|
import base64 |
|
|
|
import streamlit as st |
|
|
|
|
|
|
|
def get_base64(file_path): |
|
with open(file_path, "rb") as file: |
|
base64_bytes = base64.b64encode(file.read()) |
|
base64_string = base64_bytes.decode("utf-8") |
|
return base64_string |
|
|
|
|
|
|
|
def set_background(png_file): |
|
bin_str = get_base64(png_file) |
|
page_bg_img = ( |
|
""" |
|
<style> |
|
.stApp { |
|
background-image: url("data:image/png;base64,%s"); |
|
background-size: auto; |
|
} |
|
</style> |
|
""" |
|
% bin_str |
|
) |
|
st.markdown(page_bg_img, unsafe_allow_html=True) |
|
|
|
|
|
|
|
set_background("tg_toxic.png") |
|
|
|
title_html = """<p style='font-size: 50px; color: black;'>Toxicity Assessment of User Comments</p>""" |
|
st.markdown(title_html, unsafe_allow_html=True) |
|
|
|
st.write( |
|
"""<p style='font-size: 18px; color: black;'>Used model: rubert-tiny-toxicity</p> |
|
<p style='font-size: 18px; color: black;'>Accuracy:</p> |
|
<p style='font-size: 18px; color: black;'>Pretrained model: 82%</p> |
|
<p style='font-size: 18px; color: black;'>After training on user's data: 90%</p> |
|
<a href='https://t.me/toxicity_assessment12345_bot' style='font-size: 18px; color: black; text-decoration: underline;'>Link: Toxicity Assessment Bot</a> |
|
""", |
|
unsafe_allow_html=True, |
|
) |
|
|
