Enhance Dockerfile and app.py for model directory permissions and download logging

Dockerfile

@@ -28,8 +28,8 @@ WORKDIR /app
 # Install runtime dependency: libopenblas.so.0 is provided by libopenblas-base.
 RUN apt-get update && apt-get install -y build-essential cmake libopenblas-dev liblapack-dev libopenblas-dev liblapack-dev
 
-# Create the "model" folder for caching the model file
-RUN mkdir -p /app/model
+# Create the "model" directory with appropriate permissions
+RUN mkdir -p /app/model && chmod -R 777 /app/model
 
 COPY --from=builder /app/venv venv
 

app.py

@@ -1,4 +1,5 @@
 import os
+import time
 import torch
 from models import UNet
 from test_functions import process_image
@@ -12,13 +13,14 @@ MODEL_PATH = "model/best_unet_model.pth"
 os.makedirs("model", exist_ok=True)
 
 if not os.path.exists(MODEL_PATH):
-    print("Downloading model from Hugging Face...")
+    print("Starting model download at", time.strftime("%Y-%m-%d %H:%M:%S"))
     path = hf_hub_download(repo_id="Robys01/face-aging", filename="best_unet_model.pth", local_dir="model", cache_dir="model")
-    print(f"Model downloaded to {path}")
+    print("Model downloaded to", MODEL_PATH, "at", time.strftime("%Y-%m-%d %H:%M:%S"))
 
 model = UNet()  
 model.load_state_dict(torch.load(MODEL_PATH, map_location=torch.device("cpu"), weights_only=False))
 model.eval()
+print("Model loaded at", time.strftime("%Y-%m-%d %H:%M:%S"))
 
 def age_image(image: Image.Image, source_age: int, target_age: int) -> Image.Image:
     # Ensure the image is in RGB or grayscale; if not, convert it.