Ada lebih banyak contoh AWS SDK yang tersedia di repo Contoh [SDK AWS Doc](https://github.com/awsdocs/aws-doc-sdk-examples). GitHub
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# Contoh kode untuk Amazon Texttract menggunakan AWS SDKs
Contoh kode berikut menunjukkan cara menggunakan Amazon Textract dengan AWS perangkat pengembangan perangkat lunak (SDK).
*Tindakan* merupakan kutipan kode dari program yang lebih besar dan harus dijalankan dalam konteks. Sementara tindakan menunjukkan cara memanggil fungsi layanan individual, Anda dapat melihat tindakan dalam konteks dalam skenario terkait.
*Skenario* adalah contoh kode yang menunjukkan kepada Anda bagaimana menyelesaikan tugas tertentu dengan memanggil beberapa fungsi dalam layanan atau dikombinasikan dengan yang lain Layanan AWS.
**Sumber daya lainnya**
+ **[Panduan Pengembang Amazon Texttract](https://docs.aws.amazon.com/textract/latest/dg/what-is.html)** - Informasi lebih lanjut tentang Amazon Ttract.
+ **[Referensi API Amazon Textract](https://docs.aws.amazon.com/textract/latest/dg/API_Reference.html)** — Detail tentang semua tindakan Amazon Textract yang tersedia.
+ **[AWS Pusat Pengembang](https://aws.amazon.com/developer/code-examples/?awsf.sdk-code-examples-product=product%23textract)** - Contoh kode yang dapat Anda filter berdasarkan kategori atau pencarian teks lengkap.
+ **[AWS Contoh SDK](https://github.com/awsdocs/aws-doc-sdk-examples)** — GitHub repo dengan kode lengkap dalam bahasa pilihan. Termasuk instruksi untuk mengatur dan menjalankan kode.
**Contents**
+ [Hal-hal mendasar](textract_code_examples_basics.md)
+ [Tindakan](textract_code_examples_actions.md)
+ [`AnalyzeDocument`](textract_example_textract_AnalyzeDocument_section.md)
+ [`DetectDocumentText`](textract_example_textract_DetectDocumentText_section.md)
+ [`GetDocumentAnalysis`](textract_example_textract_GetDocumentAnalysis_section.md)
+ [`StartDocumentAnalysis`](textract_example_textract_StartDocumentAnalysis_section.md)
+ [`StartDocumentTextDetection`](textract_example_textract_StartDocumentTextDetection_section.md)
+ [Skenario](textract_code_examples_scenarios.md)
+ [Membuat aplikasi penjelajah Amazon Textract](textract_example_cross_TextractExplorer_section.md)
+ [Buat aplikasi untuk menganalisis umpan balik pelanggan](textract_example_cross_FSA_section.md)
+ [Mendeteksi entitas dalam teks yang diekstrak dari gambar](textract_example_cross_TextractComprehendDetectEntities_section.md)
+ [Memulai dengan analisis dokumen](textract_example_textract_Scenario_GettingStarted_section.md)
# Contoh dasar untuk Amazon Texttract menggunakan AWS SDKs
Contoh kode berikut menunjukkan cara menggunakan dasar-dasar Amazon Textract dengan. AWS SDKs
**Contents**
+ [Tindakan](textract_code_examples_actions.md)
+ [`AnalyzeDocument`](textract_example_textract_AnalyzeDocument_section.md)
+ [`DetectDocumentText`](textract_example_textract_DetectDocumentText_section.md)
+ [`GetDocumentAnalysis`](textract_example_textract_GetDocumentAnalysis_section.md)
+ [`StartDocumentAnalysis`](textract_example_textract_StartDocumentAnalysis_section.md)
+ [`StartDocumentTextDetection`](textract_example_textract_StartDocumentTextDetection_section.md)
# Tindakan untuk Amazon Texttract menggunakan AWS SDKs
Contoh kode berikut menunjukkan cara melakukan tindakan Amazon Textract individual dengan. AWS SDKs Setiap contoh menyertakan tautan ke GitHub, di mana Anda dapat menemukan instruksi untuk mengatur dan menjalankan kode.
Kutipan ini memanggil Amazon Textract API dan merupakan kutipan kode dari program yang lebih besar yang harus dijalankan dalam konteks. Anda dapat melihat tindakan dalam konteks di[Skenario untuk Amazon Texttract menggunakan AWS SDKs](textract_code_examples_scenarios.md).
Contoh berikut hanya mencakup tindakan yang paling umum digunakan. Untuk daftar lengkapnya, lihat Referensi [API Amazon Texttract](https://docs.aws.amazon.com/textract/latest/dg/API_Reference.html).
**Topics**
+ [`AnalyzeDocument`](textract_example_textract_AnalyzeDocument_section.md)
+ [`DetectDocumentText`](textract_example_textract_DetectDocumentText_section.md)
+ [`GetDocumentAnalysis`](textract_example_textract_GetDocumentAnalysis_section.md)
+ [`StartDocumentAnalysis`](textract_example_textract_StartDocumentAnalysis_section.md)
+ [`StartDocumentTextDetection`](textract_example_textract_StartDocumentTextDetection_section.md)
# Gunakan `AnalyzeDocument` dengan AWS SDK atau CLI
Contoh kode berikut menunjukkan cara menggunakan`AnalyzeDocument`.
------
#### [ CLI ]
**AWS CLI**
**Untuk menganalisis teks dalam dokumen**
`analyze-document`Contoh berikut menunjukkan cara menganalisis teks dalam dokumen.
Linux/macOS:
```
aws textract analyze-document \
--document '{"S3Object":{"Bucket":"bucket","Name":"document"}}' \
--feature-types '["TABLES","FORMS"]'
```
Windows:
```
aws textract analyze-document \
--document "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
--feature-types "[\"TABLES\",\"FORMS\"]" \
--region region-name
```
Output:
```
{
"Blocks": [
{
"Geometry": {
"BoundingBox": {
"Width": 1.0,
"Top": 0.0,
"Left": 0.0,
"Height": 1.0
},
"Polygon": [
{
"Y": 0.0,
"X": 0.0
},
{
"Y": 0.0,
"X": 1.0
},
{
"Y": 1.0,
"X": 1.0
},
{
"Y": 1.0,
"X": 0.0
}
]
},
"Relationships": [
{
"Type": "CHILD",
"Ids": [
"87586964-d50d-43e2-ace5-8a890657b9a0",
"a1e72126-21d9-44f4-a8d6-5c385f9002ba",
"e889d012-8a6b-4d2e-b7cd-7a8b327d876a"
]
}
],
"BlockType": "PAGE",
"Id": "c2227f12-b25d-4e1f-baea-1ee180d926b2"
}
],
"DocumentMetadata": {
"Pages": 1
}
}
```
Untuk informasi selengkapnya, lihat Menganalisis Teks Dokumen dengan Amazon Ttract di Panduan Pengembang *Amazon Texttract*
+ Untuk detail API, lihat [AnalyzeDocument](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/analyze-document.html)di *Referensi AWS CLI Perintah*.
------
#### [ Java ]
**SDK untuk Java 2.x**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/textract#code-examples).
```
import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.textract.TextractClient;
import software.amazon.awssdk.services.textract.model.AnalyzeDocumentRequest;
import software.amazon.awssdk.services.textract.model.Document;
import software.amazon.awssdk.services.textract.model.FeatureType;
import software.amazon.awssdk.services.textract.model.AnalyzeDocumentResponse;
import software.amazon.awssdk.services.textract.model.Block;
import software.amazon.awssdk.services.textract.model.TextractException;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
/**
* Before running this Java V2 code example, set up your development
* environment, including your credentials.
