遮蓋圖片中的機密資料

您可以使用 Cloud Data Loss Prevention API 偵測圖片中的機密文字和物件，然後取得遮蓋後的圖片。在傳回的圖片中，系統會以不透明的矩形遮蓋偵測到的機密資料元素。您可以使用 infoType 偵測工具，指定要偵測及遮蓋的資訊類型。

根據預設，Sensitive Data Protection 會使用黑色矩形遮蓋已遮蓋的內容，但您可以在圖片遮蓋設定中，為每個 infoType 指定顏色。

遮蓋文字

Sensitive Data Protection 會使用物件字元辨識 (OCR) 技術偵測圖片中的文字。您可以在圖片中遮蓋下列內容：

• 與任何預設 infoType 相符的文字
• 與您在圖片遮蓋設定中列出的任何 infoType 相符的文字
• 所有偵測到的文字

舉例來說，請參考以下圖片。原始圖片是含有聯絡資訊的文件。在本範例中，Sensitive Data Protection 已設定為遮蓋符合 PERSON_NAME、EMAIL_ADDRESS 和 PHONE_NUMBER infoType 的任何文字。產生的圖片會以黑色矩形遮蓋偵測到的機密文字。

物件遮蓋

您可以設定 Sensitive Data Protection，遮蓋通常含有私密/機密資訊的物件。

舉例來說，請參考以下圖片。原始圖片是 AI 生成的圖片，包含條碼、車牌和白板。在本範例中，Sensitive Data Protection 已設定為遮蓋符合 OBJECT_TYPE/BARCODE、OBJECT_TYPE/LICENSE_PLATE 和 OBJECT_TYPE/WHITEBOARD infoType 的物件。系統會以彩色矩形遮蓋偵測到的敏感物件，系統會為每個 infoType 指派一種顏色。

如需可用的物件 infoType 偵測工具完整清單，請參閱「圖像中的物件」。

限制和注意事項

從圖片中遮蓋內容時，請注意下列事項。

支援的檔案類型

Sensitive Data Protection 可以遮蓋多種圖片類型中的機密資料，包括 JPEG、BMP 和 PNG。詳情請參閱「支援的檔案類型」。

內容遮蓋功能不支援 SVG、PDF、XLSX、PPTX 或 DOCX 檔案。

檢查設定限制

從圖片中遮蓋資料時，您無法在檢查設定中加入 limits。如果設定限制，系統可能只會遮蓋部分資料，導致結果與預期不符或不一致。如果您在要求中設定 limits 欄位，Sensitive Data Protection 會產生錯誤。

事前準備

開始執行本頁面的工作前，請先設定驗證機制並取得必要的 IAM 權限。您可以使用 Google Cloud使用者帳戶或服務帳戶。無論是哪種情況，請確保您使用的帳戶具備serviceusage.services.use權限的角色，例如 DLP 管理員 (roles/dlp.admin)、DLP 使用者 (roles/dlp.user) 或自訂角色。

1. Select the tab for how you plan to use the samples on this page:

   C#

   如要在本機開發環境中使用本頁的 .NET 範例，請安裝並初始化 gcloud CLI，然後使用使用者憑證設定應用程式預設憑證。

   1. Install the Google Cloud CLI.

   2. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   3. To initialize the gcloud CLI, run the following command:

      gcloud init

   4. If you're using a local shell, then create local authentication credentials for your user account:

      gcloud auth application-default login

      You don't need to do this if you're using Cloud Shell.

      If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

   詳情請參閱 Google Cloud 驗證說明文件中的「 為本機開發環境設定 ADC」。

   Go

   如要在本機開發環境中使用本頁的 Go 範例，請安裝並初始化 gcloud CLI，然後使用使用者憑證設定應用程式預設憑證。

   1. Install the Google Cloud CLI.

   2. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   3. To initialize the gcloud CLI, run the following command:

      gcloud init

   4. If you're using a local shell, then create local authentication credentials for your user account:

      gcloud auth application-default login

      You don't need to do this if you're using Cloud Shell.

      If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

   詳情請參閱 Google Cloud 驗證說明文件中的「 為本機開發環境設定 ADC」。

   Java

   如要在本機開發環境中使用本頁的 Java 範例，請安裝並初始化 gcloud CLI，然後使用使用者憑證設定應用程式預設憑證。

   1. Install the Google Cloud CLI.

   2. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   3. To initialize the gcloud CLI, run the following command:

      gcloud init

   4. If you're using a local shell, then create local authentication credentials for your user account:

      gcloud auth application-default login

      You don't need to do this if you're using Cloud Shell.

      If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

   詳情請參閱 Google Cloud 驗證說明文件中的「 為本機開發環境設定 ADC」。

   Node.js

   如要在本機開發環境中使用本頁的 Node.js 範例，請安裝並初始化 gcloud CLI，然後使用使用者憑證設定應用程式預設憑證。

   1. Install the Google Cloud CLI.

   2. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   3. To initialize the gcloud CLI, run the following command:

      gcloud init

   4. If you're using a local shell, then create local authentication credentials for your user account:

      gcloud auth application-default login

      You don't need to do this if you're using Cloud Shell.

      If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

   詳情請參閱 Google Cloud 驗證說明文件中的「 為本機開發環境設定 ADC」。

   PHP

   如要在本機開發環境中使用本頁的 PHP 範例，請安裝並初始化 gcloud CLI，然後使用使用者憑證設定應用程式預設憑證。

   1. Install the Google Cloud CLI.

   2. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   3. To initialize the gcloud CLI, run the following command:

      gcloud init

   4. If you're using a local shell, then create local authentication credentials for your user account:

      gcloud auth application-default login

      You don't need to do this if you're using Cloud Shell.

      If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

   詳情請參閱 Google Cloud 驗證說明文件中的「 為本機開發環境設定 ADC」。

   Python

   如要在本機開發環境中使用本頁的 Python 範例，請安裝並初始化 gcloud CLI，然後使用使用者憑證設定應用程式預設憑證。

   1. Install the Google Cloud CLI.

   2. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   3. To initialize the gcloud CLI, run the following command:

      gcloud init

   4. If you're using a local shell, then create local authentication credentials for your user account:

      gcloud auth application-default login

      You don't need to do this if you're using Cloud Shell.

