Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,32 +1,31 @@
+import tempfile
 import streamlit as st
 import tensorflow as tf
 from tensorflow import keras
 import numpy as np
 from PIL import Image
 import io
+from huggingface_hub import hf_hub_download
 import os
 
-from huggingface_hub import hf_hub_download, HfFolder
-
-# Set Hugging Face cache dir to a writable path
-HF_CACHE_DIR = "./hf_cache"
-os.environ["HF_HOME"] = HF_CACHE_DIR
-os.environ["HF_HUB_CACHE"] = HF_CACHE_DIR
-os.makedirs(HF_CACHE_DIR, exist_ok=True)
-
-# Streamlit UI
+# Set Streamlit page
 st.set_page_config(page_title="NaxiLowLight Enhancer", layout="centered")
 st.title("🌙 NaxiLowLight - Low-Light Image Enhancer")
 
+# ✅ Load model using temporary directory (no caching to /.cache!)
 @st.cache_resource
-def load_model_from_huggingface():
+def load_model_from_huggingface_temp():
     repo_id = "NEXAS/low_light_enhance"
     filename = "model.h5"
-    model_path = hf_hub_download(repo_id=repo_id, filename=filename, cache_dir=HF_CACHE_DIR)
-    return keras.models.load_model(model_path, compile=False)
 
-model = load_model_from_huggingface()
+    with tempfile.TemporaryDirectory() as temp_dir:
+        model_path = hf_hub_download(repo_id=repo_id, filename=filename, cache_dir=temp_dir)
+        model = keras.models.load_model(model_path, compile=False)
+    return model
 
+model = load_model_from_huggingface_temp()
+
+# 🔧 Enhancement function
 def enhance_image(image: Image.Image) -> Image.Image:
     image_resized = image.resize((256, 256))
     img_array = keras.utils.img_to_array(image_resized) / 255.0
@@ -35,6 +34,7 @@ def enhance_image(image: Image.Image) -> Image.Image:
     output = np.clip(output * 255.0, 0, 255).astype(np.uint8)
     return Image.fromarray(output)
 
+# 📤 Upload & Enhance UI
 uploaded_file = st.file_uploader("📤 Upload a low-light image", type=["jpg", "jpeg", "png"])
 
 if uploaded_file:
@@ -44,8 +44,10 @@ if uploaded_file:
     if st.button("✨ Enhance Image"):
         with st.spinner("Enhancing image..."):
             enhanced = enhance_image(image)
-        st.image(enhanced, caption="🚀 Enhanced by NaxiLowLight", use_column_width=True)
 
+        st.image(enhanced, caption="🚀 Enhanced Image", use_column_width=True)
+
+        # Download
         img_bytes = io.BytesIO()
         enhanced.save(img_bytes, format="PNG")
         st.download_button("💾 Download Enhanced Image", data=img_bytes.getvalue(), file_name="enhanced.png", mime="image/png")