*
* For more information, see the following documentation topic:
*
* https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
*/
public class AnalyzeDocument {
public static void main(String[] args) {
final String usage = """
Usage:
\s
Where:
sourceDoc - The path where the document is located (must be an image, for example, C:/AWS/book.png).\s
""";
if (args.length != 1) {
System.out.println(usage);
System.exit(1);
}
String sourceDoc = args[0];
Region region = Region.US_EAST_2;
TextractClient textractClient = TextractClient.builder()
.region(region)
.build();
analyzeDoc(textractClient, sourceDoc);
textractClient.close();
}
public static void analyzeDoc(TextractClient textractClient, String sourceDoc) {
try {
InputStream sourceStream = new FileInputStream(new File(sourceDoc));
SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
// Get the input Document object as bytes
Document myDoc = Document.builder()
.bytes(sourceBytes)
.build();
List featureTypes = new ArrayList();
featureTypes.add(FeatureType.FORMS);
featureTypes.add(FeatureType.TABLES);
AnalyzeDocumentRequest analyzeDocumentRequest = AnalyzeDocumentRequest.builder()
.featureTypes(featureTypes)
.document(myDoc)
.build();
AnalyzeDocumentResponse analyzeDocument = textractClient.analyzeDocument(analyzeDocumentRequest);
List docInfo = analyzeDocument.blocks();
Iterator blockIterator = docInfo.iterator();
while (blockIterator.hasNext()) {
Block block = blockIterator.next();
System.out.println("The block type is " + block.blockType().toString());
}
} catch (TextractException | FileNotFoundException e) {
System.err.println(e.getMessage());
System.exit(1);
}
}
}
```
+ Untuk detail API, lihat [AnalyzeDocument](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/AnalyzeDocument)di *Referensi AWS SDK for Java 2.x API*.
------
#### [ Python ]
**SDK untuk Python (Boto3)**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples).
```
class TextractWrapper:
"""Encapsulates Textract functions."""
def __init__(self, textract_client, s3_resource, sqs_resource):
"""
:param textract_client: A Boto3 Textract client.
:param s3_resource: A Boto3 Amazon S3 resource.
:param sqs_resource: A Boto3 Amazon SQS resource.
"""
self.textract_client = textract_client
self.s3_resource = s3_resource
self.sqs_resource = sqs_resource
def analyze_file(
self, feature_types, *, document_file_name=None, document_bytes=None
):
"""
Detects text and additional elements, such as forms or tables, in a local image
file or from in-memory byte data.
The image must be in PNG or JPG format.
:param feature_types: The types of additional document features to detect.
:param document_file_name: The name of a document image file.
:param document_bytes: In-memory byte data of a document image.
:return: The response from Amazon Textract, including a list of blocks
that describe elements detected in the image.
"""
if document_file_name is not None:
with open(document_file_name, "rb") as document_file:
document_bytes = document_file.read()
try:
response = self.textract_client.analyze_document(
Document={"Bytes": document_bytes}, FeatureTypes=feature_types
)
logger.info("Detected %s blocks.", len(response["Blocks"]))
except ClientError:
logger.exception("Couldn't detect text.")
raise
else:
return response
```
+ Untuk detail API, lihat [AnalyzeDocument](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/AnalyzeDocument)di *AWS SDK for Python (Boto3) Referensi* API.
------
#### [ SAP ABAP ]
**SDK for SAP ABAP**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples).
```
"Detects text and additional elements, such as forms or tables,"
"in a local image file or from in-memory byte data."
"The image must be in PNG or JPG format."
"Create ABAP objects for feature type."
"Add TABLES to return information about the tables."
"Add FORMS to return detected form data."
"To perform both types of analysis, add TABLES and FORMS to FeatureTypes."
DATA(lt_featuretypes) = VALUE /aws1/cl_texfeaturetypes_w=>tt_featuretypes(
( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'FORMS' ) )
( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'TABLES' ) ) ).
"Create an ABAP object for the Amazon Simple Storage Service (Amazon S3) object."
DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
iv_name = iv_s3object ).
"Create an ABAP object for the document."
DATA(lo_document) = NEW /aws1/cl_texdocument( io_s3object = lo_s3object ).
"Analyze document stored in Amazon S3."
TRY.
oo_result = lo_tex->analyzedocument( "oo_result is returned for testing purposes."
io_document = lo_document
it_featuretypes = lt_featuretypes ).
LOOP AT oo_result->get_blocks( ) INTO DATA(lo_block).
IF lo_block->get_text( ) = 'INGREDIENTS: POWDERED SUGAR* (CANE SUGAR,'.
MESSAGE 'Found text in the doc: ' && lo_block->get_text( ) TYPE 'I'.
ENDIF.
ENDLOOP.
MESSAGE 'Analyze document completed.' TYPE 'I'.
CATCH /aws1/cx_texaccessdeniedex.
MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
CATCH /aws1/cx_texbaddocumentex.
MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
CATCH /aws1/cx_texdocumenttoolargeex.
MESSAGE 'The document is too large.' TYPE 'E'.
CATCH /aws1/cx_texhlquotaexceededex.
MESSAGE 'Human loop quota exceeded.' TYPE 'E'.
CATCH /aws1/cx_texinternalservererr.
MESSAGE 'Internal server error.' TYPE 'E'.
CATCH /aws1/cx_texinvalidparameterex.
MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
CATCH /aws1/cx_texinvalids3objectex.
MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
CATCH /aws1/cx_texprovthruputexcdex.
MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
CATCH /aws1/cx_texthrottlingex.
MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
CATCH /aws1/cx_texunsupporteddocex.
MESSAGE 'The document is not supported.' TYPE 'E'.
ENDTRY.
```
+ Untuk detail API, lihat [AnalyzeDocument](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)di *AWS SDK untuk referensi SAP ABAP* API.
------
# Gunakan `DetectDocumentText` dengan AWS SDK atau CLI
Contoh kode berikut menunjukkan cara menggunakan`DetectDocumentText`.
------
#### [ CLI ]
**AWS CLI**
**Untuk mendeteksi teks dalam dokumen**
Berikut `detect-document-text` ini Contoh berikut menunjukkan cara mendeteksi teks dalam dokumen.
Linux/macOS:
```
aws textract detect-document-text \
--document '{"S3Object":{"Bucket":"bucket","Name":"document"}}'
```
Windows:
```
aws textract detect-document-text \
--document "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
--region region-name
```
Output:
```
{
"Blocks": [
{
"Geometry": {
"BoundingBox": {
"Width": 1.0,
"Top": 0.0,
"Left": 0.0,
"Height": 1.0
},
"Polygon": [
{
"Y": 0.0,
"X": 0.0
},
{
"Y": 0.0,
"X": 1.0
},
{
"Y": 1.0,
"X": 1.0
},
{
"Y": 1.0,
"X": 0.0
}
]
},
"Relationships": [
{
"Type": "CHILD",
"Ids": [
"896a9f10-9e70-4412-81ce-49ead73ed881",
"0da18623-dc4c-463d-a3d1-9ac050e9e720",
"167338d7-d38c-4760-91f1-79a8ec457bb2"
]
}
],
"BlockType": "PAGE",
"Id": "21f0535e-60d5-4bc7-adf2-c05dd851fa25"
},
{
"Relationships": [
{
"Type": "CHILD",
"Ids": [
"62490c26-37ea-49fa-8034-7a9ff9369c9c",
"1e4f3f21-05bd-4da9-ba10-15d01e66604c"
]
}
],
"Confidence": 89.11581420898438,
"Geometry": {
"BoundingBox": {
"Width": 0.33642634749412537,
"Top": 0.17169663310050964,
"Left": 0.13885067403316498,
"Height": 0.49159330129623413
},
"Polygon": [
{
"Y": 0.17169663310050964,
"X": 0.13885067403316498
},
{
"Y": 0.17169663310050964,
"X": 0.47527703642845154
},
{
"Y": 0.6632899641990662,
"X": 0.47527703642845154
},
{
"Y": 0.6632899641990662,
"X": 0.13885067403316498
}
]
},
"Text": "He llo,",
"BlockType": "LINE",
"Id": "896a9f10-9e70-4412-81ce-49ead73ed881"
},
{
"Relationships": [
{
"Type": "CHILD",
"Ids": [
"19b28058-9516-4352-b929-64d7cef29daf"
]
}
],
"Confidence": 85.5694351196289,
"Geometry": {
"BoundingBox": {
"Width": 0.33182239532470703,
"Top": 0.23131252825260162,
"Left": 0.5091826915740967,
"Height": 0.3766750991344452
},
"Polygon": [
{
"Y": 0.23131252825260162,
"X": 0.5091826915740967
},
{
"Y": 0.23131252825260162,
"X": 0.8410050868988037
},
{
"Y": 0.607987642288208,
"X": 0.8410050868988037
},
{
"Y": 0.607987642288208,
"X": 0.5091826915740967
}
]
},
"Text": "worlc",
"BlockType": "LINE",
"Id": "0da18623-dc4c-463d-a3d1-9ac050e9e720"
}
],
"DocumentMetadata": {
"Pages": 1
}
}
```
Untuk informasi selengkapnya, lihat Mendeteksi Teks Dokumen dengan Amazon Textract di Panduan Pengembang Amazon *Textract*
+ Untuk detail API, lihat [DetectDocumentText](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/detect-document-text.html)di *Referensi AWS CLI Perintah*.
