Upload app.py with huggingface_hub

app.py

@@ -5,45 +5,60 @@ import tensorflow as tf
 from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
 import gradio as gr
 
-# Try to load model from various sources
+# Load model from Hugging Face Hub
 model = None
+HF_MODEL_ID = os.environ.get("HF_MODEL_ID", "Sharris/age_detection_regression")
 
-# Try local files first (for development)
-local_model_paths = ["saved_model", "best_model.h5", "final_model.h5"]
-for path in local_model_paths:
-    if os.path.exists(path):
-        try:
-            model = tf.keras.models.load_model(path, compile=False)
-            print(f"Loaded model from local path: {path}")
-            break
-        except Exception as e:
-            print(f"Failed to load local model from {path}: {e}")
+print(f"Attempting to load model from: {HF_MODEL_ID}")
 
-# If no local model, try to download from Hugging Face Hub
-if model is None:
-    HF_MODEL_ID = os.environ.get("HF_MODEL_ID", "Sharris/age_detection_regression")
+try:
+    from huggingface_hub import hf_hub_download
+    print("Downloading best_model.h5...")
+    model_path = hf_hub_download(repo_id=HF_MODEL_ID, filename="best_model.h5")
+    print(f"Model downloaded to: {model_path}")
+    
+    print("Loading model with TensorFlow...")
+    model = tf.keras.models.load_model(model_path, compile=False)
+    print(f"✅ Successfully loaded model from {HF_MODEL_ID}")
+    
+except Exception as e:
+    print(f"❌ Failed to download best_model.h5: {e}")
+    
+    # Fallback: try to download entire repo and look for model files
     try:
-        from huggingface_hub import hf_hub_download
-        # Try to download the .h5 model file
-        model_path = hf_hub_download(repo_id=HF_MODEL_ID, filename="best_model.h5")
-        model = tf.keras.models.load_model(model_path, compile=False)
-        print(f"Loaded model from HF Hub: {HF_MODEL_ID}/best_model.h5")
-    except Exception as e:
-        print(f"Failed to load model from HF Hub ({HF_MODEL_ID}): {e}")
-        # Fallback: try to download entire repo and load from there
-        try:
-            from huggingface_hub import snapshot_download
-            repo_dir = snapshot_download(repo_id=HF_MODEL_ID)
-            model_file = os.path.join(repo_dir, "best_model.h5")
+        print("Trying fallback: downloading entire repository...")
+        from huggingface_hub import snapshot_download
+        repo_dir = snapshot_download(repo_id=HF_MODEL_ID)
+        print(f"Repository downloaded to: {repo_dir}")
+        
+        # Look for model files in the downloaded repo
+        possible_files = ["best_model.h5", "final_model.h5", "model.h5"]
+        for filename in possible_files:
+            model_file = os.path.join(repo_dir, filename)
             if os.path.exists(model_file):
-                model = tf.keras.models.load_model(model_file, compile=False)
-                print(f"Loaded model from downloaded repo: {model_file}")
-        except Exception as e2:
-            print(f"Fallback download also failed: {e2}")
+                print(f"Found model file: {model_file}")
+                try:
+                    model = tf.keras.models.load_model(model_file, compile=False)
+                    print(f"✅ Successfully loaded model from {model_file}")
+                    break
+                except Exception as load_error:
+                    print(f"Failed to load {model_file}: {load_error}")
+                    continue
+        
+        if model is None:
+            # List all files in the repo for debugging
+            import os
+            print("Files in downloaded repository:")
+            for root, dirs, files in os.walk(repo_dir):
+                for file in files:
+                    print(f"  {os.path.join(root, file)}")
+                    
+    except Exception as e2:
+        print(f"❌ Fallback download also failed: {e2}")
 
 if model is None:
     raise RuntimeError(
-        "No model found. Ensure 'best_model.h5' exists locally or set HF_MODEL_ID env var to a Hugging Face model repo containing the model."
+        f"❌ Could not load model from {HF_MODEL_ID}. Please ensure the repository contains a valid model file (best_model.h5, final_model.h5, or model.h5)."
     )
 
 INPUT_SIZE = (224, 224)