Update app.py

app.py

@@ -116,5 +116,97 @@ else:
     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 pandas as pd
+import numpy as np
+import plotly.express as px
+
+# Function to generate example data for SSD (replace with your data)
+def generate_example_data_ssd(model, task):
+    data = {
+        'Model': [],
+        'KL Factor': [],
+        'FLOPS': [],
+        'Params': [],
+        'mAP': []
+    }
+    
+    # Define KL Factor, FLOPS, Params, and mAP for each SSD model and task
+    if model == 'SSD300' or model == 'SSD512':
+        for _ in range(5):  # Generate example data for 5 samples
+            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")
+    
+    # Filter for Transferability vs Pruning
+    task = st.radio("Select Task", ["Transferability", "Pruning"])
+    
+    # Filter for SSD model
+    model = st.radio("Select Model", ["SSD300", "SSD512"])
+
+    # Generate example data based on selected filters
+    ssd_data = generate_example_data_ssd(model, task)
+
+    # Display table for SSD
+    st.write("Table for SSD:")
+    st.table(ssd_data)
+
+    # Plot graphs for SSD
+    st.write("Graphs for SSD:")
+    fig_flops = px.scatter(ssd_data, x='FLOPS', y='mAP', hover_name='Model', title=f'SSD: {task} - FLOPS vs mAP')
+    fig_params = px.scatter(ssd_data, x='Params', y='mAP', hover_name='Model', title=f'SSD: {task} - 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)
+
+