------
#### [ Java ]
**SDK untuk Java 2.x**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/textract#code-examples).
Mendeteksi teks dari dokumen input.
```
import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.textract.TextractClient;
import software.amazon.awssdk.services.textract.model.Document;
import software.amazon.awssdk.services.textract.model.DetectDocumentTextRequest;
import software.amazon.awssdk.services.textract.model.DetectDocumentTextResponse;
import software.amazon.awssdk.services.textract.model.Block;
import software.amazon.awssdk.services.textract.model.DocumentMetadata;
import software.amazon.awssdk.services.textract.model.TextractException;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
import java.util.List;
/**
* Before running this Java V2 code example, set up your development
* environment, including your credentials.
*
* For more information, see the following documentation topic:
*
* https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
*/
public class DetectDocumentText {
public static void main(String[] args) {
final String usage = """
Usage:
\s
Where:
sourceDoc - The path where the document is located (must be an image, for example, C:/AWS/book.png).\s
""";
if (args.length != 1) {
System.out.println(usage);
System.exit(1);
}
String sourceDoc = args[0];
Region region = Region.US_EAST_2;
TextractClient textractClient = TextractClient.builder()
.region(region)
.build();
detectDocText(textractClient, sourceDoc);
textractClient.close();
}
public static void detectDocText(TextractClient textractClient, String sourceDoc) {
try {
InputStream sourceStream = new FileInputStream(new File(sourceDoc));
SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
// Get the input Document object as bytes.
Document myDoc = Document.builder()
.bytes(sourceBytes)
.build();
DetectDocumentTextRequest detectDocumentTextRequest = DetectDocumentTextRequest.builder()
.document(myDoc)
.build();
// Invoke the Detect operation.
DetectDocumentTextResponse textResponse = textractClient.detectDocumentText(detectDocumentTextRequest);
List docInfo = textResponse.blocks();
for (Block block : docInfo) {
System.out.println("The block type is " + block.blockType().toString());
}
DocumentMetadata documentMetadata = textResponse.documentMetadata();
System.out.println("The number of pages in the document is " + documentMetadata.pages());
} catch (TextractException | FileNotFoundException e) {
System.err.println(e.getMessage());
System.exit(1);
}
}
}
```
Mendeteksi teks dari dokumen yang terletak di bucket Amazon S3.
```
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.textract.model.S3Object;
import software.amazon.awssdk.services.textract.TextractClient;
import software.amazon.awssdk.services.textract.model.Document;
import software.amazon.awssdk.services.textract.model.DetectDocumentTextRequest;
import software.amazon.awssdk.services.textract.model.DetectDocumentTextResponse;
import software.amazon.awssdk.services.textract.model.Block;
import software.amazon.awssdk.services.textract.model.DocumentMetadata;
import software.amazon.awssdk.services.textract.model.TextractException;
/**
* Before running this Java V2 code example, set up your development
* environment, including your credentials.
*
* For more information, see the following documentation topic:
*
* https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
*/
public class DetectDocumentTextS3 {
public static void main(String[] args) {
final String usage = """
Usage:
\s
Where:
bucketName - The name of the Amazon S3 bucket that contains the document.\s
docName - The document name (must be an image, i.e., book.png).\s
""";
if (args.length != 2) {
System.out.println(usage);
System.exit(1);
}
String bucketName = args[0];
String docName = args[1];
Region region = Region.US_WEST_2;
TextractClient textractClient = TextractClient.builder()
.region(region)
.build();
detectDocTextS3(textractClient, bucketName, docName);
textractClient.close();
}
public static void detectDocTextS3(TextractClient textractClient, String bucketName, String docName) {
try {
S3Object s3Object = S3Object.builder()
.bucket(bucketName)
.name(docName)
.build();
// Create a Document object and reference the s3Object instance.
Document myDoc = Document.builder()
.s3Object(s3Object)
.build();
DetectDocumentTextRequest detectDocumentTextRequest = DetectDocumentTextRequest.builder()
.document(myDoc)
.build();
DetectDocumentTextResponse textResponse = textractClient.detectDocumentText(detectDocumentTextRequest);
for (Block block : textResponse.blocks()) {
System.out.println("The block type is " + block.blockType().toString());
}
DocumentMetadata documentMetadata = textResponse.documentMetadata();
System.out.println("The number of pages in the document is " + documentMetadata.pages());
} catch (TextractException e) {
System.err.println(e.getMessage());
System.exit(1);
}
}
}
```
+ Untuk detail API, lihat [DetectDocumentText](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/DetectDocumentText)di *Referensi AWS SDK for Java 2.x API*.
------
#### [ Python ]
**SDK untuk Python (Boto3)**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples).
```
class TextractWrapper:
"""Encapsulates Textract functions."""
def __init__(self, textract_client, s3_resource, sqs_resource):
"""
:param textract_client: A Boto3 Textract client.
:param s3_resource: A Boto3 Amazon S3 resource.
:param sqs_resource: A Boto3 Amazon SQS resource.
"""
self.textract_client = textract_client
self.s3_resource = s3_resource
self.sqs_resource = sqs_resource
def detect_file_text(self, *, document_file_name=None, document_bytes=None):
"""
Detects text elements in a local image file or from in-memory byte data.
The image must be in PNG or JPG format.
:param document_file_name: The name of a document image file.
:param document_bytes: In-memory byte data of a document image.
:return: The response from Amazon Textract, including a list of blocks
that describe elements detected in the image.
"""
if document_file_name is not None:
with open(document_file_name, "rb") as document_file:
document_bytes = document_file.read()
try:
response = self.textract_client.detect_document_text(
Document={"Bytes": document_bytes}
)
logger.info("Detected %s blocks.", len(response["Blocks"]))
except ClientError:
logger.exception("Couldn't detect text.")
raise
else:
return response
```
+ Untuk detail API, lihat [DetectDocumentText](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/DetectDocumentText)di *AWS SDK for Python (Boto3) Referensi* API.
------
#### [ SAP ABAP ]
**SDK for SAP ABAP**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples).
```
"Detects text in the input document."
"Amazon Textract can detect lines of text and the words that make up a line of text."
"The input document must be in one of the following image formats: JPEG, PNG, PDF, or TIFF."
"Create an ABAP object for the Amazon S3 object."
DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
iv_name = iv_s3object ).
"Create an ABAP object for the document."
DATA(lo_document) = NEW /aws1/cl_texdocument( io_s3object = lo_s3object ).
"Analyze document stored in Amazon S3."
TRY.
oo_result = lo_tex->detectdocumenttext( io_document = lo_document ). "oo_result is returned for testing purposes."
LOOP AT oo_result->get_blocks( ) INTO DATA(lo_block).
IF lo_block->get_text( ) = 'INGREDIENTS: POWDERED SUGAR* (CANE SUGAR,'.
MESSAGE 'Found text in the doc: ' && lo_block->get_text( ) TYPE 'I'.
ENDIF.
ENDLOOP.
DATA(lo_metadata) = oo_result->get_documentmetadata( ).
