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import streamlit as st
import pandas as pd
from persist import persist, load_widget_state
import numpy as np
import matplotlib.pyplot as plt
global variable_output
def main():
cs_body()
def convert_csv():
d = {'col1': [], 'col2': []}
df = pd.DataFrame(data=d, columns=['Age', 'Sex'])
return df.to_csv().encode("utf-8")
def cs_body():
st.header('Training Data and Methodology')
st.write("Provide an overview of the Training Data and Training Procedure for this model")
st.markdown('##### Training dataset')
left, right = st.columns(2)
left.number_input("Training set size",value=100)
right.number_input("Validation set size",value=20)
st.text("Demographical and clinical characteristics")
left, right = st.columns(2)#, vertical_alignment ="center")
left.download_button("Download Template", data=convert_csv(), file_name='file.csv')
demo = right.file_uploader("Load template",type=['csv'])
if demo is not None:
left, right = st.columns(2)#, vertical_alignment ="center")
fig, ax = plt.subplots()
ax.set_title("Age distribution")
ax.hist(np.random.normal(loc=40,scale=4.0,size=500))
age = left.pyplot(fig)
fig, ax = plt.subplots()
ax.pie([45,55],labels=["Men","Women"])
right.pyplot(fig)
st.text_input("Source",placeholder="Brats challenge/ Clinic ...")
st.text("Acquisition date")
left, right = st.columns(2)
left.date_input("From")
right.date_input("To")
if __name__ == '__main__':
load_widget_state()
main() |