add octree depth controls fix 1

app.py

@@ -67,9 +67,10 @@ rmbg_net = BriaRMBG.from_pretrained(rmbg_path).to(device)
 rmbg_net.eval()
 
 
-# def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25):
-def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25, octree_depth=9):
-    print(f"[INPUT] face_number={face_number}, guidance_scale={guidance_scale}, num_steps={num_steps}, octree_depth={octree_depth}")# 👈 добавлено
+def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25):
+# def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25, octree_depth=9):
+    # print(f"[INPUT] face_number={face_number}, guidance_scale={guidance_scale}, num_steps={num_steps}, octree_depth={octree_depth}")# 👈 добавлено
+    print(f"[INPUT] face_number={face_number}, guidance_scale={guidance_scale}, num_steps={num_steps}")# 👈 добавлено
     print("[API CALL] image_path received:", image_path)
     print("[API CALL] File exists:", os.path.exists(image_path))
 
@@ -86,7 +87,7 @@ def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25, oc
             num_inference_steps=int(num_steps),
             guidance_scale=float(guidance_scale),
             faces=int(face_number),
-            octree_depth=int(octree_depth), # 👈 добавлено
+            # octree_depth=int(octree_depth), # 👈 добавлено
         )
 
         if mesh is None or mesh.vertices.shape[0] == 0 or mesh.faces.shape[0] == 0:
@@ -128,14 +129,14 @@ def generate(image_path, face_number=50000, guidance_scale=5.0, num_steps=25, oc
 # Интерфейс Gradio
 demo = gr.Interface(
     fn=generate,
-    # inputs=gr.Image(type="filepath", label="Upload image"),
-    inputs=[
-        gr.Image(type="filepath", label="Upload image"),
-        gr.Slider(10000, 150000, step=10000, value=50000, label="Face count"),
-        gr.Slider(1.0, 10.0, step=0.5, value=5.0, label="Guidance Scale"),
-        gr.Slider(10, 100, step=5, value=25, label="Steps"),
-        gr.Slider(6, 10, step=1, value=9, label="Octree Depth"),
-    ], # 👈 добавлено
+    inputs=gr.Image(type="filepath", label="Upload image"),
+    # inputs=[
+    #     gr.Image(type="filepath", label="Upload image"),
+    #     gr.Slider(10000, 150000, step=10000, value=50000, label="Face count"),
+    #     gr.Slider(1.0, 10.0, step=0.5, value=5.0, label="Guidance Scale"),
+    #     gr.Slider(10, 100, step=5, value=25, label="Steps"),
+    #     gr.Slider(6, 10, step=1, value=9, label="Octree Depth"),
+    # ], # 👈 добавлено
     outputs=gr.File(label="Download .glb"),
     title="TripoSG Image to 3D",
     description="Upload an image to generate a 3D model (.glb)",

inference_triposg.py

@@ -54,7 +54,7 @@ def run_triposg(
     num_inference_steps: int = 50,
     guidance_scale: float = 7.0,
     faces: int = -1,
-    octree_depth: int = 9, # 👈 добавлено
+    # octree_depth: int = 9, # 👈 добавлено
 ) -> trimesh.Scene:
     print("[DEBUG] Preparing image...")
     img_pil = prepare_image(image_input, bg_color=np.array([1.0, 1.0, 1.0]), rmbg_net=rmbg_net)
@@ -65,7 +65,7 @@ def run_triposg(
         generator=torch.Generator(device=pipe.device).manual_seed(seed),
         num_inference_steps=num_inference_steps,
         guidance_scale=guidance_scale,
-        flash_octree_depth=octree_depth, # 👈 добавлено
+        # flash_octree_depth=octree_depth, # 👈 добавлено
     ).samples[0]
 
     print("[DEBUG] TripoSG output keys:", type(outputs), outputs[0].shape, outputs[1].shape)