MESSAGE 'The number of pages in the document is ' && lo_metadata->ask_pages( ) TYPE 'I'.
MESSAGE 'Detect document text completed.' TYPE 'I'.
CATCH /aws1/cx_texaccessdeniedex.
MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
CATCH /aws1/cx_texbaddocumentex.
MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
CATCH /aws1/cx_texdocumenttoolargeex.
MESSAGE 'The document is too large.' TYPE 'E'.
CATCH /aws1/cx_texinternalservererr.
MESSAGE 'Internal server error.' TYPE 'E'.
CATCH /aws1/cx_texinvalidparameterex.
MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
CATCH /aws1/cx_texinvalids3objectex.
MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
CATCH /aws1/cx_texprovthruputexcdex.
MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
CATCH /aws1/cx_texthrottlingex.
MESSAGE 'The request processing exceeded the limit' TYPE 'E'.
CATCH /aws1/cx_texunsupporteddocex.
MESSAGE 'The document is not supported.' TYPE 'E'.
ENDTRY.
```
+ Untuk detail API, lihat [DetectDocumentText](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)di *AWS SDK untuk referensi SAP ABAP* API.
------
# Gunakan `GetDocumentAnalysis` dengan AWS SDK atau CLI
Contoh kode berikut menunjukkan cara menggunakan`GetDocumentAnalysis`.
Contoh tindakan adalah kutipan kode dari program yang lebih besar dan harus dijalankan dalam konteks. Anda dapat melihat tindakan ini dalam konteks dalam contoh kode berikut:
+ [Memulai dengan analisis dokumen](textract_example_textract_Scenario_GettingStarted_section.md)
------
#### [ CLI ]
**AWS CLI**
**Untuk mendapatkan hasil analisis teks asinkron dari dokumen multi-halaman**
`get-document-analysis`Contoh berikut menunjukkan cara mendapatkan hasil analisis teks asinkron dari dokumen multi-halaman.
```
aws textract get-document-analysis \
--job-id df7cf32ebbd2a5de113535fcf4d921926a701b09b4e7d089f3aebadb41e0712b \
--max-results 1000
```
Output:
```
{
"Blocks": [
{
"Geometry": {
"BoundingBox": {
"Width": 1.0,
"Top": 0.0,
"Left": 0.0,
"Height": 1.0
},
"Polygon": [
{
"Y": 0.0,
"X": 0.0
},
{
"Y": 0.0,
"X": 1.0
},
{
"Y": 1.0,
"X": 1.0
},
{
"Y": 1.0,
"X": 0.0
}
]
},
"Relationships": [
{
"Type": "CHILD",
"Ids": [
"75966e64-81c2-4540-9649-d66ec341cd8f",
"bb099c24-8282-464c-a179-8a9fa0a057f0",
"5ebf522d-f9e4-4dc7-bfae-a288dc094595"
]
}
],
"BlockType": "PAGE",
"Id": "247c28ee-b63d-4aeb-9af0-5f7ea8ba109e",
"Page": 1
}
],
"NextToken": "cY1W3eTFvoB0cH7YrKVudI4Gb0H8J0xAYLo8xI/JunCIPWCthaKQ+07n/ElyutsSy0+1VOImoTRmP1zw4P0RFtaeV9Bzhnfedpx1YqwB4xaGDA==",
"DocumentMetadata": {
"Pages": 1
},
"JobStatus": "SUCCEEDED"
}
```
Untuk informasi selengkapnya, lihat Mendeteksi dan Menganalisis Teks dalam Dokumen Multi-Halaman di Panduan Pengembang *Amazon Texttract*
+ Untuk detail API, lihat [GetDocumentAnalysis](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/get-document-analysis.html)di *Referensi AWS CLI Perintah*.
------
#### [ Python ]
**SDK untuk Python (Boto3)**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples).
```
class TextractWrapper:
"""Encapsulates Textract functions."""
def __init__(self, textract_client, s3_resource, sqs_resource):
"""
:param textract_client: A Boto3 Textract client.
:param s3_resource: A Boto3 Amazon S3 resource.
:param sqs_resource: A Boto3 Amazon SQS resource.
"""
self.textract_client = textract_client
self.s3_resource = s3_resource
self.sqs_resource = sqs_resource
def get_analysis_job(self, job_id):
"""
Gets data for a previously started detection job that includes additional
elements.
:param job_id: The ID of the job to retrieve.
:return: The job data, including a list of blocks that describe elements
detected in the image.
"""
try:
response = self.textract_client.get_document_analysis(JobId=job_id)
job_status = response["JobStatus"]
logger.info("Job %s status is %s.", job_id, job_status)
except ClientError:
logger.exception("Couldn't get data for job %s.", job_id)
raise
else:
return response
```
+ Untuk detail API, lihat [GetDocumentAnalysis](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/GetDocumentAnalysis)di *AWS SDK for Python (Boto3) Referensi* API.
------
#### [ SAP ABAP ]
**SDK for SAP ABAP**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples).
```
"Gets the results for an Amazon Textract"
"asynchronous operation that analyzes text in a document."
TRY.
oo_result = lo_tex->getdocumentanalysis( iv_jobid = iv_jobid ). "oo_result is returned for testing purposes."
WHILE oo_result->get_jobstatus( ) <> 'SUCCEEDED'.
IF sy-index = 10.
EXIT. "Maximum 300 seconds.
ENDIF.
WAIT UP TO 30 SECONDS.
oo_result = lo_tex->getdocumentanalysis( iv_jobid = iv_jobid ).
ENDWHILE.
DATA(lt_blocks) = oo_result->get_blocks( ).
LOOP AT lt_blocks INTO DATA(lo_block).
IF lo_block->get_text( ) = 'INGREDIENTS: POWDERED SUGAR* (CANE SUGAR,'.
MESSAGE 'Found text in the doc: ' && lo_block->get_text( ) TYPE 'I'.
ENDIF.
ENDLOOP.
MESSAGE 'Document analysis retrieved.' TYPE 'I'.
CATCH /aws1/cx_texaccessdeniedex.
MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
CATCH /aws1/cx_texinternalservererr.
MESSAGE 'Internal server error.' TYPE 'E'.
CATCH /aws1/cx_texinvalidjobidex.
MESSAGE 'Job ID is not valid.' TYPE 'E'.
CATCH /aws1/cx_texinvalidkmskeyex.
MESSAGE 'AWS KMS key is not valid.' TYPE 'E'.
CATCH /aws1/cx_texinvalidparameterex.
MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
CATCH /aws1/cx_texinvalids3objectex.
MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
CATCH /aws1/cx_texprovthruputexcdex.
MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
CATCH /aws1/cx_texthrottlingex.
MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
ENDTRY.
```
+ Untuk detail API, lihat [GetDocumentAnalysis](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)di *AWS SDK untuk referensi SAP ABAP* API.
------
# Gunakan `StartDocumentAnalysis` dengan AWS SDK atau CLI
Contoh kode berikut menunjukkan cara menggunakan`StartDocumentAnalysis`.
Contoh tindakan adalah kutipan kode dari program yang lebih besar dan harus dijalankan dalam konteks. Anda dapat melihat tindakan ini dalam konteks dalam contoh kode berikut:
+ [Memulai dengan analisis dokumen](textract_example_textract_Scenario_GettingStarted_section.md)
------
#### [ CLI ]
**AWS CLI**
**Untuk mulai menganalisis teks dalam dokumen multi-halaman**
`start-document-analysis`Contoh berikut menunjukkan bagaimana memulai analisis asinkron teks dalam dokumen multi-halaman.
Linux/macOS:
```
aws textract start-document-analysis \
--document-location '{"S3Object":{"Bucket":"bucket","Name":"document"}}' \
--feature-types '["TABLES","FORMS"]' \
--notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleArn"
```
Windows:
```
aws textract start-document-analysis \
--document-location "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
--feature-types "[\"TABLES\", \"FORMS\"]" \
--region region-name \
--notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleArn"
```
Output:
```
{
"JobId": "df7cf32ebbd2a5de113535fcf4d921926a701b09b4e7d089f3aebadb41e0712b"
}
```
Untuk informasi selengkapnya, lihat Mendeteksi dan Menganalisis Teks dalam Dokumen Multi-Halaman di Panduan Pengembang *Amazon Texttract*
+ Untuk detail API, lihat [StartDocumentAnalysis](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/start-document-analysis.html)di *Referensi AWS CLI Perintah*.
