Xojo Plugin Requires Chilkat v11.7.0+
Xojo Plugin
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.)Chilkat Xojo Plugin Downloads
Dim success As Boolean
success = 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 New Chilkat.Pdf
success = pdf.LoadFile("qa_data/pdf/mixed_text_image.pdf")
If (success = False) Then
System.DebugLog(pdf.LastErrorText)
Return
End If
Dim json As New Chilkat.JsonObject
Dim jsonOut As New Chilkat.JsonObject
// "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
System.DebugLog(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.
System.DebugLog("Rating: " + jsonOut.StringOf("quality.rating"))
// Is the PDF tagged (does it have a structure tree)?
System.DebugLog("Tagged: " + Str(jsonOut.BoolOf("quality.tagged")))
// The pages that are images only and would need OCR, such as "2" or "4,9".
System.DebugLog("Pages needing OCR: " + jsonOut.StringOf("quality.pagesNeedingOcr"))
// The per-page report.
Dim j As Int32
Dim count_j As Int32
Dim i As Int32
i = 0
Dim count_i As Int32
count_i = jsonOut.SizeOfArray("quality.pages")
While i < count_i
jsonOut.I = i
// textSource is "text" (real text), "ocrLayer" (invisible text over an image),
// "imageOnly" (needs OCR), "mixed", or "empty".
System.DebugLog("Page " + Str(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")
While j < count_j
jsonOut.J = j
System.DebugLog(" " + jsonOut.StringOf("quality.pages[i].issues[j].code") + ": " + jsonOut.StringOf("quality.pages[i].issues[j].message"))
j = j + 1
Wend
i = i + 1
Wend
// Decide what to do with the document:
If (jsonOut.StringOf("quality.rating") = "none") Then
System.DebugLog("No extractable text; the whole document needs OCR.")
Else
If (jsonOut.StringOf("quality.pagesNeedingOcr") <> "") Then
System.DebugLog("Some pages need OCR; the remaining pages can be extracted with the text or markdown operation.")
Else
System.DebugLog("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.