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from src.table_creator.table_extractor import TableExtraction
import streamlit as st
import base64
from PIL import Image
import os
import cv2
import numpy as np
import tempfile
import traceback
# Load models only once
if 'tab_ext' not in st.session_state:
st.session_state.tab_ext = TableExtraction()
print('Models loaded.')
def process_image(imgpath):
return st.session_state.tab_ext.detect(imgpath)
def draw_bounding_box(image, bbox):
"""Draw a bounding box on the image"""
img_array = np.array(image)
if len(img_array.shape) == 3:
img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
x_min, y_min, x_max, y_max = bbox
cv2.rectangle(img_array, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)
if len(img_array.shape) == 3:
img_array = cv2.cvtColor(img_array, cv2.COLOR_BGR2RGB)
return Image.fromarray(img_array)
# Set page config
st.set_page_config(
page_title="Table Extraction Tool",
layout="wide",
initial_sidebar_state="expanded" # Changed to expanded to show guide by default
)
# Enhanced CSS styling with updated upload section
st.markdown("""
<style>
/* Main container and background */
.main { padding: 1.5rem; }
.stApp {
background: linear-gradient(135deg, #f6f9fc 0%, #f0f4f8 100%);
}
/* Header styling */
.main-header {
background: linear-gradient(90deg, #1a365d 0%, #2563eb 100%);
color: white;
padding: 2rem 3rem;
border-radius: 15px;
margin-bottom: 2rem;
box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
}
.main-header h1 {
font-size: 2.5rem;
margin-bottom: 0.5rem;
font-weight: 600;
color: white;
}
.main-header p {
font-size: 1.1rem;
opacity: 0.9;
}
/* Card containers */
.content-card {
background-color: white;
padding: 1.5rem;
border-radius: 12px;
box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
border: 1px solid #e5e7eb;
margin-bottom: 1.5rem;
}
/* Upload section - Reduced size */
.upload-section {
text-align: center;
padding: 1rem;
border: 2px dashed #e5e7eb;
border-radius: 12px;
background-color: #f8fafc;
max-width: 600px;
margin: 0 auto;
}
.upload-icon {
font-size: 1.5rem;
color: #2563eb;
margin-bottom: 0.5rem;
}
/* Results section */
.results-header {
font-size: 1.25rem;
color: #1f2937;
margin-bottom: 1rem;
padding-bottom: 0.5rem;
border-bottom: 2px solid #e5e7eb;
}
/* Download buttons */
.download-button {
display: inline-block;
padding: 0.75rem 1.5rem;
background-color: #2563eb;
color: white;
text-decoration: none;
border-radius: 8px;
transition: all 0.2s;
text-align: center;
width: 100%;
}
.download-button:hover {
background-color: #1d4ed8;
box-shadow: 0 4px 6px -1px rgba(37, 99, 235, 0.2);
}
/* Tabs styling */
.stTabs [data-baseweb="tab-list"] {
gap: 1rem;
background-color: #f8fafc;
padding: 0.5rem;
border-radius: 8px;
}
.stTabs [data-baseweb="tab"] {
color: #4b5563;
font-weight: 500;
padding: 0.5rem 1.5rem;
border-radius: 6px;
}
.stTabs [data-baseweb="tab"][aria-selected="true"] {
background-color: #2563eb;
color: white;
}
/* Guide section styling */
.guide-section {
background-color: white;
padding: 2rem;
border-radius: 12px;
margin-bottom: 1.5rem;
}
.guide-header {
color: #1a365d;
font-size: 1.5rem;
margin-bottom: 1rem;
border-bottom: 2px solid #e5e7eb;
padding-bottom: 0.5rem;
}
.guide-subheader {
color: #2563eb;
font-size: 1.2rem;
margin: 1.5rem 0 0.5rem 0;
}
.guide-text {
color: #4b5563;
line-height: 1.6;
margin-bottom: 1rem;
}
.feature-card {
background-color: #f8fafc;
padding: 1rem;
border-radius: 8px;
margin-bottom: 1rem;
border-left: 4px solid #2563eb;
}
.step-container {
display: flex;
align-items: flex-start;
margin-bottom: 1rem;
}
.step-number {
background-color: #2563eb;
color: white;
width: 24px;
height: 24px;
border-radius: 12px;
display: flex;
align-items: center;
justify-content: center;
margin-right: 1rem;
flex-shrink: 0;
}
.info-icon {
color: #2563eb;
margin-right: 0.5rem;
}
.tech-details {
background-color: #f0f9ff;
padding: 1rem;
border-radius: 8px;
margin: 1rem 0;
}
</style>
""", unsafe_allow_html=True)
# Create sidebar with guide content
with st.sidebar:
# st.markdown('<div class="guide-section">', unsafe_allow_html=True)
st.divider()
st.markdown('<h2 class="guide-header">π User Guide</h2>', unsafe_allow_html=True)
# How It Works section
st.markdown('<h3 class="guide-subheader">π― How It Works</h3>', unsafe_allow_html=True)