------
#### [ Java ]
**SDK untuk Java 2.x**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/textract#code-examples).
```
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.textract.model.S3Object;
import software.amazon.awssdk.services.textract.TextractClient;
import software.amazon.awssdk.services.textract.model.StartDocumentAnalysisRequest;
import software.amazon.awssdk.services.textract.model.DocumentLocation;
import software.amazon.awssdk.services.textract.model.TextractException;
import software.amazon.awssdk.services.textract.model.StartDocumentAnalysisResponse;
import software.amazon.awssdk.services.textract.model.GetDocumentAnalysisRequest;
import software.amazon.awssdk.services.textract.model.GetDocumentAnalysisResponse;
import software.amazon.awssdk.services.textract.model.FeatureType;
import java.util.ArrayList;
import java.util.List;
/**
* Before running this Java V2 code example, set up your development
* environment, including your credentials.
*
* For more information, see the following documentation topic:
*
* https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
*/
public class StartDocumentAnalysis {
public static void main(String[] args) {
final String usage = """
Usage:
\s
Where:
bucketName - The name of the Amazon S3 bucket that contains the document.\s
docName - The document name (must be an image, for example, book.png).\s
""";
if (args.length != 2) {
System.out.println(usage);
System.exit(1);
}
String bucketName = args[0];
String docName = args[1];
Region region = Region.US_WEST_2;
TextractClient textractClient = TextractClient.builder()
.region(region)
.build();
String jobId = startDocAnalysisS3(textractClient, bucketName, docName);
System.out.println("Getting results for job " + jobId);
String status = getJobResults(textractClient, jobId);
System.out.println("The job status is " + status);
textractClient.close();
}
public static String startDocAnalysisS3(TextractClient textractClient, String bucketName, String docName) {
try {
List myList = new ArrayList<>();
myList.add(FeatureType.TABLES);
myList.add(FeatureType.FORMS);
S3Object s3Object = S3Object.builder()
.bucket(bucketName)
.name(docName)
.build();
DocumentLocation location = DocumentLocation.builder()
.s3Object(s3Object)
.build();
StartDocumentAnalysisRequest documentAnalysisRequest = StartDocumentAnalysisRequest.builder()
.documentLocation(location)
.featureTypes(myList)
.build();
StartDocumentAnalysisResponse response = textractClient.startDocumentAnalysis(documentAnalysisRequest);
// Get the job ID
String jobId = response.jobId();
return jobId;
} catch (TextractException e) {
System.err.println(e.getMessage());
System.exit(1);
}
return "";
}
private static String getJobResults(TextractClient textractClient, String jobId) {
boolean finished = false;
int index = 0;
String status = "";
try {
while (!finished) {
GetDocumentAnalysisRequest analysisRequest = GetDocumentAnalysisRequest.builder()
.jobId(jobId)
.maxResults(1000)
.build();
GetDocumentAnalysisResponse response = textractClient.getDocumentAnalysis(analysisRequest);
status = response.jobStatus().toString();
if (status.compareTo("SUCCEEDED") == 0)
finished = true;
else {
System.out.println(index + " status is: " + status);
Thread.sleep(1000);
}
index++;
}
return status;
} catch (InterruptedException e) {
System.out.println(e.getMessage());
System.exit(1);
}
return "";
}
}
```
+ Untuk detail API, lihat [StartDocumentAnalysis](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/StartDocumentAnalysis)di *Referensi AWS SDK for Java 2.x API*.
------
#### [ Python ]
**SDK untuk Python (Boto3)**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples).
Mulai pekerjaan asinkron untuk menganalisis dokumen.
```
class TextractWrapper:
"""Encapsulates Textract functions."""
def __init__(self, textract_client, s3_resource, sqs_resource):
"""
:param textract_client: A Boto3 Textract client.
:param s3_resource: A Boto3 Amazon S3 resource.
:param sqs_resource: A Boto3 Amazon SQS resource.
"""
self.textract_client = textract_client
self.s3_resource = s3_resource
self.sqs_resource = sqs_resource
def start_analysis_job(
self,
bucket_name,
document_file_name,
feature_types,
sns_topic_arn,
sns_role_arn,
):
"""
Starts an asynchronous job to detect text and additional elements, such as
forms or tables, in an image stored in an Amazon S3 bucket. Textract publishes
a notification to the specified Amazon SNS topic when the job completes.
The image must be in PNG, JPG, or PDF format.
:param bucket_name: The name of the Amazon S3 bucket that contains the image.
:param document_file_name: The name of the document image stored in Amazon S3.
:param feature_types: The types of additional document features to detect.
:param sns_topic_arn: The Amazon Resource Name (ARN) of an Amazon SNS topic
where job completion notification is published.
:param sns_role_arn: The ARN of an AWS Identity and Access Management (IAM)
role that can be assumed by Textract and grants permission
to publish to the Amazon SNS topic.
:return: The ID of the job.
"""
try:
response = self.textract_client.start_document_analysis(
DocumentLocation={
"S3Object": {"Bucket": bucket_name, "Name": document_file_name}
},
NotificationChannel={
"SNSTopicArn": sns_topic_arn,
"RoleArn": sns_role_arn,
},
FeatureTypes=feature_types,
)
job_id = response["JobId"]
logger.info(
"Started text analysis job %s on %s.", job_id, document_file_name
)
except ClientError:
logger.exception("Couldn't analyze text in %s.", document_file_name)
raise
else:
return job_id
```
+ Untuk detail API, lihat [StartDocumentAnalysis](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/StartDocumentAnalysis)di *AWS SDK for Python (Boto3) Referensi* API.
------
#### [ SAP ABAP ]
**SDK for SAP ABAP**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples).
```
"Starts the asynchronous analysis of an input document for relationships"
"between detected items such as key-value pairs, tables, and selection elements."
"Create ABAP objects for feature type."
"Add TABLES to return information about the tables."
"Add FORMS to return detected form data."
"To perform both types of analysis, add TABLES and FORMS to FeatureTypes."
DATA(lt_featuretypes) = VALUE /aws1/cl_texfeaturetypes_w=>tt_featuretypes(
( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'FORMS' ) )
( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'TABLES' ) ) ).
"Create an ABAP object for the Amazon S3 object."
DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
iv_name = iv_s3object ).
"Create an ABAP object for the document."
DATA(lo_documentlocation) = NEW /aws1/cl_texdocumentlocation( io_s3object = lo_s3object ).
"Start async document analysis."
TRY.
oo_result = lo_tex->startdocumentanalysis( "oo_result is returned for testing purposes."
io_documentlocation = lo_documentlocation
it_featuretypes = lt_featuretypes ).
DATA(lv_jobid) = oo_result->get_jobid( ).
MESSAGE 'Document analysis started.' TYPE 'I'.
CATCH /aws1/cx_texaccessdeniedex.
MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
CATCH /aws1/cx_texbaddocumentex.
MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
CATCH /aws1/cx_texdocumenttoolargeex.
MESSAGE 'The document is too large.' TYPE 'E'.
CATCH /aws1/cx_texidempotentprmmis00.
MESSAGE 'Idempotent parameter mismatch exception.' TYPE 'E'.
CATCH /aws1/cx_texinternalservererr.
MESSAGE 'Internal server error.' TYPE 'E'.
CATCH /aws1/cx_texinvalidkmskeyex.
MESSAGE 'AWS KMS key is not valid.' TYPE 'E'.
CATCH /aws1/cx_texinvalidparameterex.
MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
CATCH /aws1/cx_texinvalids3objectex.
MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
CATCH /aws1/cx_texlimitexceededex.
