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DocClassification samples #174

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63 changes: 63 additions & 0 deletions Samples/DataExtractionTest/GO/DataExtraction_test.go
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Original file line number Diff line number Diff line change
Expand Up @@ -302,6 +302,60 @@ func GenericKeyValueTest() (err error) {
return nil
}

//---------------------------------------------------------------------------------------
// The following sample illustrates how to extract document classes from PDF documents.
//---------------------------------------------------------------------------------------

func DocClassifierTest() (err error) {
defer catch(&err)

// Test if the add-on is installed
if !DataExtractionModuleIsModuleAvailable(DataExtractionModuleE_DocClassification) {
fmt.Println("")
fmt.Println("Unable to run Data Extraction: PDFTron SDK Structured Output module not available.")
fmt.Println("-----------------------------------------------------------------------------")
fmt.Println("The Data Extraction suite is an optional add-on, available for download")
fmt.Println("at https://docs.apryse.com/documentation/core/info/modules/. If you have already")
fmt.Println("downloaded this module, ensure that the SDK is able to find the required files")
fmt.Println("using the PDFNetAddResourceSearchPath() function.")
fmt.Println("")
return nil
}

// Simple example: classify pages as a JSON file
fmt.Println("Classify pages as a JSON file")

inputFile := inputPath + "Invoice.pdf"
outputFile := outputPath + "Invoice_Classified.json"
DataExtractionModuleExtractData(inputFile, outputFile, DataExtractionModuleE_DocClassification)

fmt.Println("Result saved in " + outputFile)

// Classify pages as a JSON string
fmt.Println("Classify pages as a JSON string")

inputFile = inputPath + "Scientific_Publication.pdf"
outputFile = outputPath + "Scientific_Publication_Classified.json"
json := DataExtractionModuleExtractData(inputFile, DataExtractionModuleE_DocClassification).(string)
WriteTextToFile(outputFile, json)

fmt.Println("Result saved in " + outputFile)

// Example with customized options:
fmt.Println("Classify pages with customized options")

inputFile = inputPath + "Email.pdf"
outputFile = outputPath + "Email_Classified.json"
options := NewDataExtractionOptions()
// Classes that don't meet the minimum confidence threshold of 70% will not be listed in the output JSON
options.SetMinimumConfidenceThreshold(0.7)
DataExtractionModuleExtractData(inputFile, outputFile, DataExtractionModuleE_DocClassification, options)

fmt.Println("Result saved in " + outputFile)

return nil
}

//---------------------------------------------------------------------------------------

func TestDataExtraction(t *testing.T) {
Expand Down Expand Up @@ -335,13 +389,22 @@ func TestDataExtraction(t *testing.T) {
fmt.Println(fmt.Errorf("Unable to extract form fields data, error: %s", err))
}

//-----------------------------------------------------------------------------------

err = GenericKeyValueTest()
if err != nil {
fmt.Println(fmt.Errorf("Unable to extract key-value pairs, error: %s", err))
}

//-----------------------------------------------------------------------------------

err = DocClassifierTest()
if err != nil {
fmt.Println(fmt.Errorf("Unable to extract document classifications, error: %s", err))
}

//-----------------------------------------------------------------------------------

PDFNetTerminate()
fmt.Println("Done.")
}
56 changes: 54 additions & 2 deletions Samples/DataExtractionTest/PHP/DataExtractionTest.php
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Expand Up @@ -212,7 +212,7 @@ function main()
}

//////////////////////////////////////////////////////////////////////////
// The following sample illustrates how to extract document structure from PDF documents.
// The following sample illustrates how to extract key-value pairs from PDF documents.
//////////////////////////////////////////////////////////////////////////

// Test if the add-on is installed
Expand All @@ -239,7 +239,7 @@ function main()
// Example with customized options:
// Extract Keys & Values from pages 2-4, excluding ads
$options = new DataExtractionOptions();
$options->setPages("2-4");
$options->SetPages("2-4");

