updated app.py

app.py

@@ -31,19 +31,32 @@ CLASS_NAMES = [
     'Tomato___healthy'
 ]
 
+import tempfile
+import os
+
 @st.cache_resource
 def load_model():
     """Load the plant disease classification model from Hugging Face"""
     model_url = "https://huggingface.co/ziadmostafa/EfficientNetB0-for-Plants-Diseases-Classification/resolve/main/densenet_model.keras"
     response = requests.get(model_url)
     if response.status_code == 200:
-        with BytesIO(response.content) as model_bytes:
-            model = tf.keras.models.load_model(model_bytes, compile=False)
+        # Write the model to a temporary file and load from there
+        with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
+            tmp_file.write(response.content)
+            model_path = tmp_file.name
+        
+        # Load the model from the file path
+        model = tf.keras.models.load_model(model_path, compile=False)
+        
+        # Clean up the temporary file
+        os.remove(model_path)
+        
         return model
     else:
         st.error("Failed to load the model. Please check the URL.")
         return None
 
+
 def preprocess_image(img):
     """Preprocess image for model prediction using the specified preprocessing steps"""
     img = img.resize((224, 224))