      If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

   詳情請參閱 Google Cloud 驗證說明文件中的「 為本機開發環境設定 ADC」。

   REST

   如要在本機開發環境中使用本頁的 REST API 範例，請使用您提供給 gcloud CLI 的憑證。

   After installing the Google Cloud CLI, initialize it by running the following command:

   gcloud init

   If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   詳情請參閱 Google Cloud 驗證說明文件中的「Authenticate for using REST」。

   image.redact 方法也支援 API 金鑰。 如要使用 API 金鑰進行驗證，您不需要設定本機應用程式預設憑證檔案。 詳情請參閱 請參閱 Google Cloud 驗證說明文件，建立 API 金鑰。

   如要瞭解如何為正式版環境設定驗證，請參閱 Google Cloud 驗證說明文件中的 Set up Application Default Credentials for code running on Google Cloud。

2. 如要取得檢查、遮蓋及去識別化內容所需的權限，請要求管理員授予專案的 DLP 使用者 (roles/dlp.user) IAM 角色。如要進一步瞭解如何授予角色，請參閱「管理專案、資料夾和機構的存取權」。

   您或許還可透過自訂角色或其他預先定義的角色取得必要權限。

遮蓋圖片中的所有預設 infoType

如要遮蓋圖片中的機密資料，請將圖片提交至 DLP API 的 image.redact 方法。除非您指定要搜尋的特定資訊類型 (infoTypes)，否則 Sensitive Data Protection 會搜尋最常見的 infoType。

預設 infoType 不會包含圖片中的物件。

如要遮蓋圖片中的預設 infoType，請按照下列步驟操作：

1. 將圖片編碼為 Base64 字串。

   如果打算使用其中一個 Sensitive Data Protection 用戶端程式庫執行這項工作，請略過這個步驟。

2. 向 image.redact 方法提出要求。

   如要遮蓋預設的 infoType，要求只需要 base64 編碼的圖片。

舉例來說，請參考以下文件圖片。



如要從這張圖片中遮蓋預設 infoType，請將下列要求傳送至 DLP API 的 image.redact 方法：

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Protobuf;
using System;
using System.IO;

public class RedactSensitiveDataFromImageUsingDefaultInfoTypes
{
    public static RedactImageResponse RedactImage(
        string projectId,
        string originalImagePath,
        string redactedImagePath)
    {
        // Instantiate the dlp client.
        var dlp = DlpServiceClient.Create();

        // Construct the content item.
        var byteContentItem = new ByteContentItem
        {
            Type = ByteContentItem.Types.BytesType.ImagePng,
            Data = ByteString.FromStream(new FileStream(originalImagePath, FileMode.Open))
        };

        // Construct the Redact request to be sent by the client. Do not specify the type of info to redact.
        var request = new RedactImageRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            ByteItem = byteContentItem
        };

        // Call the API.
        var response = dlp.RedactImage(request);

        // Inspect the response.
        Console.WriteLine($"Redacted image written to: {redactedImagePath}");

        // Writes redacted image into file
        response.RedactedImage.WriteTo(new FileStream(redactedImagePath, FileMode.Create, FileAccess.Write));

        return response;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import (
	"context"
	"fmt"
	"io"
	"os"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// redactImageFileAllInfoTypes redact sensitive data from an image using default infoTypes.
func redactImageFileAllInfoTypes(w io.Writer, projectID, inputPath, outputPath string) error {
	// projectId := "my-project-id"
	// inputPath := "testdata/image.jpg"
	// outputPath := "testdata/test-output-image-file-all-infoType.jpeg"

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Read the image file.
	fileBytes, err := os.ReadFile(inputPath)
	if err != nil {
		fmt.Fprintf(w, "os.ReadFile: %v", err)
		return err
	}

	// Specify the content to be redacted.
	byteItem := &dlppb.ByteContentItem{
		Type: dlppb.ByteContentItem_IMAGE_JPEG,
		Data: fileBytes,
	}

	// Construct the Redact request to be sent by the client.
	// Do not specify the type of info to redact.
	req := &dlppb.RedactImageRequest{
		Parent:   fmt.Sprintf("projects/%s/locations/global", projectID),
		ByteItem: byteItem,
	}

	// Send the request.
	resp, err := client.RedactImage(ctx, req)
	if err != nil {
		return err
	}

	// Write the output file.
	if err := os.WriteFile(outputPath, resp.GetRedactedImage(), 0644); err != nil {
		return err
	}
	fmt.Fprintf(w, "Wrote output to %s", outputPath)
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.RedactImageRequest;
import com.google.privacy.dlp.v2.RedactImageResponse;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;

class RedactImageFileAllInfoTypes {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "my-project-id";
    String inputPath = "src/test/resources/sensitive-data-image.jpeg";
    String outputPath = "sensitive-data-image-redacted.jpeg";
    redactImageFileAllInfoTypes(projectId, inputPath, outputPath);
  }

  static void redactImageFileAllInfoTypes(String projectId, String inputPath, String outputPath)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify the content to be redacted.
      ByteString fileBytes = ByteString.readFrom(new FileInputStream(inputPath));
      ByteContentItem byteItem =
          ByteContentItem.newBuilder().setType(BytesType.IMAGE_JPEG).setData(fileBytes).build();

      // Construct the Redact request to be sent by the client.
      // Do not specify the type of info to redact.
      RedactImageRequest request =
          RedactImageRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setByteItem(byteItem)
              .build();

      // Use the client to send the API request.
      RedactImageResponse response = dlp.redactImage(request);

      // Parse the response and process results.
      FileOutputStream redacted = new FileOutputStream(outputPath);
      redacted.write(response.getRedactedImage().toByteArray());
      redacted.close();
      System.out.println("Redacted image written to " + outputPath);
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Imports required Node.js libraries
const mime = require('mime');
const fs = require('fs');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// The path to a local file to inspect. Can be a JPG or PNG image file.
// const filepath = 'path/to/image.png';

// The local path to save the resulting image to.
// const outputPath = 'result.png';

async function redactImage() {
  // Specify the content to be redacted.
  const fileTypeConstant =
    ['image/jpeg', 'image/bmp', 'image/png', 'image/svg'].indexOf(
      mime.getType(filepath)
    ) + 1;
  const fileBytes = Buffer.from(fs.readFileSync(filepath)).toString('base64');

  // Construct the Redact request to be sent by the client.
  // Do not specify the type of info to redact.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    byteItem: {
      type: fileTypeConstant,
      data: fileBytes,
    },
  };

  // Use the client to send the API request.
  const [response] = await dlp.redactImage(request);

