TableCV

TableCV is a Python package designed to extract tables from images. It offers two approaches for extracting tables, allowing you to choose the one that best suits your needs.

Installation

You can easily install TableCV using pip:

pip install tablecv

Usage

Approach 1 (using PaddleOCR)

TableCV offers a straightforward method to extract tables using PaddleOCR. This approach returns a pandas DataFrame object:

from tablecv import extract_table

# Replace "image_path" with the path to your image
print(extract_table(image_path="your_image.png"))

Approach 2 (OCR with Your Preferred Tool)

If you prefer using a different OCR tool like EasyOCR, KerasOCR, or any other OCR solution, you can still use TableCV. First, perform OCR on your image using your chosen tool. The OCR results should be structured as a list of tuples, each containing a bounding box and corresponding text:

# List of tuples: (bounding box as (x, y, w, h), text)
ocr_results = [
    ((1, 2, 3, 4), "a"),
    ((4, 5, 6, 7), "b"),
    # Add more tuples as needed
]

After obtaining your OCR results, you can extract tables from them using TableCV:

from tablecv import extract_table_from_ocr

# Replace "ocr_results" with your OCR results list
print(extract_table_from_ocr(ocr_results))

With these two approaches, TableCV provides flexibility for table extraction from images, whether you prefer using PaddleOCR or another OCR tool of your choice.