MESSAGE 'An Amazon Textract service limit was exceeded.' TYPE 'E'.
CATCH /aws1/cx_texprovthruputexcdex.
MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
CATCH /aws1/cx_texthrottlingex.
MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
CATCH /aws1/cx_texunsupporteddocex.
MESSAGE 'The document is not supported.' TYPE 'E'.
ENDTRY.
```
+ Untuk detail API, lihat [StartDocumentAnalysis](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)di *AWS SDK untuk referensi SAP ABAP* API.
------
# Gunakan `StartDocumentTextDetection` dengan AWS SDK atau CLI
Contoh kode berikut menunjukkan cara menggunakan`StartDocumentTextDetection`.
------
#### [ CLI ]
**AWS CLI**
**Untuk mulai mendeteksi teks dalam dokumen multi-halaman**
`start-document-text-detection`Contoh berikut menunjukkan bagaimana memulai deteksi asinkron teks dalam dokumen multi-halaman.
Linux/macOS:
```
aws textract start-document-text-detection \
--document-location '{"S3Object":{"Bucket":"bucket","Name":"document"}}' \
--notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleARN"
```
Windows:
```
aws textract start-document-text-detection \
--document-location "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
--region region-name \
--notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleArn"
```
Output:
```
{
"JobId": "57849a3dc627d4df74123dca269d69f7b89329c870c65bb16c9fd63409d200b9"
}
```
Untuk informasi selengkapnya, lihat Mendeteksi dan Menganalisis Teks dalam Dokumen Multi-Halaman di Panduan Pengembang *Amazon Texttract*
+ Untuk detail API, lihat [StartDocumentTextDetection](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/start-document-text-detection.html)di *Referensi AWS CLI Perintah*.
------
#### [ Python ]
**SDK untuk Python (Boto3)**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples).
Mulai pekerjaan asinkron untuk mendeteksi teks dalam dokumen.
```
class TextractWrapper:
"""Encapsulates Textract functions."""
def __init__(self, textract_client, s3_resource, sqs_resource):
"""
:param textract_client: A Boto3 Textract client.
:param s3_resource: A Boto3 Amazon S3 resource.
:param sqs_resource: A Boto3 Amazon SQS resource.
"""
self.textract_client = textract_client
self.s3_resource = s3_resource
self.sqs_resource = sqs_resource
def start_detection_job(
self, bucket_name, document_file_name, sns_topic_arn, sns_role_arn
):
"""
Starts an asynchronous job to detect text elements in an image stored in an
Amazon S3 bucket. Textract publishes a notification to the specified Amazon SNS
topic when the job completes.
The image must be in PNG, JPG, or PDF format.
:param bucket_name: The name of the Amazon S3 bucket that contains the image.
:param document_file_name: The name of the document image stored in Amazon S3.
:param sns_topic_arn: The Amazon Resource Name (ARN) of an Amazon SNS topic
where the job completion notification is published.
:param sns_role_arn: The ARN of an AWS Identity and Access Management (IAM)
role that can be assumed by Textract and grants permission
to publish to the Amazon SNS topic.
:return: The ID of the job.
"""
try:
response = self.textract_client.start_document_text_detection(
DocumentLocation={
"S3Object": {"Bucket": bucket_name, "Name": document_file_name}
},
NotificationChannel={
"SNSTopicArn": sns_topic_arn,
"RoleArn": sns_role_arn,
},
)
job_id = response["JobId"]
logger.info(
"Started text detection job %s on %s.", job_id, document_file_name
)
except ClientError:
logger.exception("Couldn't detect text in %s.", document_file_name)
raise
else:
return job_id
```
+ Untuk detail API, lihat [StartDocumentTextDetection](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/StartDocumentTextDetection)di *AWS SDK for Python (Boto3) Referensi* API.
------
#### [ SAP ABAP ]
**SDK for SAP ABAP**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples).
```
"Starts the asynchronous detection of text in a document."
"Amazon Textract can detect lines of text and the words that make up a line of text."
"Create an ABAP object for the Amazon S3 object."
DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
iv_name = iv_s3object ).
"Create an ABAP object for the document."
DATA(lo_documentlocation) = NEW /aws1/cl_texdocumentlocation( io_s3object = lo_s3object ).
"Start document analysis."
TRY.
oo_result = lo_tex->startdocumenttextdetection( io_documentlocation = lo_documentlocation ).
DATA(lv_jobid) = oo_result->get_jobid( ). "oo_result is returned for testing purposes."
MESSAGE 'Document analysis started.' TYPE 'I'.
CATCH /aws1/cx_texaccessdeniedex.
MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
CATCH /aws1/cx_texbaddocumentex.
MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
CATCH /aws1/cx_texdocumenttoolargeex.
MESSAGE 'The document is too large.' TYPE 'E'.
CATCH /aws1/cx_texidempotentprmmis00.
MESSAGE 'Idempotent parameter mismatch exception.' TYPE 'E'.
CATCH /aws1/cx_texinternalservererr.
MESSAGE 'Internal server error.' TYPE 'E'.
CATCH /aws1/cx_texinvalidkmskeyex.
MESSAGE 'AWS KMS key is not valid.' TYPE 'E'.
CATCH /aws1/cx_texinvalidparameterex.
MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
CATCH /aws1/cx_texinvalids3objectex.
MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
CATCH /aws1/cx_texlimitexceededex.
MESSAGE 'An Amazon Textract service limit was exceeded.' TYPE 'E'.
CATCH /aws1/cx_texprovthruputexcdex.
MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
CATCH /aws1/cx_texthrottlingex.
MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
CATCH /aws1/cx_texunsupporteddocex.
MESSAGE 'The document is not supported.' TYPE 'E'.
ENDTRY.
```
+ Untuk detail API, lihat [StartDocumentTextDetection](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)di *AWS SDK untuk referensi SAP ABAP* API.
------
# Skenario untuk Amazon Texttract menggunakan AWS SDKs
Contoh kode berikut menunjukkan cara menerapkan skenario umum di Amazon Textract dengan. AWS SDKs Skenario ini menunjukkan kepada Anda cara menyelesaikan tugas tertentu dengan memanggil beberapa fungsi dalam Amazon Ttract atau digabungkan dengan yang lain. Layanan AWS Setiap skenario menyertakan tautan ke kode sumber lengkap, di mana Anda dapat menemukan instruksi tentang cara mengatur dan menjalankan kode.
Skenario menargetkan tingkat pengalaman menengah untuk membantu Anda memahami tindakan layanan dalam konteks.
**Topics**
+ [Membuat aplikasi penjelajah Amazon Textract](textract_example_cross_TextractExplorer_section.md)
+ [Buat aplikasi untuk menganalisis umpan balik pelanggan](textract_example_cross_FSA_section.md)
+ [Mendeteksi entitas dalam teks yang diekstrak dari gambar](textract_example_cross_TextractComprehendDetectEntities_section.md)
+ [Memulai dengan analisis dokumen](textract_example_textract_Scenario_GettingStarted_section.md)
# Membuat aplikasi penjelajah Amazon Textract
Contoh kode berikut ini menunjukkan cara menjelajahi output Amazon Textract melalui aplikasi interaktif.
------
#### [ JavaScript ]
**SDK untuk JavaScript (v3)**
Menunjukkan cara menggunakan aplikasi AWS SDK untuk JavaScript untuk membangun aplikasi React yang menggunakan Amazon Textract untuk mengekstrak data dari gambar dokumen dan menampilkannya di halaman web interaktif. Contoh ini berjalan di peramban web dan memerlukan identitas Amazon Cognito yang diautentikasi sebagai kredensialnya. Contoh ini menggunakan Amazon Simple Storage Service (Amazon S3) untuk penyimpanan, dan untuk notifikasi, contoh ini mengambil polling antrean Amazon Simple Queue Service (Amazon SQS) yang berlangganan topik Amazon Simple Notification Service (Amazon SNS).
Untuk kode sumber lengkap dan instruksi tentang cara mengatur dan menjalankan, lihat contoh lengkapnya di [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javascriptv3/example_code/cross-services/textract-react).