$p2ExclusionZones = new RectCollection();
// Exclude the ad on page 2
Expand Down Expand Up @@ -267,6 +267,58 @@ function main()
}
}

//////////////////////////////////////////////////////////////////////////
// The following sample illustrates how to extract document classes from PDF documents.
//////////////////////////////////////////////////////////////////////////

// Test if the add-on is installed
if (!DataExtractionModule::IsModuleAvailable(DataExtractionModule::e_DocClassification)) {
echo(nl2br("\n"));
echo(nl2br("Unable to run Data Extraction: PDFTron SDK Structured Output module not available.\n"));
echo(nl2br("-----------------------------------------------------------------------------\n"));
echo(nl2br("The Data Extraction suite is an optional add-on, available for download\n"));
echo(nl2br("at https://docs.apryse.com/documentation/core/info/modules/. If you have already\n"));
echo(nl2br("downloaded this module, ensure that the SDK is able to find the required files\n"));
echo(nl2br("using the PDFNet::AddResourceSearchPath() function.\n"));
echo(nl2br("\n"));
}
else {
try {
// Simple example: classify pages as a JSON file
echo(nl2br("Classify pages as a JSON file\n"));

$outputFile = $outputPath."Invoice_Classified.json";
DataExtractionModule::ExtractData($inputPath."Invoice.pdf", $outputFile, DataExtractionModule::e_DocClassification);

echo(nl2br("Result saved in " . $outputFile . "\n"));

///////////////////////////////////////////////////////
// Classify pages as a JSON string
echo(nl2br("Classify pages as a JSON string\n"));

$outputFile = $outputPath."Scientific_Publication_Classified.json";
$json = DataExtractionModule::ExtractData($inputPath."Scientific_Publication.pdf", DataExtractionModule::e_DocClassification);
WriteTextToFile($outputFile, $json);

echo(nl2br("Result saved in " . $outputFile . "\n"));

///////////////////////////////////////////////////////
// Example with customized options:
echo(nl2br("Classify pages with customized options\n"));

$options = new DataExtractionOptions();
// Classes that don't meet the minimum confidence threshold of 70% will not be listed in the output JSON
$options->SetMinimumConfidenceThreshold(0.7);
$outputFile = $outputPath."Email_Classified.json";
DataExtractionModule::ExtractData($inputPath."Email.pdf", $outputFile, DataExtractionModule::e_DocClassification, $options);

echo(nl2br("Result saved in " . $outputFile . "\n"));
}
catch(Exception $e) {
echo(nl2br("Unable to extract document structure data, error: " . $e->getMessage() . "\n"));
}
}

//-----------------------------------------------------------------------------------

PDFNet::Terminate();
Expand Down
49 changes: 49 additions & 0 deletions Samples/DataExtractionTest/PYTHON/DataExtractionTest.py
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Expand Up @@ -252,6 +252,55 @@ def main():
print("Unable to extract key-value data, error: " + str(e))


#-----------------------------------------------------------------------------------
# The following sample illustrates how to extract document classes from PDF documents.
#-----------------------------------------------------------------------------------

# Test if the add-on is installed
if not DataExtractionModule.IsModuleAvailable(DataExtractionModule.e_DocClassification):
print("")
print("Unable to run Data Extraction: PDFTron SDK Structured Output module not available.")
print("-----------------------------------------------------------------------------")
print("The Data Extraction suite is an optional add-on, available for download")
print("at https://docs.apryse.com/documentation/core/info/modules/. If you have already")
print("downloaded this module, ensure that the SDK is able to find the required files")
print("using the PDFNet.AddResourceSearchPath() function.")
print("")
else:
try:
# Simple example: classify pages as a JSON file
print("Classify pages as a JSON file")

outputFile = outputPath + "Invoice_Classified.json"
DataExtractionModule.ExtractData(inputPath + "Invoice.pdf", outputFile, DataExtractionModule.e_DocClassification)

print("Result saved in " + outputFile)