  // Parse the response and process results.
  const image = response.redactedImage;
  fs.writeFileSync(outputPath, image);
  console.log(`Saved image redaction results to path: ${outputPath}`);
}
redactImage();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

use Google\Cloud\Dlp\V2\ByteContentItem;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\RedactImageRequest;

/**
 * Redact sensitive data from an image using default infoTypes.
 *
 * @param string $callingProjectId    The project ID to run the API call under.
 * @param string $imagePath           The local filepath of the image to inspect.
 * @param string $outputPath          The local filepath to save the resulting image to.
 */
function redact_image_all_infotypes(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $imagePath = './test/data/test.png',
    string $outputPath = './test/data/redact_image_all_infotypes.png'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Read image file into a buffer.
    $imageRef = fopen($imagePath, 'rb');
    $imageBytes = fread($imageRef, filesize($imagePath));
    fclose($imageRef);

    // Get the image's content type.
    $typeConstant = (int) array_search(
        mime_content_type($imagePath),
        [false, 'image/jpeg', 'image/bmp', 'image/png', 'image/svg']
    );

    // Create the byte-storing object.
    $byteContent = (new ByteContentItem())
        ->setType($typeConstant)
        ->setData($imageBytes);

    $parent = "projects/$callingProjectId/locations/global";

    // Run request.
    $redactImageRequest = (new RedactImageRequest())
        ->setParent($parent)
        ->setByteItem($byteContent);
    $response = $dlp->redactImage($redactImageRequest);

    // Save result to file.
    file_put_contents($outputPath, $response->getRedactedImage());

    // Print completion message.
    printf('Redacted image saved to %s ' . PHP_EOL, $outputPath);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import google.cloud.dlp


def redact_image_all_info_types(
    project: str,
    filename: str,
    output_filename: str,
) -> None:
    """Uses the Data Loss Prevention API to redact protected data in an image.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        filename: The path to the file to inspect.
        output_filename: The path to which the redacted image will be written.
            A full list of info type categories can be fetched from the API.
    Returns:
        None; the response from the API is printed to the terminal.
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the byte_item, containing the file's byte data.
    with open(filename, mode="rb") as f:
        byte_item = {"type_": google.cloud.dlp_v2.FileType.IMAGE, "data": f.read()}

    # Convert the project id into a full resource id.
    parent = f"projects/{project}"

    # Call the API.
    response = dlp.redact_image(
        request={
            "parent": parent,
            "byte_item": byte_item,
        }
    )

    # Write out the results.
    with open(output_filename, mode="wb") as f:
        f.write(response.redacted_image)
    print(f"Wrote {len(response.redacted_image)} to {output_filename}")

REST

{
  "byteItem": {
    "data": "[BASE64-ENCODED-IMAGE]",
    "type": "IMAGE_PNG"
  }
}

Sensitive Data Protection 會傳回下列項目：

    {
      "redactedImage": "[BASE64-ENCODED-IMAGE]"
    }

解碼 Base64 編碼的圖片。

產生的圖片如下所示：



請注意，除了遮蓋手寫的身分證字號、電子郵件地址和電話號碼，Sensitive Data Protection 也會遮蓋年份。下一節將示範如何只遮蓋特定 infoType。

遮蓋圖片中的特定 infoType

如要只遮蓋圖片中的特定機密資料，請指定對應的內建 infoType。

如要從圖片中遮蓋特定 infoType，請將要求提交至 DLP API 的 image.redact 方法。要求必須包含下列資訊：

• 圖片。
• 一或多個 infoType 偵測工具。

請參考上一節的原始圖片。如要只遮蓋美國社會安全號碼、電子郵件地址和電話號碼，請將下列 JSON 傳送至 DLP API 的 image.redact 方法：

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Protobuf;
using System;
using System.IO;

public class RedactImageWithListedInfotypes
{
    public static RedactImageResponse Redact(string projectId, string originalImagePath, string redactedImagePath)
    {
        var request = new RedactImageRequest
        {
            Parent = new LocationName(projectId, "global").ToString(),
            InspectConfig = new InspectConfig
            {
                MinLikelihood = Likelihood.Likely,
                Limits = new InspectConfig.Types.FindingLimits() { MaxFindingsPerItem = 5 },
                IncludeQuote = true,
                InfoTypes =
                    {
                        new InfoType { Name = "PHONE_NUMBER" },
                        new InfoType { Name = "EMAIL_ADDRESS" }
                    }
            },
            ByteItem = new ByteContentItem
            {
                Type = ByteContentItem.Types.BytesType.ImagePng,
                Data = ByteString.FromStream(new FileStream(originalImagePath, FileMode.Open))
            },
        };

        var client = DlpServiceClient.Create();
        var response = client.RedactImage(request);

        Console.WriteLine($"Extracted text: {response.ExtractedText}");

        // Writes redacted image into file
        response.RedactedImage.WriteTo(new FileStream(redactedImagePath, FileMode.Create, FileAccess.Write));

        return response;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import (
	"context"
	"fmt"
	"io"
	"os"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// redactImageFileListedInfoTypes redacts only certain sensitive
// data from an image using infoTypes
func redactImageFileListedInfoTypes(w io.Writer, projectID, inputPath, outputPath string) error {
	// projectId := "my-project-id"
	// inputPath := "testdata/image.jpg"
	// outputPath := "testdata/test-output-image-file-listed-infoTypes-redacted.jpeg"

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// read the image file
	fileBytes, err := os.ReadFile(inputPath)
	if err != nil {
		return err
	}

	// Specify the content to be redacted.
	byteItem := &dlppb.ByteContentItem{
		Type: dlppb.ByteContentItem_IMAGE_JPEG,
		Data: fileBytes,
	}

	// Specify the types of info necessary to redact.
	// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
	infoTypes := []*dlppb.InfoType{
		{Name: "US_SOCIAL_SECURITY_NUMBER"},
		{Name: "EMAIL_ADDRESS"},
		{Name: "PHONE_NUMBER"},
	}

	inspectConfig := &dlppb.InspectConfig{
		InfoTypes: infoTypes,
	}

	// Prepare redaction configs.
	var x []*dlppb.RedactImageRequest_ImageRedactionConfig
	for _, v := range infoTypes {
		x = append(x, &dlppb.RedactImageRequest_ImageRedactionConfig{Target: &dlppb.RedactImageRequest_ImageRedactionConfig_InfoType{InfoType: v}})
	}

	// Construct the Inspect request to be sent by the client.
	req := &dlppb.RedactImageRequest{
		Parent:                fmt.Sprintf("projects/%s/locations/global", projectID),
		ByteItem:              byteItem,
		ImageRedactionConfigs: x,
		InspectConfig:         inspectConfig,
	}