**Layanan yang digunakan dalam contoh ini**
+ Identitas Amazon Cognito
+ Amazon S3
+ Amazon SNS
+ Amazon SQS
+ Amazon Textract
------
#### [ Python ]
**SDK untuk Python (Boto3)**
Menunjukkan cara menggunakan Amazon Textract untuk mendeteksi elemen teks, formulir, dan tabel dalam gambar dokumen. AWS SDK untuk Python (Boto3) Gambar input dan output Amazon Textract ditampilkan dalam aplikasi Tkinter yang memungkinkan Anda menjelajahi elemen yang terdeteksi.
+ Kirim gambar dokumen ke Amazon Textract dan jelajahi output elemen yang terdeteksi.
+ Kirim gambar langsung ke Amazon Textract atau melalui bucket Amazon Simple Storage Service (Amazon S3).
+ Gunakan asinkron APIs untuk memulai pekerjaan yang menerbitkan pemberitahuan ke topik Simple Notification Service Amazon (Amazon SNS) saat pekerjaan selesai.
+ Lakukan polling pada antrean Amazon Simple Queue Service (Amazon SQS) untuk mendapatkan pesan penyelesaian tugas dan tampilkan hasilnya.
Untuk kode sumber lengkap dan instruksi tentang cara mengatur dan menjalankan, lihat contoh lengkapnya di [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/textract_explorer).
**Layanan yang digunakan dalam contoh ini**
+ Identitas Amazon Cognito
+ Amazon S3
+ Amazon SNS
+ Amazon SQS
+ Amazon Textract
------
# Buat aplikasi yang menganalisis umpan balik pelanggan dan mensintesis audio
Contoh kode berikut menunjukkan cara membuat aplikasi yang menganalisis kartu komentar pelanggan, menerjemahkannya dari bahasa aslinya, menentukan sentimen mereka, dan menghasilkan file audio dari teks yang diterjemahkan.
------
#### [ .NET ]
**SDK untuk .NET**
Aplikasi contoh ini menganalisis dan menyimpan kartu umpan balik pelanggan. Secara khusus, ini memenuhi kebutuhan sebuah hotel fiktif di New York City. Hotel menerima umpan balik dari para tamu dalam berbagai bahasa dalam bentuk kartu komentar fisik. Umpan balik itu diunggah ke aplikasi melalui klien web. Setelah gambar kartu komentar diunggah, langkah-langkah berikut terjadi:
+ Teks diekstraksi dari gambar menggunakan Amazon Textract.
+ Amazon Comprehend menentukan sentimen teks yang diekstraksi dan bahasanya.
+ Teks yang diekstraksi diterjemahkan ke bahasa Inggris menggunakan Amazon Translate.
+ Amazon Polly mensintesis file audio dari teks yang diekstraksi.
Aplikasi lengkap dapat digunakan dengan. AWS CDK Untuk kode sumber dan petunjuk penerapan, lihat proyek di [ GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/dotnetv3/cross-service/FeedbackSentimentAnalyzer).
**Layanan yang digunakan dalam contoh ini**
+ Amazon Comprehend
+ Lambda
+ Amazon Polly
+ Amazon Textract
+ Amazon Translate
------
#### [ Java ]
**SDK untuk Java 2.x**
Aplikasi contoh ini menganalisis dan menyimpan kartu umpan balik pelanggan. Secara khusus, ini memenuhi kebutuhan sebuah hotel fiktif di New York City. Hotel menerima umpan balik dari para tamu dalam berbagai bahasa dalam bentuk kartu komentar fisik. Umpan balik itu diunggah ke aplikasi melalui klien web. Setelah gambar kartu komentar diunggah, langkah-langkah berikut terjadi:
+ Teks diekstraksi dari gambar menggunakan Amazon Textract.
+ Amazon Comprehend menentukan sentimen teks yang diekstraksi dan bahasanya.
+ Teks yang diekstraksi diterjemahkan ke bahasa Inggris menggunakan Amazon Translate.
+ Amazon Polly mensintesis file audio dari teks yang diekstraksi.
Aplikasi lengkap dapat digunakan dengan. AWS CDK Untuk kode sumber dan petunjuk penerapan, lihat proyek di [ GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/usecases/creating_fsa_app).
**Layanan yang digunakan dalam contoh ini**
+ Amazon Comprehend
+ Lambda
+ Amazon Polly
+ Amazon Textract
+ Amazon Translate
------
#### [ JavaScript ]
**SDK untuk JavaScript (v3)**
Aplikasi contoh ini menganalisis dan menyimpan kartu umpan balik pelanggan. Secara khusus, ini memenuhi kebutuhan sebuah hotel fiktif di New York City. Hotel menerima umpan balik dari para tamu dalam berbagai bahasa dalam bentuk kartu komentar fisik. Umpan balik itu diunggah ke aplikasi melalui klien web. Setelah gambar kartu komentar diunggah, langkah-langkah berikut terjadi:
+ Teks diekstraksi dari gambar menggunakan Amazon Textract.
+ Amazon Comprehend menentukan sentimen teks yang diekstraksi dan bahasanya.
+ Teks yang diekstraksi diterjemahkan ke bahasa Inggris menggunakan Amazon Translate.
+ Amazon Polly mensintesis file audio dari teks yang diekstraksi.
Aplikasi lengkap dapat digunakan dengan. AWS CDK Untuk kode sumber dan petunjuk penerapan, lihat proyek di [ GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javascriptv3/example_code/cross-services/feedback-sentiment-analyzer). Kutipan berikut menunjukkan bagaimana digunakan di dalam AWS SDK untuk JavaScript fungsi Lambda.
```
import {
ComprehendClient,
DetectDominantLanguageCommand,
DetectSentimentCommand,
} from "@aws-sdk/client-comprehend";
/**
* Determine the language and sentiment of the extracted text.
*
* @param {{ source_text: string}} extractTextOutput
*/
export const handler = async (extractTextOutput) => {
const comprehendClient = new ComprehendClient({});
const detectDominantLanguageCommand = new DetectDominantLanguageCommand({
Text: extractTextOutput.source_text,
});
// The source language is required for sentiment analysis and
// translation in the next step.
const { Languages } = await comprehendClient.send(
detectDominantLanguageCommand,
);
const languageCode = Languages[0].LanguageCode;
const detectSentimentCommand = new DetectSentimentCommand({
Text: extractTextOutput.source_text,
LanguageCode: languageCode,
});
const { Sentiment } = await comprehendClient.send(detectSentimentCommand);
return {
sentiment: Sentiment,
language_code: languageCode,
};
};
```
```
import {
DetectDocumentTextCommand,
TextractClient,
} from "@aws-sdk/client-textract";
/**
* Fetch the S3 object from the event and analyze it using Amazon Textract.
*
* @param {import("@types/aws-lambda").EventBridgeEvent<"Object Created">} eventBridgeS3Event
*/
export const handler = async (eventBridgeS3Event) => {
const textractClient = new TextractClient();
const detectDocumentTextCommand = new DetectDocumentTextCommand({
Document: {
S3Object: {
Bucket: eventBridgeS3Event.bucket,
Name: eventBridgeS3Event.object,
},
},
});
// Textract returns a list of blocks. A block can be a line, a page, word, etc.
// Each block also contains geometry of the detected text.
// For more information on the Block type, see https://docs.aws.amazon.com/textract/latest/dg/API_Block.html.
const { Blocks } = await textractClient.send(detectDocumentTextCommand);
// For the purpose of this example, we are only interested in words.
const extractedWords = Blocks.filter((b) => b.BlockType === "WORD").map(
(b) => b.Text,
);
return extractedWords.join(" ");
};
```
```
import { PollyClient, SynthesizeSpeechCommand } from "@aws-sdk/client-polly";
import { S3Client } from "@aws-sdk/client-s3";
import { Upload } from "@aws-sdk/lib-storage";
/**
* Synthesize an audio file from text.
