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import streamlit as st
import pandas as pd
data_df = pd.DataFrame(
{
"apps": [
"https://storage.googleapis.com/s4a-prod-share-preview/default/st_app_screenshot_image/5435b8cb-6c6c-490b-9608-799b543655d3/Home_Page.png",
"https://storage.googleapis.com/s4a-prod-share-preview/default/st_app_screenshot_image/ef9a7627-13f2-47e5-8f65-3f69bb38a5c2/Home_Page.png",
"https://storage.googleapis.com/s4a-prod-share-preview/default/st_app_screenshot_image/31b99099-8eae-4ff8-aa89-042895ed3843/Home_Page.png",
"https://storage.googleapis.com/s4a-prod-share-preview/default/st_app_screenshot_image/6a399b09-241e-4ae7-a31f-7640dc1d181e/Home_Page.png",
],
}
)
st.set_page_config(
page_title="P&ID Object Detection ",
layout="wide",
initial_sidebar_state="expanded"
)
st.title('P&ID Object Detection App')
st.subheader(' Identify valves and pumps with deep learning model', divider='rainbow')
st.caption('Developed by Deep Drawings Co.')
col1, col2, col3 = st.columns([10, 10, 10])
with col2:
with st.expander('How to use it'):
st.markdown(
'''
1) Upload your P&ID or Select Test Diagrams 📬
2) Set Confidence Threshold 📈
3) Press to Perform Inference 🚀
4) Visualize Model Predictions 🔎
'''
)
st.data_editor(
data_df,
column_config={
"apps": st.column_config.ImageColumn(
"Preview Image", help="Streamlit app preview screenshots"
)
},
hide_index=True,
)
st.write('##')
col1, col2, col3 = st.columns([10, 10, 10])
with col1:
st.markdown(f"##### Upload your File:")
# set input image by upload
image_file = st.file_uploader("Upload your diagram:", type=["pdf"]) |