Update front

app.py

@@ -1,10 +1,11 @@
 import streamlit as st
 import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
 import sahi.utils.file
 from PIL import Image
 from sahi import AutoDetectionModel
 from utils import sahi_yolov8m_inference
-from streamlit_image_comparison import image_comparison
 from ultralyticsplus.hf_utils import download_from_hub
 
 IMAGE_TO_URL = {
@@ -204,6 +205,8 @@ with col2:
             col1,col2,col3 = st.columns([1,4,1])
             with col2:
                 chart_data = st.session_state["output_4"]
-                st.bar_chart(chart_data[['category','count']], x='category', y='count', use_container_width=True)
+                bar_plot = sns.barplot(x='count', y='category', data=chart_data)
+                st.pyplot(bar_plot.figure, use_container_width=True)
+                #st.bar_chart(chart_data[['category','count']], x='category', y='count', use_container_width=True)
             
   

utils.py

@@ -52,7 +52,5 @@ def sahi_yolov8m_inference(
     category_counts.columns = ['category', 'count']
     # update the `count` column in the base DataFrame
     output_df['count'] = output_df['category'].map(category_counts.set_index('category')['count']).fillna(0).astype(int)
-    # calculate percentages
-    output_df['percentage'] = round((output_df['count'] / output_df['count'].sum()) * 100, 1)
 
     return output_visual,coco_df,output_df