Update app.py

app.py

@@ -24,22 +24,20 @@ os.environ['TF_FORCE_GPU_ALLOW_GROWTH'] = 'true'
 # Try loading with h5py directly for better compatibility
 import h5py
 
+# Load model with old TensorFlow/Keras compatibility
 try:
-    # Use legacy loader which is more compatible
-    from tensorflow.keras.saving import legacy
-    model = legacy.load_model.load_model('cancer_model.h5', compile=False)
-    print("Model loaded successfully with legacy loader!")
+    # Direct loading with old Keras
+    from keras.models import load_model as keras_load_model
+    model = keras_load_model('cancer_model.h5', compile=False)
+    print("✓ Model loaded successfully with Keras 2.4.3!")
 except Exception as e:
-    print(f"Legacy loader failed: {e}")
+    print(f"Keras loader failed: {e}")
     try:
-        # Fallback: try standard loader
-        model = load_model('cancer_model.h5', compile=False)
-        print("Model loaded successfully!")
+        # Try TensorFlow loader
+        model = tf.keras.models.load_model('cancer_model.h5', compile=False)
+        print("✓ Model loaded successfully with TensorFlow!")
     except Exception as e2:
-        print(f"Standard loader also failed: {e2}")
-        print("\nPlease re-save your model using:")
-        print("  model.save('cancer_model.h5', save_format='h5')")
-        print("Or convert to SavedModel format for better compatibility")
+        print(f"Error: {e2}")
         raise
 
 def resize_with_padding(img, target_size):