B4X Requires Chilkat v11.7.0+

Assess PDF Text Quality Before Extracting

See more PDF Text Extraction Examples

Demonstrates the "assess" operation, which returns only the quality report: whether the text can be trusted, which pages are scanned images that need OCR, and how each page's text was found. Use it to triage documents before extracting. (Chilkat does not perform OCR.) B4X

Dim success As Boolean = False

'  This example requires the Chilkat API to have been previously unlocked.
'  See Global Unlock Sample for sample code.

'  The PDF used in this example (page 2 is a scanned image with no text) is available at mixed_text_image.pdf

Dim pdf As ChilkatPdf
pdf.Initialize("pdf")
success = pdf.LoadFile("qa_data/pdf/mixed_text_image.pdf")
If success = False Then
    Log(pdf.LastErrorText)
    Return
End If


Dim json As ChilkatJsonObject
json.Initialize
Dim jsonOut As ChilkatJsonObject
jsonOut.Initialize

'  "assess" computes the quality report without producing any text.
'  It is fast, and it is always allowed, even for an encrypted PDF that forbids copying.
success = pdf.ExtractText("assess", json, jsonOut)
If success = False Then
    Log(pdf.LastErrorText)
    Return
End If


'  The overall rating is the worst rating among the pages that have text:
'  "good", "fair", "poor", or "none" when there is no text at all.
Log("Rating: " & jsonOut.StringOf("quality.rating"))

'  Is the PDF tagged (does it have a structure tree)?
Log("Tagged: " & jsonOut.BoolOf("quality.tagged"))

'  The pages that are images only and would need OCR, such as "2" or "4,9".
Log("Pages needing OCR: " & jsonOut.StringOf("quality.pagesNeedingOcr"))

'  The per-page report.
Dim j As Int
Dim count_j As Int
Dim i As Int = 0
Dim count_i As Int = jsonOut.SizeOfArray("quality.pages")
Do While i < count_i
    jsonOut.I = i
    '  textSource is "text" (real text), "ocrLayer" (invisible text over an image),
    '  "imageOnly" (needs OCR), "mixed", or "empty".
    Log("Page " & jsonOut.IntOf("quality.pages[i].page") & ": rating " & jsonOut.StringOf("quality.pages[i].rating") & ", textSource " & jsonOut.StringOf("quality.pages[i].textSource"))
    '  Each issue has a machine-readable code and a sentence.
    j = 0
    count_j = jsonOut.SizeOfArray("quality.pages[i].issues")
    Do While j < count_j
        jsonOut.J = j
        Log("    " & jsonOut.StringOf("quality.pages[i].issues[j].code") & ": " & jsonOut.StringOf("quality.pages[i].issues[j].message"))
        j = j + 1
    Loop
    i = i + 1
Loop

'  Decide what to do with the document:
If jsonOut.StringOf("quality.rating") = "none" Then
    Log("No extractable text; the whole document needs OCR.")
Else
    If jsonOut.StringOf("quality.pagesNeedingOcr") <> "" Then
        Log("Some pages need OCR; the remaining pages can be extracted with the text or markdown operation.")
    Else
        Log("All pages can be extracted.")
    End If

End If


'  Sample output:

'  Rating: good
'  Tagged: false
'  Pages needing OCR: 2
'  Page 1: rating good, textSource text
'  Page 2: rating none, textSource imageOnly
'      imageOnly: No text; page is a scanned image
'  Page 3: rating good, textSource text
'  Some pages need OCR; the remaining pages can be extracted with the text or markdown operation.