	// Send the request.
	resp, err := client.RedactImage(ctx, req)
	if err != nil {
		return err
	}

	// Write the output file.
	if err := os.WriteFile(outputPath, resp.GetRedactedImage(), 0644); err != nil {
		return err
	}
	fmt.Fprintf(w, "Wrote output to %s\n", outputPath)
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.RedactImageRequest;
import com.google.privacy.dlp.v2.RedactImageRequest.ImageRedactionConfig;
import com.google.privacy.dlp.v2.RedactImageResponse;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.Collectors;

class RedactImageFileListedInfoTypes {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "my-project-id";
    String inputPath = "src/test/resources/sensitive-data-image.jpeg";
    String outputPath = "sensitive-data-image-redacted.jpeg";
    redactImageFileListedInfoTypes(projectId, inputPath, outputPath);
  }

  static void redactImageFileListedInfoTypes(String projectId, String inputPath, String outputPath)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify the content to be redacted.
      ByteString fileBytes = ByteString.readFrom(new FileInputStream(inputPath));
      ByteContentItem byteItem =
          ByteContentItem.newBuilder().setType(BytesType.IMAGE_JPEG).setData(fileBytes).build();

      // Specify the types of info necessary to redact.
      List<InfoType> infoTypes = new ArrayList<>();
      // See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
      for (String typeName :
          new String[] {"US_SOCIAL_SECURITY_NUMBER", "EMAIL_ADDRESS", "PHONE_NUMBER"}) {
        infoTypes.add(InfoType.newBuilder().setName(typeName).build());
      }
      InspectConfig inspectConfig = InspectConfig.newBuilder().addAllInfoTypes(infoTypes).build();

      // Prepare redaction configs.
      List<ImageRedactionConfig> imageRedactionConfigs =
          infoTypes.stream()
              .map(infoType -> ImageRedactionConfig.newBuilder().setInfoType(infoType).build())
              .collect(Collectors.toList());

      // Construct the Redact request to be sent by the client.
      RedactImageRequest request =
          RedactImageRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setByteItem(byteItem)
              .addAllImageRedactionConfigs(imageRedactionConfigs)
              .setInspectConfig(inspectConfig)
              .build();

      // Use the client to send the API request.
      RedactImageResponse response = dlp.redactImage(request);

      // Parse the response and process results.
      FileOutputStream redacted = new FileOutputStream(outputPath);
      redacted.write(response.getRedactedImage().toByteArray());
      redacted.close();
      System.out.println("Redacted image written to " + outputPath);
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Imports required Node.js libraries
const mime = require('mime');
const fs = require('fs');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// The path to a local file to inspect. Can be a JPG or PNG image file.
// const filepath = 'path/to/image.png';

// The infoTypes of information to redact
// const infoTypes = [{ name: 'EMAIL_ADDRESS' }, { name: 'PHONE_NUMBER' }];

// The local path to save the resulting image to.
// const outputPath = 'result.png';

async function redactImageWithInfoTypes() {
  // Load image
  const fileTypeConstant =
    ['image/jpeg', 'image/bmp', 'image/png', 'image/svg'].indexOf(
      mime.getType(filepath)
    ) + 1;
  const fileBytes = Buffer.from(fs.readFileSync(filepath)).toString('base64');

  // Construct image redaction request
  const request = {
    parent: `projects/${projectId}/locations/global`,
    byteItem: {
      type: fileTypeConstant,
      data: fileBytes,
    },
    inspectConfig: {
      infoTypes: infoTypes,
    },
    imageRedactionConfigs: infoTypes.map(infoType => ({infoType: infoType})),
  };

  // Run image redaction request
  const [response] = await dlp.redactImage(request);
  const image = response.redactedImage;
  fs.writeFileSync(outputPath, image);
  console.log(`Saved image redaction results to path: ${outputPath}`);
}
redactImageWithInfoTypes();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

use Google\Cloud\Dlp\V2\ByteContentItem;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\RedactImageRequest;
use Google\Cloud\Dlp\V2\RedactImageRequest\ImageRedactionConfig;

/**
 * Redact only certain sensitive data from an image using infoTypes.
 *
 * @param string $callingProjectId    The project ID to run the API call under.
 * @param string $imagePath           The local filepath of the image to redact.
 * @param string $outputPath          The local filepath to save the resulting image to.
 */
function redact_image_listed_infotypes(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $imagePath = './test/data/test.png',
    string $outputPath = './test/data/redact_image_listed_infotypes.png'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Specify the types of info necessary to redact.
    $infoTypes = [
        (new InfoType())
            ->setName('US_SOCIAL_SECURITY_NUMBER'),
        (new InfoType())
            ->setName('EMAIL_ADDRESS'),
        (new InfoType())
            ->setName('PHONE_NUMBER'),
    ];

    // Create the configuration object.
    $inspectConfig = (new InspectConfig())
        ->setInfoTypes($infoTypes);

    // Read image file into a buffer.
    $imageRef = fopen($imagePath, 'rb');
    $imageBytes = fread($imageRef, filesize($imagePath));
    fclose($imageRef);

    // Get the image's content type.
    $typeConstant = (int) array_search(
        mime_content_type($imagePath),
        [false, 'image/jpeg', 'image/bmp', 'image/png', 'image/svg']
    );

    // Create the byte-storing object.
    $byteContent = (new ByteContentItem())
        ->setType($typeConstant)
        ->setData($imageBytes);

    // Create the image redaction config objects.
    $imageRedactionConfigs = [];
    foreach ($infoTypes as $infoType) {
        $config = (new ImageRedactionConfig())
            ->setInfoType($infoType);
        $imageRedactionConfigs[] = $config;
    }

    $parent = "projects/$callingProjectId/locations/global";

    // Run request.
    $redactImageRequest = (new RedactImageRequest())
        ->setParent($parent)
        ->setInspectConfig($inspectConfig)
        ->setByteItem($byteContent)
        ->setImageRedactionConfigs($imageRedactionConfigs);
    $response = $dlp->redactImage($redactImageRequest);

    // Save result to file.
    file_put_contents($outputPath, $response->getRedactedImage());

