Patch Gradio api_info to ignore schema parsing errors

app.py

@@ -490,7 +490,55 @@ def convert_image_to_stl(
             final_min, final_max, final_range, final_std
         )
         
+        # Detect and flatten background to base level
+        # This prevents the background from creating unwanted 3D structure
+        # Background is typically the most common/brightest value
+        background_threshold = 0.85  # Pixels above this are considered background
+        background_mask = normalized_depth >= background_threshold
+        
+        if np.any(background_mask):
+            background_count = np.sum(background_mask)
+            total_pixels = normalized_depth.size
+            background_ratio = background_count / total_pixels
+            logger.info(
+                "Detected background: %.1f%% of pixels above threshold %.2f",
+                background_ratio * 100, background_threshold
+            )
+            
+            # Set background pixels to 0 (base level)
+            normalized_depth[background_mask] = 0.0
+            
+            # Re-normalize non-background pixels to use full height range
+            non_bg_mask = ~background_mask
+            if np.any(non_bg_mask):
+                non_bg_values = normalized_depth[non_bg_mask]
+                if len(non_bg_values) > 0:
+                    non_bg_min = float(non_bg_values.min())
+                    non_bg_max = float(non_bg_values.max())
+                    if non_bg_max - non_bg_min > 1e-8:
+                        # Scale non-background to [0, 1] range
+                        normalized_depth[non_bg_mask] = (
+                            (non_bg_values - non_bg_min) / (non_bg_max - non_bg_min)
+                        )
+                    logger.info(
+                        "Re-normalized content area: min=%.4f, max=%.4f",
+                        float(normalized_depth[non_bg_mask].min()),
+                        float(normalized_depth[non_bg_mask].max())
+                    )
+        
+        # Final statistics after background removal
+        final_min = float(normalized_depth.min())
+        final_max = float(normalized_depth.max())
+        final_range = final_max - final_min
+        final_std = float(np.std(normalized_depth))
+        
+        logger.info(
+            "After background removal: min=%.4f, max=%.4f, range=%.4f, std=%.4f",
+            final_min, final_max, final_range, final_std
+        )
+        
         # Calculate expected z-range in the final mesh
+        # Background will be at base_height, content will be above
         expected_z_min = final_min * height_scale_val + base_thickness_val
         expected_z_max = final_max * height_scale_val + base_thickness_val
         expected_z_range = expected_z_max - expected_z_min