yolo4tab 0.2.3

An End-to-End table extraction system for printed documents based on YOLOv9.

YOLO4TAB - An End-to-End Table Extraction System for printed documents

Introduction

• YOLO4TAB is an end-to-end table extraction system for printed documents. It is based on the YOLOv9 to solve both table detection and table structure recognition problem. Besides, it also includes a skew correction algorithm to correct the skew of the input document.

• This is an end-to-end system that user can input a document image and get the table structure in HTML/LaTex/CSV format. The system also support some custom border styles and alignment for the table.

Installation

• You can easily install the package by using pip:

pip install yolo4tab

Usage

• You can use the package by running the following command:

from yolo4tab import TableExtraction

table_extraction = TableExtraction(device="cpu")
image_path = "/content/example.png"

outputs = table_extraction.extract_table(
    image_source=image_path,
)

for idx, table in enumerate(outputs):
    print(f"Table {idx}")
    print(table["outputs"]["html"])
    print(table["outputs"]["latex"])
    print(table["outputs"]["csv"])

Release Version

• v0.2.3 (26/6/2024) -> Update output format and device selection

• v0.2.2 (25/6/2024) -> Update output format

• v0.2.1 (23/6/2024) -> Update output format

• v0.2.0 (23/6/2024) -> Public release

• v0.1.1 - v0.1.9 (6/2024) -> Under development (Private release)

• v0.1.0 (2/6/2024) -> Update weights and new baseline model (Private release)

• v0.0.2 (17/5/2024) and v0.0.3 (23/05/2024) -> Update codebase (Private release)

• v0.0.1 (16/5/2024) -> Initial version with full pipeline (training, testing, evaluation) for table extraction on printed documents. (Private release)

Contributing

• vm7608