    // Print completion message.
    printf('Redacted image saved to %s' . PHP_EOL, $outputPath);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import mimetypes
from typing import List, Optional

import google.cloud.dlp


def redact_image_listed_info_types(
    project: str,
    filename: str,
    output_filename: str,
    info_types: List[str],
    min_likelihood: Optional[str] = None,
    mime_type: Optional[str] = None,
) -> None:
    """Uses the Data Loss Prevention API to redact protected data in an image.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        filename: The path to the file to inspect.
        output_filename: The path to which the redacted image will be written.
            A full list of info type categories can be fetched from the API.
        info_types: A list of strings representing info types to look for.
            A full list of info type categories can be fetched from the API.
        min_likelihood: A string representing the minimum likelihood threshold
            that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
            'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
        mime_type: The MIME type of the file. If not specified, the type is
            inferred via the Python standard library's mimetypes module.
    Returns:
        None; the response from the API is printed to the terminal.
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Prepare info_types by converting the list of strings into a list of
    # dictionaries (protos are also accepted).
    info_types = [{"name": info_type} for info_type in info_types]

    # Prepare image_redaction_configs, a list of dictionaries. Each dictionary
    # contains an info_type and optionally the color used for the replacement.
    # The color is omitted in this sample, so the default (black) will be used.
    image_redaction_configs = []
    if info_types is not None:
        for info_type in info_types:
            image_redaction_configs.append({"info_type": info_type})

    # Construct the configuration dictionary. Keys which are None may
    # optionally be omitted entirely.
    inspect_config = {"min_likelihood": min_likelihood, "info_types": info_types}

    # If mime_type is not specified, guess it from the filename.
    if mime_type is None:
        mime_guess = mimetypes.MimeTypes().guess_type(filename)
        mime_type = mime_guess[0] or "application/octet-stream"

    # Select the content type index from the list of supported types.
    # https://github.com/googleapis/googleapis/blob/master/google/privacy/dlp/v2/dlp.proto / message ByteContentItem
    supported_content_types = {
        None: 0,  # "Unspecified" or BYTES_TYPE_UNSPECIFIED
        "image/jpeg": 1,  # IMAGE_JPEG
        "image/bmp": 2,  # IMAGE_BMP
        "image/png": 3,  # IMAGE_PNG
        "image/svg": 4,  # IMAGE_SVG - Adjusted to "image/svg+xml" for correct MIME type
        "text/plain": 5,  # TEXT_UTF8
        # Note: No specific MIME type for general "image", mapping to IMAGE for any image type not specified
        "image": 6,  # IMAGE - Any image type
        "application/msword": 7,  # WORD_DOCUMENT
        "application/pdf": 8,  # PDF
        "application/powerpoint": 9,  # POWERPOINT_DOCUMENT
        "application/msexcel": 10,  # EXCEL_DOCUMENT
        "application/avro": 11,  # AVRO
        "text/csv": 12,  # CSV
        "text/tsv": 13,  # TSV
    }
    content_type_index = supported_content_types.get(mime_type, 0)

    # Construct the byte_item, containing the file's byte data.
    with open(filename, mode="rb") as f:
        byte_item = {"type_": content_type_index, "data": f.read()}

    # Convert the project id into a full resource id.
    parent = f"projects/{project}"

    # Call the API.
    response = dlp.redact_image(
        request={
            "parent": parent,
            "inspect_config": inspect_config,
            "image_redaction_configs": image_redaction_configs,
            "byte_item": byte_item,
        }
    )

    # Write out the results.
    with open(output_filename, mode="wb") as f:
        f.write(response.redacted_image)
    print(f"Wrote {len(response.redacted_image)} to {output_filename}")

REST

    {
      "byteItem": {
        "data": "[BASE64-ENCODED-IMAGE]",
        "type": "IMAGE_PNG"
      },
      "imageRedactionConfigs": [
        {
          "infoType": {
            "name": "PERSON_NAME"
          }
        },
        {
          "infoType": {
            "name": "EMAIL_ADDRESS"
          }
        },
        {
          "infoType": {
            "name": "PHONE_NUMBER"
          }
        }
      ]
    }

Sensitive Data Protection 會傳回下列項目：

    {
      "redactedImage": "[BASE64-ENCODED-IMAGE]"
    }

解碼 Base64 編碼的圖片。

產生的圖片如下所示：



如要快速瞭解哪些資訊已遮蓋，可以根據 infoType 為遮蓋資訊設定顏色。詳情請參閱下節。

使用顏色代碼遮蓋圖片中的 infoType

如要依 infoType 為遮蓋資訊加上顏色代碼，請將 infoType 偵測工具與 RGB 色域值配對。

如要使用不同顏色遮蓋圖片中的 infoType，請將要求提交至 DLP API 的 image.redact 方法。要求必須包含下列資訊：

• 圖片。
• 一或多個 infoType 偵測工具，每個工具都使用 RGB 色域值指派顏色。

請參考第一節中的原始圖片。如要以紫色方塊遮蓋美國身分證字號、以綠色方塊遮蓋電子郵件地址，以及以橘色方塊遮蓋電話號碼，請將下列 JSON 傳送至 DLP API 的 image.redact 方法：

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Protobuf;
using System;
using System.IO;

public class RedactImageWithColorCodedInfoTypes
{
    public static RedactImageResponse RedactImage(
        string projectId,
        string originalImagePath,
        string redactedImagePath)
    {
        // Instantiate the dlp client.
        var dlp = DlpServiceClient.Create();

        // Construct the content item by providing the image and its type.
        var byteContentItem = new ByteContentItem
        {
            Type = ByteContentItem.Types.BytesType.ImagePng,
            Data = ByteString.FromStream(new FileStream(originalImagePath, FileMode.Open))
        };

        // Define types of info and associate each one with a different color to redact config.
        var ssnRedactionConfig = new RedactImageRequest.Types.ImageRedactionConfig
        {
            InfoType = new InfoType { Name = "US_SOCIAL_SECURITY_NUMBER" },
            RedactionColor = new Color
            {
                Red = 0.3f,
                Green = 0.1f,
                Blue = 0.6f
            }
        };

        var emailRedactionConfig = new RedactImageRequest.Types.ImageRedactionConfig
        {
            InfoType = new InfoType { Name = "EMAIL_ADDRESS" },
            RedactionColor = new Color
            {
                Red = 0.5f,
                Green = 0.5f,
                Blue = 1f
            }
        };

        var phoneRedactionConfig = new RedactImageRequest.Types.ImageRedactionConfig
        {
            InfoType = new InfoType { Name = "PHONE_NUMBER" },
            RedactionColor = new Color
            {
                Red = 1f,
                Green = 0f,
                Blue = 0.6f
            }
        };