*
* @param {{ bucket: string, translated_text: string, object: string}} sourceDestinationConfig
*/
export const handler = async (sourceDestinationConfig) => {
const pollyClient = new PollyClient({});
const synthesizeSpeechCommand = new SynthesizeSpeechCommand({
Engine: "neural",
Text: sourceDestinationConfig.translated_text,
VoiceId: "Ruth",
OutputFormat: "mp3",
});
const { AudioStream } = await pollyClient.send(synthesizeSpeechCommand);
const audioKey = `${sourceDestinationConfig.object}.mp3`;
// Store the audio file in S3.
const s3Client = new S3Client();
const upload = new Upload({
client: s3Client,
params: {
Bucket: sourceDestinationConfig.bucket,
Key: audioKey,
Body: AudioStream,
ContentType: "audio/mp3",
},
});
await upload.done();
return audioKey;
};
```
```
import {
TranslateClient,
TranslateTextCommand,
} from "@aws-sdk/client-translate";
/**
* Translate the extracted text to English.
*
* @param {{ extracted_text: string, source_language_code: string}} textAndSourceLanguage
*/
export const handler = async (textAndSourceLanguage) => {
const translateClient = new TranslateClient({});
const translateCommand = new TranslateTextCommand({
SourceLanguageCode: textAndSourceLanguage.source_language_code,
TargetLanguageCode: "en",
Text: textAndSourceLanguage.extracted_text,
});
const { TranslatedText } = await translateClient.send(translateCommand);
return { translated_text: TranslatedText };
};
```
**Layanan yang digunakan dalam contoh ini**
+ Amazon Comprehend
+ Lambda
+ Amazon Polly
+ Amazon Textract
+ Amazon Translate
------
#### [ Ruby ]
**SDK untuk Ruby**
Aplikasi contoh ini menganalisis dan menyimpan kartu umpan balik pelanggan. Secara khusus, ini memenuhi kebutuhan sebuah hotel fiktif di New York City. Hotel menerima umpan balik dari para tamu dalam berbagai bahasa dalam bentuk kartu komentar fisik. Umpan balik itu diunggah ke aplikasi melalui klien web. Setelah gambar kartu komentar diunggah, langkah-langkah berikut terjadi:
+ Teks diekstraksi dari gambar menggunakan Amazon Textract.
+ Amazon Comprehend menentukan sentimen teks yang diekstraksi dan bahasanya.
+ Teks yang diekstraksi diterjemahkan ke bahasa Inggris menggunakan Amazon Translate.
+ Amazon Polly mensintesis file audio dari teks yang diekstraksi.
Aplikasi lengkap dapat digunakan dengan. AWS CDK Untuk kode sumber dan petunjuk penerapan, lihat proyek di [ GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/ruby/cross_service_examples/feedback_sentiment_analyzer).
**Layanan yang digunakan dalam contoh ini**
+ Amazon Comprehend
+ Lambda
+ Amazon Polly
+ Amazon Textract
+ Amazon Translate
------
# Mendeteksi entitas dalam teks yang diekstrak dari gambar menggunakan SDK AWS
Contoh kode berikut menunjukkan cara menggunakan Amazon Comprehend untuk mendeteksi entitas dalam teks yang diekstrak oleh Amazon Textract dari gambar yang disimpan di Amazon S3.
------
#### [ Python ]
**SDK untuk Python (Boto3)**
Menunjukkan cara menggunakan AWS SDK untuk Python (Boto3) dalam buku catatan Jupyter untuk mendeteksi entitas dalam teks yang diekstraksi dari gambar. Contoh ini menggunakan Amazon Textract untuk mengekstrak teks dari gambar yang disimpan di Amazon Simple Storage Service (Amazon S3) dan Amazon Comprehend untuk mendeteksi entitas dalam teks yang diekstraksi.
Contoh ini adalah notebook Jupyter dan harus dijalankan di lingkungan yang dapat meng-host notebook. Untuk petunjuk tentang cara menjalankan contoh menggunakan Amazon SageMaker AI, lihat petunjuk di [TextractAndComprehendNotebook.ipynb](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/textract_comprehend_notebook/TextractAndComprehendNotebook.ipynb).
Untuk kode sumber lengkap dan instruksi tentang cara mengatur dan menjalankan, lihat contoh lengkapnya di [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/textract_comprehend_notebook#readme).
**Layanan yang digunakan dalam contoh ini**
+ Amazon Comprehend
+ Amazon S3
+ Amazon Textract
------
# Memulai analisis dokumen Amazon Texttract menggunakan SDK AWS
Contoh kode berikut ini menunjukkan cara untuk melakukan:
+ Mulai analisis asinkron.
+ Dapatkan analisis dokumen.
------
#### [ SAP ABAP ]
**SDK for SAP ABAP**
Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di [Repositori Contoh Kode AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples).
```
"Create ABAP objects for feature type."
"Add TABLES to return information about the tables."
"Add FORMS to return detected form data."
"To perform both types of analysis, add TABLES and FORMS to FeatureTypes."
DATA(lt_featuretypes) = VALUE /aws1/cl_texfeaturetypes_w=>tt_featuretypes(
( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'FORMS' ) )
( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'TABLES' ) ) ).
"Create an ABAP object for the Amazon Simple Storage Service (Amazon S3) object."
DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
iv_name = iv_s3object ).
"Create an ABAP object for the document."
DATA(lo_documentlocation) = NEW /aws1/cl_texdocumentlocation( io_s3object = lo_s3object ).
"Start document analysis."
TRY.
DATA(lo_start_result) = lo_tex->startdocumentanalysis(
io_documentlocation = lo_documentlocation
it_featuretypes = lt_featuretypes ).
MESSAGE 'Document analysis started.' TYPE 'I'.
CATCH /aws1/cx_texaccessdeniedex.
MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
CATCH /aws1/cx_texbaddocumentex.
MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
CATCH /aws1/cx_texdocumenttoolargeex.
MESSAGE 'The document is too large.' TYPE 'E'.
CATCH /aws1/cx_texidempotentprmmis00.
MESSAGE 'Idempotent parameter mismatch exception.' TYPE 'E'.
CATCH /aws1/cx_texinternalservererr.
MESSAGE 'Internal server error.' TYPE 'E'.
CATCH /aws1/cx_texinvalidkmskeyex.
MESSAGE 'AWS KMS key is not valid.' TYPE 'E'.
CATCH /aws1/cx_texinvalidparameterex.
MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
CATCH /aws1/cx_texinvalids3objectex.
MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
CATCH /aws1/cx_texlimitexceededex.
MESSAGE 'An Amazon Textract service limit was exceeded.' TYPE 'E'.
CATCH /aws1/cx_texprovthruputexcdex.
MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
CATCH /aws1/cx_texthrottlingex.
MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
CATCH /aws1/cx_texunsupporteddocex.
MESSAGE 'The document is not supported.' TYPE 'E'.
ENDTRY.
"Get job ID from the output."
DATA(lv_jobid) = lo_start_result->get_jobid( ).
"Wait for job to complete."
oo_result = lo_tex->getdocumentanalysis( iv_jobid = lv_jobid ). " oo_result is returned for testing purposes. "
WHILE oo_result->get_jobstatus( ) <> 'SUCCEEDED'.
IF sy-index = 10.
EXIT. "Maximum 300 seconds."
ENDIF.
WAIT UP TO 30 SECONDS.
oo_result = lo_tex->getdocumentanalysis( iv_jobid = lv_jobid ).
ENDWHILE.
DATA(lt_blocks) = oo_result->get_blocks( ).
LOOP AT lt_blocks INTO DATA(lo_block).
IF lo_block->get_text( ) = 'INGREDIENTS: POWDERED SUGAR* (CANE SUGAR,'.
MESSAGE 'Found text in the doc: ' && lo_block->get_text( ) TYPE 'I'.
ENDIF.
ENDLOOP.
```
+ Untuk mengetahui hal detail mengenai API, silakan lihat topik-topik berikut di *referensi API AWS SDK untuk ABAP SAP*.
+ [GetDocumentAnalysis](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)
+ [StartDocumentAnalysis](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)
------