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atlanhq avatar

atlanhq/camelotArchived

0
View on GitHub↗
3,717 stars·360 forks·Python·26 viewscamelot-py.readthedocs.io↗

Camelot

Camelot is a Python-based library designed to parse, extract, and clean tabular data from PDF files. It converts table elements from text-based PDF documents into programmable data structures and dataframes.

The tool identifies tabular regions using coordinate-based grouping, lattice-based line detection, and stream-based text extraction. It can also rasterize PDF pages into images to utilize computer vision for detecting structural lines and boundaries.

Extracted data is validated through accuracy and whitespace metrics to filter out low-quality extractions. The processed information can be exported into structured formats such as CSV, JSON, and Excel.

Features

  • Table Extraction - Provides specialized parsing of tabular data from text-based PDF files into programmable data structures.
  • Stream-Based Extraction - Extracts table data by detecting whitespace gaps between characters to determine cell boundaries.
  • PDF to CSV Converters - Transforms static PDF table layouts into structured CSV, JSON, or Excel files for analysis.
  • PDF Table Parsing - Analyzes PDF internal structures to extract tabular data via line or whitespace detection into dataframes.
  • PDF Coordinate Extraction - Identifies tabular regions by grouping text characters based on their horizontal and vertical coordinates in the PDF space.
  • PDF Lattice Detection - Locates tables by identifying intersecting horizontal and vertical lines to define a grid structure.
  • Data Cleaning Procedures - Filters out low-quality table extractions using accuracy and whitespace metrics to ensure high data integrity.
  • Table Extraction Quality Metrics - Provides automated validation of extracted tables using accuracy and whitespace consistency metrics.
  • PDF to Image Rendering - Converts PDF pages into raster images to enable computer vision based detection of structural boundaries.
  • Table Extraction Filters - Automates the cleaning of retrieved data by discarding low-quality extractions using accuracy and whitespace metrics.
  • Table Processing - Library for PDF table extraction.

Star history

Star history chart for atlanhq/camelotStar history chart for atlanhq/camelot

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Camelot

These projects share indexed features with Camelot. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • camelot-dev/camelotcamelot-dev avatar

    camelot-dev/camelot

    3,764View on GitHub↗

    Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts unstructured tables into machine-readable formats such as CSV, JSON, and Excel. The project provides specialized toolsets for different document types, using line detection for ruled tables and whitespace analysis for borderless tables. It includes an optical character recognition system to recover structured data from image-based scanned PDFs that lack a digital text layer. The library handles complex document layouts, including encrypted files, rotated pages, and tables that s

    Python
    View on GitHub↗3,764
  • tabulapdf/tabulatabulapdf avatar

    tabulapdf/tabula

    7,425View on GitHub↗

    Tabula is a PDF table extraction tool and data scraper designed to isolate tabular structures within text-based PDF files. It functions as a converter that transforms these layouts into structured CSV or spreadsheet formats for data recovery and analysis. The project provides both a visual interface for manually selecting table areas and a headless command-line interface. This dual approach allows for a choice between manual data recovery via visual-area selection and the integration of table extraction into automated data pipelines. The extraction process utilizes Java-based PDF parsing and

    CSScsvexcelpdf
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  • katanaml/sparrowkatanaml avatar

    katanaml/sparrow

    5,162View on GitHub↗

    Sparrow is an LLM document extraction platform and vision-based inference engine designed to convert images and PDFs into validated structured data. It functions as an agentic workflow orchestrator that chains classification, extraction, and validation tasks into multi-step pipelines. The system distinguishes itself through a backend-agnostic inference layer that manages models across local GPUs, Apple Silicon, and cloud providers. It employs coordinate-based visual grounding to map extracted text to precise bounding box coordinates and utilizes hint-based model steering to guide attention an

    Pythonagentic-aicomputer-visiondocumentai
    View on GitHub↗5,162
  • datawhalechina/joyful-pandasdatawhalechina avatar

    datawhalechina/joyful-pandas

    5,164View on GitHub↗

    This project is a comprehensive pandas data analysis tutorial and instructional guide designed for learning data manipulation and analysis. It serves as a tabular data processing guide and a manual for time series analysis, providing a structured approach to cleaning, merging, and transforming datasets. The repository functions as a data feature engineering course, providing tutorials on constructing and selecting dataset features to improve machine learning model performance. It also includes a vectorized data operations guide for performing element-wise mathematical computations and matrix

    Jupyter Notebookpandas
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Frequently asked questions

What does atlanhq/camelot do?

Camelot is a Python-based library designed to parse, extract, and clean tabular data from PDF files. It converts table elements from text-based PDF documents into programmable data structures and dataframes.

What are the main features of atlanhq/camelot?

The main features of atlanhq/camelot are: Table Extraction, Stream-Based Extraction, PDF to CSV Converters, PDF Table Parsing, PDF Coordinate Extraction, PDF Lattice Detection, Data Cleaning Procedures, Table Extraction Quality Metrics.

Which projects share features with atlanhq/camelot?

Projects with overlapping indexed features include: camelot-dev/camelot — Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts… tabulapdf/tabula — Tabula is a PDF table extraction tool and data scraper designed to isolate tabular structures within text-based PDF… katanaml/sparrow — Sparrow is an LLM document extraction platform and vision-based inference engine designed to convert images and PDFs… cleanlab/cleanlab — Cleanlab is a data-centric AI library and toolkit designed to improve machine learning model performance by detecting… dathere/qsv — qsv is a high-performance command line toolkit for querying, transforming, and analyzing comma-separated value files.… datawhalechina/joyful-pandas — This project is a comprehensive pandas data analysis tutorial and instructional guide designed for learning data…