        // Construct the Redact request to be sent by the client. Do not specify the type of info to redact.
        var request = new RedactImageRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            ImageRedactionConfigs = { ssnRedactionConfig, emailRedactionConfig, phoneRedactionConfig },
            ByteItem = byteContentItem
        };

        // Call the API.
        RedactImageResponse response = dlp.RedactImage(request);

        // Writes redacted image into file
        response.RedactedImage.WriteTo(new FileStream(redactedImagePath, FileMode.Create, FileAccess.Write));

        Console.WriteLine($"Redacted image written to: {redactedImagePath}");

        return response;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import (
	"context"
	"fmt"
	"io"
	"os"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// redactImageFileColoredInfoTypes redacts data from an image with color-coded infoTypes.
func redactImageFileColoredInfoTypes(w io.Writer, projectID, inputPath, outputPath string) error {
	// projectId := "my-project-id"
	// inputPath := "testdata/image.jpg"
	// outputPath := "testdata/test-output-image-file-colored-infoType.jpeg"

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// read the image file
	fileBytes, err := os.ReadFile(inputPath)
	if err != nil {
		return err
	}

	// Specify the content to be redacted.
	byteItem := &dlppb.ByteContentItem{
		Type: dlppb.ByteContentItem_IMAGE_JPEG,
		Data: fileBytes,
	}

	// Define types of info to redact associate each one with a different color.
	// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types.

	ssnRedactionConfig := &dlppb.RedactImageRequest_ImageRedactionConfig{
		Target: &dlppb.RedactImageRequest_ImageRedactionConfig_InfoType{
			InfoType: &dlppb.InfoType{
				Name: "US_SOCIAL_SECURITY_NUMBER",
			},
		},
		RedactionColor: &dlppb.Color{
			Red:   0.3,
			Green: 0.1,
			Blue:  0.6,
		},
	}

	emailRedactionConfig := &dlppb.RedactImageRequest_ImageRedactionConfig{
		Target: &dlppb.RedactImageRequest_ImageRedactionConfig_InfoType{
			InfoType: &dlppb.InfoType{
				Name: "EMAIL_ADDRESS",
			},
		},
		RedactionColor: &dlppb.Color{
			Red:   0.5,
			Green: 0.5,
			Blue:  1,
		},
	}

	phoneRedactionConfig := &dlppb.RedactImageRequest_ImageRedactionConfig{
		Target: &dlppb.RedactImageRequest_ImageRedactionConfig_InfoType{
			InfoType: &dlppb.InfoType{
				Name: "PHONE_NUMBER",
			},
		},
		RedactionColor: &dlppb.Color{
			Red:   1,
			Green: 0,
			Blue:  0.6,
		},
	}

	// Construct the Inspect request to be sent by the client.
	req := &dlppb.RedactImageRequest{
		Parent:   fmt.Sprintf("projects/%s/locations/global", projectID),
		ByteItem: byteItem,
		ImageRedactionConfigs: []*dlppb.RedactImageRequest_ImageRedactionConfig{
			emailRedactionConfig,
			phoneRedactionConfig,
			ssnRedactionConfig,
		},
	}

	// Send the request.
	resp, err := client.RedactImage(ctx, req)
	if err != nil {
		return err
	}

	// Write the output file.
	if err := os.WriteFile(outputPath, resp.GetRedactedImage(), 0644); err != nil {
		return err
	}

	fmt.Fprintf(w, "Wrote output to %s", outputPath)
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.Color;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.RedactImageRequest;
import com.google.privacy.dlp.v2.RedactImageRequest.ImageRedactionConfig;
import com.google.privacy.dlp.v2.RedactImageResponse;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Collectors;

class RedactImageFileColoredInfoTypes {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "my-project-id";
    String inputPath = "src/test/resources/test.png";
    String outputPath = "redacted.png";
    redactImageFileColoredInfoTypes(projectId, inputPath, outputPath);
  }

  static void redactImageFileColoredInfoTypes(String projectId, String inputPath, String outputPath)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify the content to be redacted.
      ByteString fileBytes = ByteString.readFrom(new FileInputStream(inputPath));
      ByteContentItem byteItem =
          ByteContentItem.newBuilder().setType(BytesType.IMAGE_JPEG).setData(fileBytes).build();

      // Define types of info to redact associate each one with a different color.
      // See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
      ImageRedactionConfig ssnRedactionConfig =
          ImageRedactionConfig.newBuilder()
              .setInfoType(InfoType.newBuilder().setName("US_SOCIAL_SECURITY_NUMBER").build())
              .setRedactionColor(Color.newBuilder().setRed(.3f).setGreen(.1f).setBlue(.6f).build())
              .build();
      ImageRedactionConfig emailRedactionConfig =
          ImageRedactionConfig.newBuilder()
              .setInfoType(InfoType.newBuilder().setName("EMAIL_ADDRESS").build())
              .setRedactionColor(Color.newBuilder().setRed(.5f).setGreen(.5f).setBlue(1).build())
              .build();
      ImageRedactionConfig phoneRedactionConfig =
          ImageRedactionConfig.newBuilder()
              .setInfoType(InfoType.newBuilder().setName("PHONE_NUMBER").build())
              .setRedactionColor(Color.newBuilder().setRed(1).setGreen(0).setBlue(.6f).build())
              .build();

      // Create collection of all redact configurations.
      List<ImageRedactionConfig> imageRedactionConfigs =
          Arrays.asList(ssnRedactionConfig, emailRedactionConfig, phoneRedactionConfig);

      // List types of info to search for.
      InspectConfig config =
          InspectConfig.newBuilder()
              .addAllInfoTypes(
                  imageRedactionConfigs.stream()
                      .map(ImageRedactionConfig::getInfoType)
                      .collect(Collectors.toList()))
              .build();

      // Construct the Redact request to be sent by the client.
      RedactImageRequest request =
          RedactImageRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setByteItem(byteItem)
              .addAllImageRedactionConfigs(imageRedactionConfigs)
              .setInspectConfig(config)
              .build();

      // Use the client to send the API request.
      RedactImageResponse response = dlp.redactImage(request);

      // Parse the response and process results.
      FileOutputStream redacted = new FileOutputStream(outputPath);
      redacted.write(response.getRedactedImage().toByteArray());
      redacted.close();
      System.out.println("Redacted image written to " + outputPath);
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Imports required Node.js libraries
const mime = require('mime');
const fs = require('fs');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// The path to a local file to inspect. Can be a JPG or PNG image file.
// const filepath = 'path/to/image.png';

