azure-ai-formrecognizer-java

仓库: sickn33/antigravity-awesome-skills
安装量: 46
排名: #15956

安装

npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill azure-ai-formrecognizer-java

Azure Document Intelligence (Form Recognizer) SDK for Java Build document analysis applications using the Azure AI Document Intelligence SDK for Java. Installation < dependency

< groupId

com.azure </ groupId

< artifactId

azure-ai-formrecognizer </ artifactId

< version

4.2.0-beta.1 </ version

</ dependency

Client Creation DocumentAnalysisClient import com . azure . ai . formrecognizer . documentanalysis . DocumentAnalysisClient ; import com . azure . ai . formrecognizer . documentanalysis . DocumentAnalysisClientBuilder ; import com . azure . core . credential . AzureKeyCredential ; DocumentAnalysisClient client = new DocumentAnalysisClientBuilder ( ) . credential ( new AzureKeyCredential ( "{key}" ) ) . endpoint ( "{endpoint}" ) . buildClient ( ) ; DocumentModelAdministrationClient import com . azure . ai . formrecognizer . documentanalysis . administration . DocumentModelAdministrationClient ; import com . azure . ai . formrecognizer . documentanalysis . administration . DocumentModelAdministrationClientBuilder ; DocumentModelAdministrationClient adminClient = new DocumentModelAdministrationClientBuilder ( ) . credential ( new AzureKeyCredential ( "{key}" ) ) . endpoint ( "{endpoint}" ) . buildClient ( ) ; With DefaultAzureCredential import com . azure . identity . DefaultAzureCredentialBuilder ; DocumentAnalysisClient client = new DocumentAnalysisClientBuilder ( ) . endpoint ( "{endpoint}" ) . credential ( new DefaultAzureCredentialBuilder ( ) . build ( ) ) . buildClient ( ) ; Prebuilt Models Model ID Purpose prebuilt-layout Extract text, tables, selection marks prebuilt-document General document with key-value pairs prebuilt-receipt Receipt data extraction prebuilt-invoice Invoice field extraction prebuilt-businessCard Business card parsing prebuilt-idDocument ID document (passport, license) prebuilt-tax.us.w2 US W2 tax forms Core Patterns Extract Layout import com . azure . ai . formrecognizer . documentanalysis . models . * ; import com . azure . core . util . BinaryData ; import com . azure . core . util . polling . SyncPoller ; import java . io . File ; File document = new File ( "document.pdf" ) ; BinaryData documentData = BinaryData . fromFile ( document . toPath ( ) ) ; SyncPoller < OperationResult , AnalyzeResult

poller

client . beginAnalyzeDocument ( "prebuilt-layout" , documentData ) ; AnalyzeResult result = poller . getFinalResult ( ) ; // Process pages for ( DocumentPage page : result . getPages ( ) ) { System . out . printf ( "Page %d: %.2f x %.2f %s%n" , page . getPageNumber ( ) , page . getWidth ( ) , page . getHeight ( ) , page . getUnit ( ) ) ; // Lines for ( DocumentLine line : page . getLines ( ) ) { System . out . println ( "Line: " + line . getContent ( ) ) ; } // Selection marks (checkboxes) for ( DocumentSelectionMark mark : page . getSelectionMarks ( ) ) { System . out . printf ( "Checkbox: %s (confidence: %.2f)%n" , mark . getSelectionMarkState ( ) , mark . getConfidence ( ) ) ; } } // Tables for ( DocumentTable table : result . getTables ( ) ) { System . out . printf ( "Table: %d rows x %d columns%n" , table . getRowCount ( ) , table . getColumnCount ( ) ) ; for ( DocumentTableCell cell : table . getCells ( ) ) { System . out . printf ( "Cell[%d,%d]: %s%n" , cell . getRowIndex ( ) , cell . getColumnIndex ( ) , cell . getContent ( ) ) ; } } Analyze from URL String documentUrl = "https://example.com/invoice.pdf" ; SyncPoller < OperationResult , AnalyzeResult

poller

client . beginAnalyzeDocumentFromUrl ( "prebuilt-invoice" , documentUrl ) ; AnalyzeResult result = poller . getFinalResult ( ) ; Analyze Receipt SyncPoller < OperationResult , AnalyzeResult

poller

client . beginAnalyzeDocumentFromUrl ( "prebuilt-receipt" , receiptUrl ) ; AnalyzeResult result = poller . getFinalResult ( ) ; for ( AnalyzedDocument doc : result . getDocuments ( ) ) { Map < String , DocumentField

fields

doc . getFields ( ) ; DocumentField merchantName = fields . get ( "MerchantName" ) ; if ( merchantName != null && merchantName . getType ( ) == DocumentFieldType . STRING ) { System . out . printf ( "Merchant: %s (confidence: %.2f)%n" , merchantName . getValueAsString ( ) , merchantName . getConfidence ( ) ) ; } DocumentField transactionDate = fields . get ( "TransactionDate" ) ; if ( transactionDate != null && transactionDate . getType ( ) == DocumentFieldType . DATE ) { System . out . printf ( "Date: %s%n" , transactionDate . getValueAsDate ( ) ) ; } DocumentField items = fields . get ( "Items" ) ; if ( items != null && items . getType ( ) == DocumentFieldType . LIST ) { for ( DocumentField item : items . getValueAsList ( ) ) { Map < String , DocumentField

itemFields

item . getValueAsMap ( ) ; System . out . printf ( "Item: %s, Price: %.2f%n" , itemFields . get ( "Name" ) . getValueAsString ( ) , itemFields . get ( "Price" ) . getValueAsDouble ( ) ) ; } } } General Document Analysis SyncPoller < OperationResult , AnalyzeResult