#------------------------------------------------------
# Classify pages as a JSON string
print("Classify pages as a JSON string")

outputFile = outputPath + "Scientific_Publication_Classified.json"
json = DataExtractionModule.ExtractData(inputPath + "Scientific_Publication.pdf", DataExtractionModule.e_DocClassification)
WriteTextToFile(outputFile, json)

print("Result saved in " + outputFile)

#------------------------------------------------------
# Example with customized options:
print("Classify pages with customized options")

options = DataExtractionOptions()
# Classes that don't meet the minimum confidence threshold of 70% will not be listed in the output JSON
options.SetMinimumConfidenceThreshold(0.7)
outputFile = outputPath + "Email_Classified.json"
DataExtractionModule.ExtractData(inputPath + "Email.pdf", outputFile, DataExtractionModule.e_DocClassification, options)

print("Result saved in " + outputFile)

except Exception as e:
print("Unable to extract document structure data, error: " + str(e))

PDFNet.Terminate()
print("Done.")

Expand Down
56 changes: 56 additions & 0 deletions Samples/DataExtractionTest/RUBY/DataExtractionTest.rb
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Expand Up @@ -200,6 +200,11 @@ def main()
end
end

#-----------------------------------------------------------------------------------
# The following sample illustrates how to extract key-value pairs from PDF documents.
#-----------------------------------------------------------------------------------

# Test if the add-on is installed
if !DataExtractionModule.IsModuleAvailable(DataExtractionModule::E_GenericKeyValue) then
puts ""
puts "Unable to run Data Extraction: PDFTron SDK AIFormFieldExtractor module not available."
Expand Down Expand Up @@ -244,6 +249,57 @@ def main()
end
end

#-----------------------------------------------------------------------------------
# The following sample illustrates how to extract document classes from PDF documents.
#-----------------------------------------------------------------------------------

# Test if the add-on is installed
if !DataExtractionModule.IsModuleAvailable(DataExtractionModule::E_DocClassification) then
puts ""
puts "Unable to run Data Extraction: PDFTron SDK Structured Output module not available."
puts "-----------------------------------------------------------------------------"
puts "The Data Extraction suite is an optional add-on, available for download"
puts "at https://docs.apryse.com/documentation/core/info/modules/. If you have already"
puts "downloaded this module, ensure that the SDK is able to find the required files"
puts "using the PDFNet.AddResourceSearchPath() function."
puts ""
else
begin
# Simple example: classify pages as a JSON file
puts "Classify pages as a JSON file"

outputFile = $outputPath + "Invoice_Classified.json"
DataExtractionModule.ExtractData($inputPath + "Invoice.pdf", outputFile, DataExtractionModule::E_DocClassification)

puts "Result saved in " + outputFile

#------------------------------------------------------
# Classify pages as a JSON string
puts "Classify pages as a JSON string"

outputFile = $outputPath + "Scientific_Publication_Classified.json"
json = DataExtractionModule.ExtractData($inputPath + "Scientific_Publication.pdf", DataExtractionModule::E_DocClassification)
File.open(outputFile, 'w') { |file| file.write(json) }

puts "Result saved in " + outputFile

#------------------------------------------------------
# Example with customized options:
puts "Classify pages with customized options"

options = DataExtractionOptions.new()
# Classes that don't meet the minimum confidence threshold of 70% will not be listed in the output JSON
options.SetMinimumConfidenceThreshold(0.7)
outputFile = $outputPath + "Email_Classified.json"
DataExtractionModule.ExtractData($inputPath + "Email.pdf", outputFile, DataExtractionModule::E_DocClassification, options)

puts "Result saved in " + outputFile

rescue => error
puts "Unable to extract document structure data, error: " + error.message
end
end

#-----------------------------------------------------------------------------------

PDFNet.Terminate
Expand Down
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