st.markdown("""
<div class="guide-text">
This tool uses advanced computer vision and machine learning techniques to:
<ul>
<li>Detect and locate tables in document images</li>
<li>Extract structured data from the detected tables</li>
<li>Convert the data into easily manageable formats</li>
</ul>
</div>
""", unsafe_allow_html=True)
# Usage Instructions
st.markdown('<h3 class="guide-subheader">π Usage Instructions</h3>', unsafe_allow_html=True)
st.markdown("""
<div class="step-container">
<div class="step-number">1</div>
<div class="guide-text">Upload a document image containing a table (JPG, or JPEG format)</div>
</div>
<div class="step-container">
<div class="step-number">2</div>
<div class="guide-text">The tool will automatically detect and highlight the table in your image</div>
</div>
<div class="step-container">
<div class="step-number">3</div>
<div class="guide-text">View both raw and enhanced versions of the extracted data</div>
</div>
<div class="step-container">
<div class="step-number">4</div>
<div class="guide-text">Download the results in CSV format for further use</div>
</div>
""", unsafe_allow_html=True)
# Best Practices
st.markdown('<h3 class="guide-subheader">π‘ Best Practices</h3>', unsafe_allow_html=True)
st.markdown("""
<div class="feature-card">
<strong>For Best Results:</strong>
<ul>
<li>Use clear, high-resolution images</li>
<li>Ensure tables have well-defined borders</li>
<li>Avoid skewed or rotated images</li>
<li>Make sure text is clearly readable</li>
</ul>
</div>
""", unsafe_allow_html=True)
# Technical Details (collapsible)
with st.expander("π§ Technical Details"):
st.markdown("""
<div class="tech-details">
<p><strong>Algorithm Overview:</strong></p>
<ul>
<li>Uses computer vision for table boundary detection</li>
<li>Employs OCR (Optical Character Recognition) for text extraction</li>
<li>Implements intelligent cell segmentation</li>
<li>Applies post-processing for enhanced accuracy</li>
</ul>
</div>
""", unsafe_allow_html=True)
# Support Info
st.markdown('<h3 class="guide-subheader">π Connect with Me</h3>', unsafe_allow_html=True)
st.markdown("""
<div class="guide-text" style="font-size: 1rem;">
If you encounter any issues or have questions, feel free to reach out:
<a href="https://github.com/Sudhanshu1304" target="_blank" style="text-decoration: none;">
<img src="https://img.icons8.com/ios-filled/20/000000/github.png" alt="GitHub" style="vertical-align: middle; margin-right: 5px;"/>
GitHub
</a> |
<a href="https://www.linkedin.com/in/sudhanshu-pandey-847448193/" target="_blank" style="text-decoration: none;">
<img src="https://img.icons8.com/ios-filled/20/000000/linkedin.png" alt="LinkedIn" style="vertical-align: middle; margin-right: 5px;"/>
LinkedIn
</a> |
<a href="https://medium.com/@sudhanshu.dpandey" target="_blank" style="text-decoration: none;">
<img src="https://img.icons8.com/ios-filled/20/000000/medium-logo.png" alt="Medium" style="vertical-align: middle; margin-right: 5px;"/>
Medium
</a>
</div>
""", unsafe_allow_html=True)
# Initialize session state for expanded view
if 'is_expanded' not in st.session_state:
st.session_state.is_expanded = False
# Title and description
st.markdown("""
<div class="main-header">
<h1>π Table Extraction Tool</h1>
<p>Upload an image containing tables and instantly convert them into structured data formats.</p>
</div>
""", unsafe_allow_html=True)
# File upload section - Reduced size
# st.markdown('<div class="content-card">', unsafe_allow_html=True)
# st.markdown("""
# <div class="upload-section">
# <div class="upload-icon">π₯</div>
# <h3 style="font-size: 1.1rem; margin: 0.5rem 0;">Upload Table Image</h3>
# <p style="font-size: 0.9rem; margin: 0;">Supported formats: PNG, JPG, JPEG</p>
# </div>
# """, unsafe_allow_html=True)
uploaded_file = st.file_uploader("", type=['png', 'jpg', 'jpeg'])
st.markdown('</div>', unsafe_allow_html=True)
# Process the uploaded file
if uploaded_file is not None:
with st.spinner('π Processing your image...'):
with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as tmp_file:
tmp_file.write(uploaded_file.getvalue())
temp_path = tmp_file.name
try:
image = Image.open(uploaded_file)
(raw_df, cleaned_df), bbox = process_image(temp_path)