// The local path to save the resulting image to.
// const outputPath = 'result.png';

async function redactImageColoredInfoType() {
  // Define types of info to redact associate each one with a different color.
  const imageRedactionConfigs = [
    {
      infoType: {name: 'US_SOCIAL_SECURITY_NUMBER'},
      redactionColor: {red: 0.3, green: 0.1, blue: 0.6},
    },
    {
      infoType: {name: 'EMAIL_ADDRESS'},
      redactionColor: {red: 0.5, green: 0.5, blue: 1},
    },
    {
      infoType: {name: 'PHONE_NUMBER'},
      redactionColor: {red: 1, green: 0, blue: 0.6},
    },
  ];

  // Load image
  const fileTypeConstant =
    ['image/jpeg', 'image/bmp', 'image/png', 'image/svg'].indexOf(
      mime.getType(filepath)
    ) + 1;
  const fileBytes = Buffer.from(fs.readFileSync(filepath)).toString('base64');

  // Construct the Redact request to be sent by the client.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    byteItem: {
      type: fileTypeConstant,
      data: fileBytes,
    },
    imageRedactionConfigs: imageRedactionConfigs,
  };

  // Send the request and receive response from the service.
  const [response] = await dlp.redactImage(request);
  const image = response.redactedImage;
  fs.writeFileSync(outputPath, image);
  console.log(`Saved image redaction results to path: ${outputPath}`);
}
redactImageColoredInfoType();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

use Google\Cloud\Dlp\V2\ByteContentItem;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\Color;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\RedactImageRequest;
use Google\Cloud\Dlp\V2\RedactImageRequest\ImageRedactionConfig;

/**
 * Redact data from an image with color-coded infoTypes.
 *
 * @param string $callingProjectId    The project ID to run the API call under.
 * @param string $imagePath           The local filepath of the image to inspect.
 * @param string $outputPath          The local filepath to save the resulting image to.
 */
function redact_image_colored_infotypes(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $imagePath = './test/data/test.png',
    string $outputPath = './test/data/sensitive-data-image-redacted-color-coding.png'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Read image file into a buffer.
    $imageRef = fopen($imagePath, 'rb');
    $imageBytes = fread($imageRef, filesize($imagePath));
    fclose($imageRef);

    // Get the image's content type.
    $typeConstant = (int) array_search(
        mime_content_type($imagePath),
        [false, 'image/jpeg', 'image/bmp', 'image/png', 'image/svg']
    );

    // Create the byte-storing object.
    $byteContent = (new ByteContentItem())
        ->setType($typeConstant)
        ->setData($imageBytes);

    // Define the types of information to redact and associate each one with a different color.
    $ssnInfotype = (new InfoType())
        ->setName('US_SOCIAL_SECURITY_NUMBER');
    $emailInfotype = (new InfoType())
        ->setName('EMAIL_ADDRESS');
    $phoneInfotype = (new InfoType())
        ->setName('PHONE_NUMBER');
    $infotypes = [$ssnInfotype, $emailInfotype, $phoneInfotype];

    $ssnRedactionConfig = (new ImageRedactionConfig())
        ->setInfoType($ssnInfotype)
        ->setRedactionColor((new Color())
            ->setRed(.3)
            ->setGreen(.1)
            ->setBlue(.6));

    $emailRedactionConfig = (new ImageRedactionConfig())
        ->setInfoType($emailInfotype)
        ->setRedactionColor((new Color())
            ->setRed(.5)
            ->setGreen(.5)
            ->setBlue(1));

    $phoneRedactionConfig = (new ImageRedactionConfig())
        ->setInfoType($phoneInfotype)
        ->setRedactionColor((new Color())
            ->setRed(1)
            ->setGreen(0)
            ->setBlue(.6));

    $imageRedactionConfigs = [$ssnRedactionConfig, $emailRedactionConfig, $phoneRedactionConfig];

    // Create the configuration object.
    $inspectConfig = (new InspectConfig())
        ->setInfoTypes($infotypes);
    $parent = "projects/$callingProjectId/locations/global";

    // Run request.
    $redactImageRequest = (new RedactImageRequest())
        ->setParent($parent)
        ->setByteItem($byteContent)
        ->setInspectConfig($inspectConfig)
        ->setImageRedactionConfigs($imageRedactionConfigs);
    $response = $dlp->redactImage($redactImageRequest);

    // Save result to file.
    file_put_contents($outputPath, $response->getRedactedImage());

    // Print completion message.
    printf('Redacted image saved to %s ' . PHP_EOL, $outputPath);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import google.cloud.dlp


def redact_image_with_colored_info_types(
    project: str,
    filename: str,
    output_filename: str,
) -> None:
    """Uses the Data Loss Prevention API to redact protected data in an image by
    color coding the infoTypes.
       Args:
           project: The Google Cloud project id to use as a parent resource.
           filename: The path of the image file to inspect.
           output_filename: The path to which the redacted image will be written.
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Prepare image_redaction_configs, a list of dictionaries. Each dictionary
    # contains an infoType and the color used for the replacement.

    ssn_redaction_config = {
        "info_type": {"name": "US_SOCIAL_SECURITY_NUMBER"},
        "redaction_color": {
            "red": 0.3,
            "green": 0.1,
            "blue": 0.6,
        },
    }

    email_redaction_config = {
        "info_type": {"name": "EMAIL_ADDRESS"},
        "redaction_color": {
            "red": 0.5,
            "green": 0.5,
            "blue": 1.0,
        },
    }

    phone_redaction_config = {
        "info_type": {"name": "PHONE_NUMBER"},
        "redaction_color": {
            "red": 1.0,
            "green": 0.0,
            "blue": 0.6,
        },
    }

    image_redaction_configs = [
        ssn_redaction_config,
        email_redaction_config,
        phone_redaction_config,
    ]

    # Construct the configuration dictionary.
    inspect_config = {"info_types": [_i["info_type"] for _i in image_redaction_configs]}

    # Construct the byte_item, containing the file's byte data.
    with open(filename, mode="rb") as f:
        byte_item = {"type_": "IMAGE", "data": f.read()}

    # Convert the project id into a full resource id.
    parent = f"projects/{project}"

    # Call the API.
    response = dlp.redact_image(
        request={
            "parent": parent,
            "inspect_config": inspect_config,
            "image_redaction_configs": image_redaction_configs,
            "byte_item": byte_item,
        }
    )

