Update app.py

app.py

@@ -1,59 +1,6 @@
 import streamlit as st
 import tensorflow as tf
 from PIL import Image
-# from src.utils import *
-# from src.vertex import *
-
-st.set_page_config(
-    page_title="Hip-Implant Image Classification",
-    page_icon=":robot:",
-    layout="centered",
-    initial_sidebar_state="expanded",
-    menu_items={
-        'How to use': "# Upload an image of a hip-implant (search <loose hip implant> on google), the app will classify the hip-implant as loose or in-control."
-    }
-)
-
-#creating session states
-create_session_state()
-
-
-
-# image = Image.open('./image/title.jpg')
-# st.image(image)
-st.title(":red[My AI Journey] :blue[Nishant Guvvada] X-ray Assistant")
-
-with st.sidebar:
-    # image = Image.open('./image/sidebar_image.jpg')
-    # st.image(image)
-    st.markdown("<h2 style='text-align: center; color: red;'>Settings Tab</h2>", unsafe_allow_html=True)
-
-
-    st.write("Model Settings:")
-
-    #define the temeperature for the model
-    temperature_value = st.slider('Temperature :', 0.0, 1.0, 0.2)
-    st.session_state['temperature'] = temperature_value
-
-    #define the temeperature for the model
-    token_limit_value = st.slider('Token limit :', 1, 1024, 256)
-    st.session_state['token_limit'] = token_limit_value
-
-    #define the temeperature for the model
-    top_k_value = st.slider('Top-K  :', 1,40,40)
-    st.session_state['top_k'] = top_k_value
-
-    #define the temeperature for the model
-    top_p_value = st.slider('Top-P :', 0.0, 1.0, 0.8)
-    st.session_state['top_p'] = top_p_value
-
-    if st.button("Reset Session"):
-        reset_session()
-
-
-st.image(bytes_data, caption='User uploaded image')
-st.balloons()
-
 
 @st.cache(allow_output_mutation=True)
 def load_model():