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app.py

@@ -266,6 +266,87 @@ def reconstruct_objects(image: np.ndarray):
         print(tb)
         return None, None, f"Error:\n{tb[-1500:]}"
 
+
+@spaces.GPU(duration=240)
+def test_sam3d_only(image: np.ndarray):
+    """Test SAM3D reconstruction with center-crop mask (no SAM2)."""
+    if image is None:
+        return None, None, "No image"
+    try:
+        import torch, time, gc
+        t0 = time.time()
+        print(f"GPU: {torch.cuda.get_device_name()}, VRAM: {torch.cuda.memory_allocated()/1e9:.1f}GB")
+
+        image_np = np.array(image) if not isinstance(image, np.ndarray) else image
+        h, w = image_np.shape[:2]
+
+        # Create a center mask (middle 60% of image)
+        mask = np.zeros((h, w), dtype=bool)
+        y1, y2 = int(h * 0.2), int(h * 0.8)
+        x1, x2 = int(w * 0.2), int(w * 0.8)
+        mask[y1:y2, x1:x2] = True
+
+        preview = image_np.copy()
+        preview[mask] = (preview[mask] * 0.5 + np.array([0, 255, 0]) * 0.5).astype(np.uint8)
+        print(f"  Mask created: {mask.sum()} pixels ({time.time()-t0:.0f}s)")
+
+        from inference import Inference
+        print(f"  Loading SAM3D... VRAM: {torch.cuda.memory_allocated()/1e9:.1f}GB")
+        sam3d = Inference(CONFIG_PATH, compile=False)
+        print(f"  SAM3D loaded ({time.time()-t0:.0f}s, VRAM: {torch.cuda.memory_allocated()/1e9:.1f}GB)")
+
+        print(f"  Running reconstruction...")
+        result = sam3d(image=image_np, mask=mask, seed=42)
+        print(f"  Done ({time.time()-t0:.0f}s, VRAM: {torch.cuda.memory_allocated()/1e9:.1f}GB)")
+
+        if result is None:
+            return None, preview, "Reconstruction returned None"
+
+        import tempfile
+        od = tempfile.mkdtemp()
+        glb = f"{od}/object.glb"
+
+        gs = None
+        if isinstance(result, dict):
+            for k in ("gs", "gaussian", "gaussians", "scene"):
+                v = result.get(k)
+                if v is not None:
+                    gs = v[0] if isinstance(v, (list, tuple)) else v
+                    break
+
+        if gs is not None and hasattr(gs, "save_ply"):
+            ply = f"{od}/temp.ply"
+            gs.save_ply(ply)
+            import open3d as o3d
+            pcd = o3d.io.read_point_cloud(ply)
+            pcd.estimate_normals()
+            mesh, _ = o3d.geometry.TriangleMesh.create_from_point_cloud_poisson(pcd, depth=8)
+            o3d.io.write_triangle_mesh(glb, mesh)
+        elif gs is not None and hasattr(gs, "_xyz"):
+            import open3d as o3d
+            pcd = o3d.geometry.PointCloud()
+            pcd.points = o3d.utility.Vector3dVector(gs._xyz.detach().cpu().numpy())
+            pcd.estimate_normals()
+            mesh, _ = o3d.geometry.TriangleMesh.create_from_point_cloud_poisson(pcd, depth=8)
+            o3d.io.write_triangle_mesh(glb, mesh)
+        else:
+            keys = list(result.keys()) if isinstance(result, dict) else dir(result)
+            return None, preview, f"Cannot extract 3D. Keys: {keys}"
+
+        import trimesh
+        n = 0
+        try:
+            n = len(trimesh.load(glb, force="mesh").faces)
+        except: pass
+        elapsed = int(time.time() - t0)
+        return glb, preview, f"OK: {n:,} faces ({elapsed}s)"
+    except Exception as e:
+        import traceback
+        tb = traceback.format_exc()
+        print(tb)
+        return None, None, f"Error:\n{tb[-1500:]}"
+
+
 # --- UI ---
 with gr.Blocks(title="SAM 3D Objects") as demo:
     gr.Markdown("# SAM 3D Objects\nImage → 3D (GLB). SAM2 detection + SAM3D reconstruction.")
@@ -282,6 +363,17 @@ with gr.Blocks(title="SAM 3D Objects") as demo:
             dl = gr.File(label="Download GLB")
         btn.click(reconstruct_objects, inputs=[inp], outputs=[m3d, prev, stat])
         m3d.change(lambda x: x, inputs=[m3d], outputs=[dl])
+    with gr.Tab("Test SAM3D Only"):
+        with gr.Row():
+            with gr.Column():
+                tinp = gr.Image(label="Input", type="numpy")
+                tbtn = gr.Button("Test SAM3D (no SAM2)", variant="primary")
+            with gr.Column():
+                tprev = gr.Image(label="Mask Preview", type="numpy", interactive=False)
+                tstat = gr.Textbox(label="Status")
+        with gr.Row():
+            tm3d = gr.Model3D(label="3D Preview")
+        tbtn.click(test_sam3d_only, inputs=[tinp], outputs=[tm3d, tprev, tstat])
     with gr.Tab("Diagnose"):
         dbtn = gr.Button("Diagnose GPU & Modules")
         dout = gr.Textbox(lines=15)