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import streamlit as st
import pandas as pd
import numpy as np
import yfinance as yf
import altair as alt
import plotly.figure_factory as ff
import pydeck as pdk
from vega_datasets import data as vds
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from streamlit_image_comparison import image_comparison
def on_input_change():
user_input = st.session_state.user_input
st.session_state.past.append(user_input)
st.session_state.generated.append(
{"data": "The messages from Bot\nWith new line", "type": "normal"}
)
def on_btn_click():
del st.session_state.past[:]
del st.session_state.generated[:]
def main():
st.title(" Image Prediction (Computer Vision)")
option = st.selectbox(" ImageNet / CoCo", [" ImageNet ", " CoCo"])
value = st.slider(" Threshold", min_value=0, max_value=100, value=50, key=65)
(
col1,
col2,
) = st.columns(2)
with col1:
if st.checkbox(" Remove Noise"):
st.write("Checkbox checked!")
with col2:
if st.checkbox(" Increase Resolution"):
st.write("Checkbox checked!")
uploaded_file = st.file_uploader("Choose a file", type=["jpg", "png", "mp3"])
if st.button(" Predict"):
st.write("Button clicked!")
st.subheader(" Original vs Predicted")
image_comparison(
img1="https://www.imgonline.com.ua/examples/red-yellow-flower.jpg",
img2="https://lettatai.sirv.com/imgonline-com-ua-Negative-lYz1br1SWE.jpg",
)
if __name__ == "__main__":
main()
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