Update app.py

app.py

@@ -6,117 +6,7 @@ import plotly.express as px
 st.set_page_config(layout="wide")
 
 
-# Function to generate example data for SSD (replace with your data)
-def generate_example_data_ssd(model):
-    data = {
-        'Model': [],
-        'KL Factor': [],
-        'FLOPS': [],
-        'Params': [],
-        'mAP': []
-    }
-    
-    # Define KL Factor, FLOPS, Params, and mAP for each SSD model
-    if model == 'SSD300' or model == 'SSD512':
-        data['Model'].append(model)
-        data['KL Factor'].append(np.random.uniform(0.1, 1.0))
-        data['FLOPS'].append(np.random.randint(100, 300))
-        data['Params'].append(np.random.randint(10, 30))
-        data['mAP'].append(np.random.uniform(0.7, 0.9))
-    
-    return pd.DataFrame(data)
-
-# Function to generate example data for DETR (replace with your data)
-def generate_example_data_detr():
-    data = {
-        'Model': ['DETR'],
-        'FLOPS': [np.random.randint(100, 300)],
-        'Params': [np.random.randint(10, 30)],
-        'mAP': [np.random.uniform(0.7, 0.9)]
-    }
-    
-    return pd.DataFrame(data)
-
-# Streamlit app
-st.title("Variational Information Bottleneck")
-
-# Text card about the page
-st.markdown("""
-    <div class="text-card">
-        <p>This page explores Variational Information Bottleneck (VIB) for SSD and DETR models.</p>
-        <p>VIB is a technique used for model compression and transfer learning in deep learning tasks.</p>
-    </div>
-    """, unsafe_allow_html=True)
-
-# Create tabs for SSD and DETR
-tabs = st.tabs(["SSD", "DETR"])
-
-# SSD tab content
-if tabs[0]:
-    st.subheader("SSD")
-    
-    # Create sub-tabs for Transferability and Pruning
-    sub_tabs = st.tabs(["Transferability", "Pruning"])
-    
-    # SSD Transferability tab content
-    if sub_tabs[0]:
-        st.subheader("Transferability")
-        
-        # Filters for Transferability
-        model = st.selectbox("Select Model", ["SSD300", "SSD512"])
-        
-        # Generate example data for SSD Transferability
-        transfer_data = generate_example_data_ssd(model)
-
-        # Display table for SSD Transferability
-        st.write("Table for SSD Transferability:")
-        st.table(transfer_data)
-
-        # Plot graphs for SSD Transferability
-        st.write("Graphs for SSD Transferability:")
-        fig_flops = px.scatter(transfer_data, x='FLOPS', y='mAP', hover_name='Model', title='SSD Transferability: FLOPS vs mAP')
-        fig_params = px.scatter(transfer_data, x='Params', y='mAP', hover_name='Model', title='SSD Transferability: Params vs mAP')
-        st.plotly_chart(fig_flops)
-        st.plotly_chart(fig_params)
-
-    # SSD Pruning tab content
-    else:
-        st.subheader("Pruning")
-        
-        # Filters for Pruning
-        model = st.selectbox("Select Model", ["SSD300", "SSD512"])
-        
-        # Generate example data for SSD Pruning
-        pruning_data = generate_example_data_ssd(model)
-
-        # Display table for SSD Pruning
-        st.write("Table for SSD Pruning:")
-        st.table(pruning_data)
-
-        # Plot graphs for SSD Pruning
-        st.write("Graphs for SSD Pruning:")
-        fig_flops = px.scatter(pruning_data, x='FLOPS', y='mAP', hover_name='Model', title='SSD Pruning: FLOPS vs mAP')
-        fig_params = px.scatter(pruning_data, x='Params', y='mAP', hover_name='Model', title='SSD Pruning: Params vs mAP')
-        st.plotly_chart(fig_flops)
-        st.plotly_chart(fig_params)
-
-# DETR tab content
-else:
-    st.subheader("DETR")
-    
-    # Generate example data for DETR
-    detr_data = generate_example_data_detr()
-
-    # Display table for DETR
-    st.write("Table for DETR:")
-    st.table(detr_data)
-
-    # Plot graphs for DETR
-    st.write("Graphs for DETR:")
-    fig_flops = px.scatter(detr_data, x='FLOPS', y='mAP', hover_name='Model', title='DETR: FLOPS vs mAP')
-    fig_params = px.scatter(detr_data, x='Params', y='mAP', hover_name='Model', title='DETR: Params vs mAP')
-    st.plotly_chart(fig_flops)
-    st.plotly_chart(fig_params)import streamlit as st
+import streamlit as st
 import pandas as pd
 import numpy as np
 import plotly.express as px
@@ -209,4 +99,3 @@ else:
     st.plotly_chart(fig_flops)
     st.plotly_chart(fig_params)
 
-