb 
+
+print("Trimesh version:", trimesh.__version__)
+
+
+from inference_triposg import run_triposg
+from triposg.pipelines.pipeline_triposg import TripoSGPipeline
+from briarmbg import BriaRMBG
+
+# Настройки устройства
+device = "cuda" if torch.cuda.is_available() else "cpu"
+dtype = torch.float16 if device == "cuda" else torch.float32
+
+# Загрузка весов
+weights_dir = "pretrained_weights"
+triposg_path = os.path.join(weights_dir, "TripoSG")
+rmbg_path = os.path.join(weights_dir, "RMBG-1.4")
+
+if not (os.path.exists(triposg_path) and os.path.exists(rmbg_path)):
+    print("📦 Downloading pretrained weights...")
+    url = "https://huggingface.co/datasets/endlesstools/pretrained-assets/resolve/main/pretrained_models.zip"
+    zip_path = "pretrained_models.zip"
+
+    with requests.get(url, stream=True) as r:
+        r.raise_for_status()
+        with open(zip_path, "wb") as f:
+            for chunk in r.iter_content(chunk_size=8192):
+                f.write(chunk)
+
+    print("📦 Extracting weights...")
+    with zipfile.ZipFile(zip_path, "r") as zip_ref:
+        zip_ref.extractall(weights_dir)
+
+    os.remove(zip_path)
+    print("✅ Weights ready.")
+
+# Загрузка моделей
+pipe = TripoSGPipeline.from_pretrained(triposg_path).to(device, dtype)
+rmbg_net = BriaRMBG.from_pretrained(rmbg_path).to(device)
+rmbg_net.eval()
+
+# Генерация .glb
+# def generate(image_path):
+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=25,
+        #     guidance_scale=5.0,
+        #     faces=-1,
+        # )
+        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:
+        #     raise ValueError("Mesh generation failed")
+
+        # mesh.export(output_path)
+        # print(f"[DEBUG] Mesh saved to {output_path}")
+
+        # return output_path if os.path.exists(output_path) else "Error: output file not found"
+
+        
+        # if mesh is None:
+        #     raise ValueError("Mesh generation failed")
+
+        # # Убираем визуал, метаданные, обертки
+        # mesh.visual = None
+        # mesh.metadata.clear()
+        # mesh.name = "endless_tools"
+
+        # # Экспорт только геометрии
+        # 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 "Error: output file not found"
+
+        if mesh is None:
+            raise ValueError("Mesh generation returned None")
+
+        # Очистка визуала, метаданных и имени
+        mesh.visual = None
+        mesh.metadata.clear()
+        mesh.name = "geometry_0"
+
+        # glb_data = mesh.export(file_type="glb")
+        glb_data = export_glb(mesh)
+        with open(output_path, "wb") as f:
+            f.write(glb_data)
+
+        # Экспорт .glb вручную (иначе Trimesh добавляет сцену)
+        # 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)
+    #     return f"Error: {e}"
+    except Exception as e:
+        # import traceback
+        print("[ERROR]", e)
+        traceback.print_exc()  # ← выведет полную трассировку в логи
+        return f"Error: {e}"
+
+# Интерфейс Gradio
+demo = gr.Interface(
+    fn=generate,
+    inputs=gr.Image(type="filepath", label="Upload image"),
+    outputs=gr.File(label="Download .glb"),
+    title="TripoSG Image to 3D",
+    description="Upload an image to generate a 3D model (.glb)",
+)
+
+# Запуск
+demo.launch()
+
+
+
+