Stable

app.py

@@ -1,16 +1,23 @@
 import os
 import pathlib
+import time
+import torch
+from models import UNet
+from test_functions import process_image
+from PIL import Image
+import gradio as gr
+from gradio_client import Client, handle_file
+from huggingface_hub import hf_hub_download
+import tempfile
+import requests
 
-# ─── Redirect Hugging Face & other caches into /tmp ────────────────────────
 os.environ["HF_HOME"]               = "/tmp/huggingface"
 os.environ["HUGGINGFACE_HUB_CACHE"] = "/tmp/huggingface"
 os.environ["XDG_CACHE_HOME"]        = "/tmp/.cache"
 
-# ─── Redirect Gradio’s caches (general + examples) into /tmp ──────────────
 os.environ["GRADIO_CACHE_DIR"]      = "/tmp/.gradio"
 os.environ["GRADIO_EXAMPLES_CACHE"] = "/tmp/.gradio/cached_examples"
 
-# ─── Pre-create all writable dirs so nothing falls back to ./ .gradio or ./model
 for d in (
     "/tmp/huggingface",
     "/tmp/.cache",
@@ -19,27 +26,12 @@ for d in (
 ):
     pathlib.Path(d).mkdir(parents=True, exist_ok=True)
 
-# ─── Your model directory under /tmp ───────────────────────────────────────
 MODEL_DIR = "/tmp/model"
 pathlib.Path(MODEL_DIR).mkdir(parents=True, exist_ok=True)
 MODEL_PATH = os.path.join(MODEL_DIR, "best_unet_model.pth")
 
-# ─── Now safely import everything else ────────────────────────────────────
-import time
-import torch
-from models import UNet
-from test_functions import process_image
-from PIL import Image
-import gradio as gr
-from gradio_client import Client, handle_file
-from huggingface_hub import hf_hub_download
-import tempfile
-import requests
-
 
-# Path to your downloaded model
 MODEL_PATH = os.path.join(MODEL_DIR, "best_unet_model.pth")
-# Download model if missing
 def download_model():
     print("Starting model download at", time.strftime("%Y-%m-%d %H:%M:%S"))
     path = hf_hub_download(