Update

.gitignore

@@ -1 +1,2 @@
-.venv/
+.venv/
+sample_images/

app.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import shutil
 import sys
 from pathlib import Path
 from typing import NamedTuple
@@ -12,7 +13,10 @@ if _REPO_ROOT not in sys.path:
     sys.path.insert(0, str(_REPO_ROOT))
 
 _GRADIO_DIR = Path(__file__).resolve().parent
-import spaces
+try:
+    import spaces
+except ModuleNotFoundError:
+    spaces = None
 import gradio as gr
 import numpy as np
 import torch
@@ -73,16 +77,28 @@ def _get_assets() -> HFAssets:
     return _cached_assets
 
 
+# Local copy of sample images under cwd so Gradio never needs allowed_paths for examples
+_SAMPLE_IMAGES_COPY_DIR: Path | None = None
+
+
 def _get_sample_image_paths() -> list[str]:
-    """Return sorted paths of sample images from the downloaded assets."""
+    """Return paths of sample images under cwd (copied from HF cache) so Gradio can use them without allowed_paths."""
+    global _SAMPLE_IMAGES_COPY_DIR
     assets = _get_assets()
-    if not assets.sample_images_dir.is_dir():
+    src = assets.sample_images_dir
+    if not src.is_dir():
         return []
-    paths = [
-        str(p)
-        for p in sorted(assets.sample_images_dir.iterdir())
-        if p.is_file() and p.suffix.lower() in IMAGE_EXTENSIONS
-    ]
+    dest = _GRADIO_DIR / "sample_images"
+    dest.mkdir(parents=True, exist_ok=True)
+    paths = []
+    for p in sorted(src.iterdir()):
+        if not p.is_file() or p.suffix.lower() not in IMAGE_EXTENSIONS:
+            continue
+        dst_file = dest / p.name
+        if not dst_file.exists() or dst_file.stat().st_mtime < p.stat().st_mtime:
+            shutil.copy2(p, dst_file)
+        paths.append(str(dst_file.resolve()))
+    _SAMPLE_IMAGES_COPY_DIR = dest
     return paths
 
 
@@ -113,13 +129,12 @@ def _get_model(device: str):
 
 def build_ui():
     _get_assets()
-
     device = "cuda" if torch.cuda.is_available() else "cpu"
     # Start loading the model in the background so it is ready (or nearly ready) by first use.
     print(f"Initializing model on {device}...")
     _get_model(device)
 
-    @spaces.GPU
+    @spaces.GPU if spaces else lambda x: x
     def run_inference(image: np.ndarray | None) -> np.ndarray | None:
         """Run reflection removal using the cached model. Returns RGB numpy [H,W,3] in 0–255 or None."""
         if image is None:
@@ -134,9 +149,15 @@ def build_ui():
         tensor = TF.resize(tensor, [target_side, target_side], antialias=True)
         tensor = tensor.to(ura_model.device, dtype=torch.float32)
         mask = tensor.mean(1, keepdim=True) > 0.9  # [1, 1, S, S]
+        import time
+
         with torch.no_grad():
+            start_time = time.time()
             diffuse = ura_model(images=tensor, inpaint_mask_override=mask)
+            end_time = time.time()
         diffuse = diffuse.cpu()
+        inference_time_ms = (end_time - start_time) * 1000
+        gr.Success(f"Inference time: {inference_time_ms:.1f} ms")
         diffuse = TF.resize(diffuse, [h, w], antialias=True)
         out = diffuse[0].numpy().transpose(1, 2, 0)
         out = (np.clip(out, 0.0, 1.0) * 255).astype(np.uint8)
@@ -178,12 +199,12 @@ def build_ui():
         with gr.Row():
             inp = gr.Image(
                 type="numpy",
-                label="Image input",
+                label="Input",
                 height=600,
                 width=600,
             )
             out_slider = gr.ImageSlider(
-                label="Input",
+                label="Output",
                 type="numpy",
                 height=600,
                 show_label=True,
@@ -208,7 +229,7 @@ def build_ui():
                     [GitHub](https://github.com/alberto-rota/UnReflectAnything) ⋅
                     [Model Card](https://huggingface.co/AlbeRota/UnReflectAnything) ⋅
                     [Paper](https://arxiv.org/abs/2512.09583) ⋅
-                    [Contact](mailto:alberto1.rota@polimi.it) ⋅
+                    [Contact](mailto:alberto1.rota@polimi.it)
                     """)
     return demo
 
@@ -221,15 +242,39 @@ def _launch_allowed_paths():
     paths = [str(_GRADIO_DIR)]
     try:
         assets = _get_assets()
-        if assets.sample_images_dir.is_dir():
-            paths.append(str(assets.sample_images_dir))
-    except Exception:
-        pass
+        sample_dir = assets.sample_images_dir
+        if sample_dir.is_dir():
+            paths.append(str(sample_dir.resolve()))
+        # Also allow parent (snapshot root) in case Gradio resolves paths from repo root
+        parent = sample_dir.parent
+        if parent.is_dir():
+            paths.append(str(parent.resolve()))
+    except Exception as e:
+        print(f"Warning: could not add HF sample_images to allowed_paths: {e}")
     return paths
 
 
+def _launch_kwargs():
+    """Default kwargs for launch() so allowed_paths are always set (e.g. when HF Spaces runs demo.launch())."""
+    return {
+        "allowed_paths": _launch_allowed_paths(),
+        "theme": gr.themes.Soft(primary_hue="orange", secondary_hue="blue"),
+    }
+
+
+# Ensure launch() always receives allowed_paths (e.g. when HF Spaces runner calls demo.launch() without args)
+_original_launch = demo.launch
+
+
+def _launch_with_allowed_paths(*args, **kwargs):
+    for key, value in _launch_kwargs().items():
+        if key not in kwargs:
+            kwargs[key] = value
+    return _original_launch(*args, **kwargs)
+
+
+demo.launch = _launch_with_allowed_paths
+
+
 if __name__ == "__main__":
-    demo.launch(
-        allowed_paths=_launch_allowed_paths(),
-        theme=gr.themes.Soft(primary_hue="orange", secondary_hue="blue"),
-    )
+    demo.launch()

tmp/config.log

@@ -1 +1,2 @@
-2026-02-11 20:08:17,718 - utilities.config - CONFIG - CONFIG    DISTRIBUTE is 'singlegpu' even though multiple GPUs are available
+2026-02-11 21:26:27,642 - utilities.config - CONFIG - CONFIG    DISTRIBUTE is 'singlegpu' even though multiple GPUs are available
+2026-02-11 21:26:32,739 - utilities.config - CONFIG - CONFIG    DISTRIBUTE is 'singlegpu' even though multiple GPUs are available

tmp/models.log

@@ -0,0 +1,2 @@
+2026-02-11 21:26:30,960 - models - MODEL - MODEL     Decoder 'diffuse' frozen due to DECODER_LR=0.0
+2026-02-11 21:26:35,539 - models - MODEL - MODEL     Decoder 'diffuse' frozen due to DECODER_LR=0.0