st.session_state.raw_data = raw_df
st.session_state.processed_data = cleaned_df
marked_image = draw_bounding_box(image, bbox[0])
st.session_state.marked_image = marked_image
# Side by side layout
col1, col2 = st.columns([0.4, 0.6])
with col1:
# st.markdown('<div class="content-card image-container">', unsafe_allow_html=True)
st.divider()
st.markdown('<h3 class="results-header">Detected Table</h3>', unsafe_allow_html=True)
st.image(marked_image, use_container_width=True)
st.markdown('</div>', unsafe_allow_html=True)
with col2:
# st.markdown('<div class="content-card">', unsafe_allow_html=True)
st.divider()
st.markdown('<h3 class="results-header">Extracted Data</h3>', unsafe_allow_html=True)
# # Toggle button for expanded view
# if st.button("π Toggle Full View" if not st.session_state.is_expanded else "β¬οΈ Collapse View"):
# st.session_state.is_expanded = not st.session_state.is_expanded
tabs = st.tabs(["π Raw Data", "β¨ Enhanced Data β"])
with tabs[0]:
st.dataframe(st.session_state.raw_data,
use_container_width=True,
height=600 if not st.session_state.is_expanded else None)
# Add HTML copy section for raw data
st.markdown("### π Copy HTML Table")
html_raw = st.session_state.raw_data.to_html(index=False)
st.markdown("""
<div style="background-color: #f8fafc; padding: 0.5rem; border-radius: 8px; margin-bottom: 0.5rem;">
<p style="margin: 0; color: #475569; font-size: 0.9rem;">
βΉοΈ This HTML can be copied and used directly in websites, LLM prompts, or other applications.
</p>
</div>
""", unsafe_allow_html=True)
st.markdown("""
<div style="max-height: 150px; overflow-y: auto; border-radius: 8px;">
""", unsafe_allow_html=True)
st.code(html_raw, language="html")
st.markdown("</div>", unsafe_allow_html=True)
with tabs[1]:
st.markdown("""
<div style="background-color: #f0f9ff; padding: 1rem; border-radius: 8px; margin-bottom: 1rem;">
<p style="margin: 0; color: #1e40af;">
β This is our enhanced version of the table with improved formatting and structure.
</p>
</div>
""", unsafe_allow_html=True)
st.dataframe(st.session_state.processed_data,
use_container_width=True,
height=600 if not st.session_state.is_expanded else None)
# Add HTML copy section for enhanced data
st.markdown("### π Copy HTML Table")
html_enhanced = st.session_state.processed_data.to_html(index=False)
st.markdown("""
<div style="background-color: #f8fafc; padding: 0.5rem; border-radius: 8px; margin-bottom: 0.5rem;">
<p style="margin: 0; color: #475569; font-size: 0.9rem;">
βΉοΈ This HTML can be copied and used directly in websites, LLM prompts, or other applications.
</p>
</div>
""", unsafe_allow_html=True)
st.markdown("""
<div style="max-height: 150px; overflow-y: auto; border-radius: 8px;">
""", unsafe_allow_html=True)
st.code(html_enhanced, language="html")
st.markdown("</div>", unsafe_allow_html=True)
# st.markdown('</div>', unsafe_allow_html=True)
# Download section below both columns
# st.markdown('<div class="content-card">', unsafe_allow_html=True)
# Download section below both columns
st.divider()
st.markdown('<h3 class="results-header">Download Options</h3>', unsafe_allow_html=True)
download_cols = st.columns([1, 0.1, 1])
def get_csv_download_link(df, filename):
csv = df.to_csv(index=False).encode()
b64 = base64.b64encode(csv).decode()
return f'<a href="data:file/csv;base64,{b64}" download="{filename}" class="download-button">π₯ Download {filename}</a>'
with download_cols[0]:
if 'raw_data' in st.session_state:
csv = st.session_state.raw_data.to_csv(index=False)
st.download_button(
label="π₯ Download Raw Data",
data=csv,
file_name="raw_data.csv",
mime="text/csv",
use_container_width=True,
key="raw_download"
)
with download_cols[2]:
if 'processed_data' in st.session_state:
csv = st.session_state.processed_data.to_csv(index=False)
st.download_button(
label="π₯ Download Enhanced Data β",
data=csv,
file_name="enhanced_data.csv",
mime="text/csv",
use_container_width=True,
key="enhanced_download"
)
st.markdown('</div>', unsafe_allow_html=True)
except Exception as e:
st.error(f"β Error processing image: {str(traceback.format_exc())}")
finally:
try:
os.unlink(temp_path)
except Exception as e:
st.warning(f"β οΈ Error removing temporary file: {str(e)}")
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