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Table Detection Module

Purpose

Table extraction from the PDF file.

What it does

Given a pdf it generates for each table detected a table element containing an array of tableRows.

Dependencies

  • Third-party python library Camelot

How it works

Given a table detected by Camelot this module fills table contents using and array of tableRows that are filled using an array of tableCells where each tableCell is filled by searching words in the document that are contained in cell bounds.

Parameters

Following is an example of the configuration of the table-detection module:

[
  "table-detection",
  {
        "checkDrawings": true,
        "runConfig": [
          {
            "pages": [1, 2, 3], // or [] for all pages
            "flavor": "lattice",
            "table_areas": []
          }
        ]
  }
]
  • checkDrawings: Boolean value to specify if the module should look for table candidates using the previously detected Drawings. Default: true,
  • runConfig: Array of different configurations for the doc
    • pages: List of numbers representing pages.
    • flavor: The parsing method to use ('lattice' or 'stream'). Lattice is used by default. For more information on each parsing method, check this information.
    • table_areas: Array of coordinates forming a box to indicate the position of a table with no outlines or visible borders. Each table_area is a string of the form "x1,y1,x2,y2" where (x1, y1) -> top-left and (x2, y2) -> bottom-right in PDF coordinate space. In PDF coordinate space, the bottom-left corner of the page is the origin, with coordinates (0, 0). This parameter is optional and only used with 'stream' flavor. For more information on table_areas param, feel free to check the camelot documentation.

Accuracy

The accuracy is high.

Limitations

  • Only works with text-based PDFs and not scanned documents.