Update app.py
Browse files
app.py
CHANGED
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@@ -10,6 +10,9 @@ import matplotlib.pyplot as plt
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import streamlit as st
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import pandas as pd
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import matplotlib.pyplot as plt
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# Sample data for demonstration purposes
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models = ['SSD300', 'SSD512', 'DETR']
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@@ -34,13 +37,14 @@ results_data = {
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# Title of the research
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st.title('Research Results')
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# Create two columns
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col1, col2 = st.columns(
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# Left section: Results and Evolution Graphs
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with col1:
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st.subheader('Results')
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# Display results table
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results = results_data[model]
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df_results = pd.DataFrame({
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'Model': [model]*4,
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@@ -74,8 +78,6 @@ with col1:
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# Right section: Filters and Hyperparameters
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with col2:
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model = st.selectbox('Select model:', models)
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if model in ['SSD300', 'SSD512']:
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pruning = st.selectbox('Select pruning method:', pruning_methods)
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hyperparameter_data = hyperparameters[model][pruning]
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import streamlit as st
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import pandas as pd
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import matplotlib.pyplot as plt
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import streamlit as st
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import pandas as pd
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import matplotlib.pyplot as plt
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# Sample data for demonstration purposes
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models = ['SSD300', 'SSD512', 'DETR']
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# Title of the research
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st.title('Research Results')
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# Create two columns with specified widths
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col1, col2 = st.columns([7, 3])
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# Left section: Results and Evolution Graphs
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with col1:
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st.subheader('Results')
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# Display results table
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model = st.selectbox('Select model:', models)
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results = results_data[model]
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df_results = pd.DataFrame({
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'Model': [model]*4,
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# Right section: Filters and Hyperparameters
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with col2:
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if model in ['SSD300', 'SSD512']:
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pruning = st.selectbox('Select pruning method:', pruning_methods)
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hyperparameter_data = hyperparameters[model][pruning]
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