Suppress third-party warnings and add render diagnostics

app.py

@@ -1,3 +1,8 @@
+import warnings
+warnings.filterwarnings("ignore", message=".*torch.distributed.reduce_op.*")
+warnings.filterwarnings("ignore", message=".*torch.cuda.amp.autocast.*")
+warnings.filterwarnings("ignore", message=".*Default grid_sample and affine_grid behavior.*")
+
 import gradio as gr
 from gradio_client import Client, handle_file
 import spaces
@@ -510,6 +515,14 @@ def image_to_3d(
     images = [image[0] for image in multiimages]
     processed_images = [preprocess_image(img) for img in images]
 
+    # Debug: save preprocessed images and log stats
+    for i, img in enumerate(processed_images):
+        arr = np.array(img)
+        print(f"[DEBUG] Preprocessed image {i}: mode={img.mode}, size={img.size}, "
+              f"dtype={arr.dtype}, min={arr.min()}, max={arr.max()}, mean={arr.mean():.1f}")
+        img.save(os.path.join(TMP_DIR, f'debug_preprocessed_{i}.png'))
+    print(f"[DEBUG] Pipeline params: mode={multiimage_algo}, tex_mode={tex_multiimage_algo}")
+
     # --- Sampling ---
     outputs, latents = pipeline.run_multi_image(
         processed_images,
@@ -545,6 +558,15 @@ def image_to_3d(
     mesh = outputs[0]
     mesh.simplify(16777216)  # nvdiffrast limit
     images = render_utils.render_snapshot(mesh, resolution=1024, r=2, fov=36, nviews=STEPS, envmap=envmap)
+
+    # Debug: save base_color render and log stats for all render modes
+    for key in images:
+        arr = images[key][0]  # first view
+        print(f"[DEBUG] Render '{key}': shape={arr.shape}, min={arr.min()}, max={arr.max()}, mean={arr.mean():.1f}")
+    # Save base_color and shaded_forest for inspection
+    Image.fromarray(images['base_color'][0]).save(os.path.join(TMP_DIR, 'debug_base_color.png'))
+    Image.fromarray(images['shaded_forest'][0]).save(os.path.join(TMP_DIR, 'debug_shaded_forest.png'))
+
     state = pack_state(latents)
     torch.cuda.empty_cache()