code formatting

frontend.py

@@ -8,11 +8,14 @@ import streamlit as st
 from PIL import Image
 from skimage.io import imread
 
+
 def infer() -> None:
     st.title("Overhead MNIST classification app")
 
     # select an input image file
-    image_file_buffer = st.sidebar.file_uploader("Select input image", type=["jpg", "jpeg"])
+    image_file_buffer = st.sidebar.file_uploader(
+        "Select input image", type=["jpg", "jpeg"]
+    )
     # read the image
     if image_file_buffer is not None:
         image = Image.open(image_file_buffer)
@@ -42,31 +45,44 @@ def infer() -> None:
         st.write(response.json())
     return
 
+
 def app_info() -> None:
     st.title("App info")
     st.markdown("_Task - Overhead MNIST classification_")
-    st.markdown("_Project repo - [https://github.com/AbhishekRS4/overhead_mnist](https://github.com/AbhishekRS4/overhead_mnist)_")
-    st.markdown("_Dataset - [Overhead MNIST dataset](https://www.kaggle.com/datasets/datamunge/overheadmnist/)_")
+    st.markdown(
+        "_Project repo - [https://github.com/AbhishekRS4/overhead_mnist](https://github.com/AbhishekRS4/overhead_mnist)_"
+    )
+    st.markdown(
+        "_Dataset - [Overhead MNIST dataset](https://www.kaggle.com/datasets/datamunge/overheadmnist/)_"
+    )
     st.header("Brief description of the project")
-    st.write("The Overhead MNIST dataset contains images extracted from satellite data.")
-    st.write("This dataset contains instances for 10 classes --- car, harbor, helicopter, oil_gas_field, parking_lot, plane, runway_mark, ship, stadium, and storage_tank.")
+    st.write(
+        "The Overhead MNIST dataset contains images extracted from satellite data."
+    )
+    st.write(
+        "This dataset contains instances for 10 classes --- car, harbor, helicopter, oil_gas_field, parking_lot, plane, runway_mark, ship, stadium, and storage_tank."
+    )
     st.write("A custom architecture is modeled for the classification task.")
     st.write("The best performing model has been used for the deployed application.")
     return
 
+
 app_modes = {
-    "App Info" : app_info,
+    "App Info": app_info,
     "Overhead MNIST Inference App": infer,
 }
 
+
 def start_app() -> None:
     selected_mode = st.sidebar.selectbox("Select mode", list(app_modes.keys()))
     app_modes[selected_mode]()
     return
 
+
 def main() -> None:
     start_app()
     return
 
+
 if __name__ == "__main__":
     main()