poller

client . beginAnalyzeDocumentFromUrl ( "prebuilt-document" , documentUrl ) ; AnalyzeResult result = poller . getFinalResult ( ) ; // Key-value pairs for ( DocumentKeyValuePair kvp : result . getKeyValuePairs ( ) ) { System . out . printf ( "Key: %s => Value: %s%n" , kvp . getKey ( ) . getContent ( ) , kvp . getValue ( ) != null ? kvp . getValue ( ) . getContent ( ) : "null" ) ; } Custom Models Build Custom Model import com . azure . ai . formrecognizer . documentanalysis . administration . models . * ; String blobContainerUrl = "{SAS_URL_of_training_data}" ; String prefix = "training-docs/" ; SyncPoller < OperationResult , DocumentModelDetails

poller

adminClient . beginBuildDocumentModel ( blobContainerUrl , DocumentModelBuildMode . TEMPLATE , prefix , new BuildDocumentModelOptions ( ) . setModelId ( "my-custom-model" ) . setDescription ( "Custom invoice model" ) , Context . NONE ) ; DocumentModelDetails model = poller . getFinalResult ( ) ; System . out . println ( "Model ID: " + model . getModelId ( ) ) ; System . out . println ( "Created: " + model . getCreatedOn ( ) ) ; model . getDocumentTypes ( ) . forEach ( ( docType , details ) -> { System . out . println ( "Document type: " + docType ) ; details . getFieldSchema ( ) . forEach ( ( field , schema ) -> { System . out . printf ( " Field: %s (%s)%n" , field , schema . getType ( ) ) ; } ) ; } ) ; Analyze with Custom Model SyncPoller < OperationResult , AnalyzeResult

poller

client . beginAnalyzeDocumentFromUrl ( "my-custom-model" , documentUrl ) ; AnalyzeResult result = poller . getFinalResult ( ) ; for ( AnalyzedDocument doc : result . getDocuments ( ) ) { System . out . printf ( "Document type: %s (confidence: %.2f)%n" , doc . getDocType ( ) , doc . getConfidence ( ) ) ; doc . getFields ( ) . forEach ( ( name , field ) -> { System . out . printf ( "Field '%s': %s (confidence: %.2f)%n" , name , field . getContent ( ) , field . getConfidence ( ) ) ; } ) ; } Compose Models List < String

modelIds

Arrays . asList ( "model-1" , "model-2" , "model-3" ) ; SyncPoller < OperationResult , DocumentModelDetails

poller

adminClient . beginComposeDocumentModel ( modelIds , new ComposeDocumentModelOptions ( ) . setModelId ( "composed-model" ) . setDescription ( "Composed from multiple models" ) ) ; DocumentModelDetails composedModel = poller . getFinalResult ( ) ; Manage Models // List models PagedIterable < DocumentModelSummary

models

adminClient . listDocumentModels ( ) ; for ( DocumentModelSummary summary : models ) { System . out . printf ( "Model: %s, Created: %s%n" , summary . getModelId ( ) , summary . getCreatedOn ( ) ) ; } // Get model details DocumentModelDetails model = adminClient . getDocumentModel ( "model-id" ) ; // Delete model adminClient . deleteDocumentModel ( "model-id" ) ; // Check resource limits ResourceDetails resources = adminClient . getResourceDetails ( ) ; System . out . printf ( "Models: %d / %d%n" , resources . getCustomDocumentModelCount ( ) , resources . getCustomDocumentModelLimit ( ) ) ; Document Classification Build Classifier Map < String , ClassifierDocumentTypeDetails

docTypes

new HashMap <

( ) ; docTypes . put ( "invoice" , new ClassifierDocumentTypeDetails ( ) . setAzureBlobSource ( new AzureBlobContentSource ( containerUrl ) . setPrefix ( "invoices/" ) ) ) ; docTypes . put ( "receipt" , new ClassifierDocumentTypeDetails ( ) . setAzureBlobSource ( new AzureBlobContentSource ( containerUrl ) . setPrefix ( "receipts/" ) ) ) ; SyncPoller < OperationResult , DocumentClassifierDetails

poller

adminClient . beginBuildDocumentClassifier ( docTypes , new BuildDocumentClassifierOptions ( ) . setClassifierId ( "my-classifier" ) ) ; DocumentClassifierDetails classifier = poller . getFinalResult ( ) ; Classify Document SyncPoller < OperationResult , AnalyzeResult

poller

client . beginClassifyDocumentFromUrl ( "my-classifier" , documentUrl , Context . NONE ) ; AnalyzeResult result = poller . getFinalResult ( ) ; for ( AnalyzedDocument doc : result . getDocuments ( ) ) { System . out . printf ( "Classified as: %s (confidence: %.2f)%n" , doc . getDocType ( ) , doc . getConfidence ( ) ) ; } Error Handling import com . azure . core . exception . HttpResponseException ; try { client . beginAnalyzeDocumentFromUrl ( "prebuilt-receipt" , "invalid-url" ) ; } catch ( HttpResponseException e ) { System . out . println ( "Status: " + e . getResponse ( ) . getStatusCode ( ) ) ; System . out . println ( "Error: " + e . getMessage ( ) ) ; } Environment Variables FORM_RECOGNIZER_ENDPOINT = https:// < resource

.cognitiveservices.azure.com/ FORM_RECOGNIZER_KEY = < your-api-key

Trigger Phrases "document intelligence Java" "form recognizer SDK" "extract text from PDF" "OCR document Java" "analyze invoice receipt" "custom document model" "document classification" When to Use This skill is applicable to execute the workflow or actions described in the overview.

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