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import streamlit as st | |
import pandas as pd | |
from bokeh.plotting import figure | |
from bokeh.models import ColumnDataSource, HoverTool | |
# --- Define Styles --- | |
st.markdown( | |
""" | |
<style> | |
.main-title { | |
font-size: 50px; | |
color: #4CAF50; | |
text-align: center; | |
} | |
.sub-title { | |
font-size: 30px; | |
color: #555; | |
} | |
.custom-text { | |
font-size: 18px; | |
line-height: 1.5; | |
} | |
</style> | |
""", | |
unsafe_allow_html=True | |
) | |
st.markdown('<h1 class="main-title">Merit Secret Embeddings πππ</h1>', unsafe_allow_html=True) | |
st.markdown('<h2 class="sub-title">Donut</h2>', unsafe_allow_html=True) | |
st.markdown( | |
""" | |
<p class="custom-text"> | |
Explore how Donut perceive real data. | |
</p> | |
""", | |
unsafe_allow_html=True | |
) | |
# Get Data | |
df = pd.read_csv("data/data.csv") | |
source = ColumnDataSource(data=dict( | |
x=df['x'], | |
y=df['y'], | |
label=df['label'], | |
img=df['img'] | |
)) | |
# Configure figure | |
TOOLTIPS = """ | |
<div> | |
<div> | |
<img src="@img{safe}" style="width:400px; height:auto; float: left; margin: 0px 15px 15px 0px;" alt="@img" border="2"></img> | |
</div> | |
<div> | |
<span style="font-size: 17px; font-weight: bold;">@label</span> | |
</div> | |
</div> | |
""" | |
p = figure(width=400, height=400, tooltips=TOOLTIPS, title="") | |
p.scatter('x', 'y', size=20, source=source) | |
st.bokeh_chart(p) | |