table2html 1.3.0

Detect and convert table image to html table

Table2HTML

A Python package that converts table images into HTML format using Object Detection model and OCR.

Installation

pip install table2html

Usage

Initialize

from table2html import Table2HTML
table2html = Table2HTML()

Table Detection

detection_data = table2html.TableDetect(image)
# Output: [{"table_bbox": Tuple[int]}]

# Visualize table detection (first table)
from table2html.source import visualize_boxes
cv2.imwrite(
    "table_detection.jpg", 
    visualize_boxes(
        image, 
        [detection_data[0]["table_bbox"]], 
        color=(0, 0, 255),
        thickness=1
    )
)

Table detection result:

Structure Detection

data = table2html.StructureDetect(image)
# Output: {
#   "cells": List[Dict],
#   "num_rows": int,
#   "num_cols": int,
#   "html": str
# }

# Visualize structure detection
from table2html.source import visualize_boxes
cv2.imwrite(
    "structure_detection.jpg", 
    visualize_boxes(
        image, 
        [cell['box'] for cell in data['cells']], 
        color=(0, 255, 0),
        thickness=1
    )
)

# Write HTML output
with open('table.html', 'w') as f:
    f.write(data["html"])

Structure detection result:

HTML output: extracted html.

Full Pipeline

Note: The cell coordinates are relative to the cropped table image.

data = table2html(image)
# Output: [{
#   "table_bbox": Tuple[int],
#   "cells": List[Dict],
#   "num_rows": int,
#   "num_cols": int,
#   "html": str
# }]

Input

• image: numpy.ndarray (OpenCV/cv2 image format)

Outputs

A list of extracted tables in structured:

1. table_bbox: Tuple[int] - Bounding box coordinates (x1, y1, x2, y2) of the table
2. cells: List[Dict] - List of cell dictionaries, where each dictionary contains:
   • row: int - Row index
   • column: int - Column index
   • box: Tuple[int] - Bounding box coordinates (x1, y1, x2, y2)
   • text: str - Cell text content
3. num_rows: int - Number of rows in the table
4. num_cols: int - Number of columns in the table
5. html: str - HTML representation of the table

License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.