    # Write out the results.
    with open(output_filename, mode="wb") as f:
        f.write(response.redacted_image)

    byte_count = len(response.redacted_image)
    print(f"Wrote {byte_count} to {output_filename}")

REST

    {
      "byteItem": {
        "data": "[BASE64-ENCODED-IMAGE]",
        "type": "IMAGE_PNG"
      },
      "imageRedactionConfigs": [
        {
          "infoType": {
            "name": "PERSON_NAME"
          },
          "redactionColor": {
            "red": 0.3,
            "green": 0.1,
            "blue": 0.6
          }
        },
        {
          "infoType": {
            "name": "EMAIL_ADDRESS"
          },
          "redactionColor": {
            "red": 0.5,
            "blue": 0.5,
            "green": 1
          }
        },
        {
          "infoType": {
            "name": "PHONE_NUMBER"
          },
          "redactionColor": {
            "red": 1,
            "blue": 0,
            "green": 0.6
          }
        }
      ]
    }

Sensitive Data Protection 會傳回下列項目：

    {
      "redactedImage": "[BASE64-ENCODED-IMAGE]"
    }

解碼 Base64 編碼的圖片。

產生的圖片如下所示：



遮蓋圖片中的所有文字

Sensitive Data Protection 也提供選項，可遮蓋圖片中偵測到的所有文字。

如要從圖片中遮蓋所有文字，請向 DLP API 的 image.redact 方法提交要求。要求必須包含下列資訊：

• 圖片。
• 「redactAllText」選項設為 true。

請參考第一節中的原始圖片。如要遮蓋所有文字，請將下列 JSON 傳送至 DLP API 的 image.redact 方法：

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Protobuf;
using System;
using System.IO;

public class RedactDetectedTextInImage
{
    public static RedactImageResponse RedactTextImage(
        string projectId,
        string originalImagePath,
        string redactedImagePath)
    {
        // Instantiate the dlp client.
        var dlp = DlpServiceClient.Create();

        // Construct the content item by specifying the content to be redacted.
        var byteContentItem = new ByteContentItem
        {
            Type = ByteContentItem.Types.BytesType.ImagePng,
            Data = ByteString.FromStream(new FileStream(originalImagePath, FileMode.Open))
        };

        // Enable redaction of all text.
        var imageRedactionConfig = new RedactImageRequest.Types.ImageRedactionConfig
        {
            RedactAllText = true
        };

        // Construct the Redact request to be sent by the client. Do not specify the type of info to redact.
        var request = new RedactImageRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            ImageRedactionConfigs = { imageRedactionConfig },
            ByteItem = byteContentItem
        };

        // Call the API.
        var response = dlp.RedactImage(request);

        // Inspect the response.
        Console.WriteLine($"Redacted image written to: {redactedImagePath}");

        // Writes redacted image into file
        response.RedactedImage.WriteTo(new FileStream(redactedImagePath, FileMode.Create, FileAccess.Write));

        return response;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import (
	"context"
	"fmt"
	"io"
	"os"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// redactImageFileAllText redacts all detected text in an image
func redactImageFileAllText(w io.Writer, projectID, inputPath, outputPath string) error {
	// projectId := "my-project-id"
	// inputPath := "testdata/image.jpg"
	// outputPath := "testdata/test-output-image-file-all-text.jpeg"
	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// read the image file
	fileBytes, err := os.ReadFile(inputPath)
	if err != nil {
		return err
	}

	// Specify the content to be redacted.
	byteItem := &dlppb.ByteContentItem{
		Type: dlppb.ByteContentItem_IMAGE_JPEG,
		Data: fileBytes,
	}

	// Enable redaction of all text.
	imageRedactConfig := &dlppb.RedactImageRequest_ImageRedactionConfig{
		Target: &dlppb.RedactImageRequest_ImageRedactionConfig_RedactAllText{
			RedactAllText: true,
		},
	}

	// Construct the Redact request to be sent by the client.
	// Do not specify the type of info to redact.
	req := &dlppb.RedactImageRequest{
		Parent:   fmt.Sprintf("projects/%s/locations/global", projectID),
		ByteItem: byteItem,
		ImageRedactionConfigs: []*dlppb.RedactImageRequest_ImageRedactionConfig{
			imageRedactConfig,
		},
	}

	// Send the request.
	resp, err := client.RedactImage(ctx, req)
	if err != nil {
		return err
	}

	// Write the output file.
	if err := os.WriteFile(outputPath, resp.GetRedactedImage(), 0644); err != nil {
		return err
	}
	fmt.Fprintf(w, "Wrote output to %s", outputPath)
	return nil

}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.RedactImageRequest;
import com.google.privacy.dlp.v2.RedactImageRequest.ImageRedactionConfig;
import com.google.privacy.dlp.v2.RedactImageResponse;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;

class RedactImageFileAllText {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "my-project-id";
    String inputPath = "src/test/resources/sensitive-data-image.jpeg";
    String outputPath = "sensitive-data-image-redacted.jpeg";
    redactImageFileAllText(projectId, inputPath, outputPath);
  }

  static void redactImageFileAllText(String projectId, String inputPath, String outputPath)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify the content to be redacted.
      ByteString fileBytes = ByteString.readFrom(new FileInputStream(inputPath));
      ByteContentItem byteItem =
          ByteContentItem.newBuilder().setType(BytesType.IMAGE_JPEG).setData(fileBytes).build();

      // Enable redaction of all text.
      ImageRedactionConfig imageRedactionConfig =
          ImageRedactionConfig.newBuilder().setRedactAllText(true).build();

      // Construct the Redact request to be sent by the client.
      // Do not specify the type of info to redact.
      RedactImageRequest request =
          RedactImageRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setByteItem(byteItem)
              .addImageRedactionConfigs(imageRedactionConfig)
              .build();

      // Use the client to send the API request.
      RedactImageResponse response = dlp.redactImage(request);

      // Parse the response and process results.
      FileOutputStream redacted = new FileOutputStream(outputPath);
      redacted.write(response.getRedactedImage().toByteArray());
      redacted.close();
      System.out.println("Redacted image written to " + outputPath);
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Imports required Node.js libraries
const mime = require('mime');
const fs = require('fs');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// The path to a local file to inspect. Can be a JPG or PNG image file.
// const filepath = 'path/to/image.png';

// The local path to save the resulting image to.
// const outputPath = 'result.png';

async function redactImageAllText() {
  // Enable redaction of all text.
  const imageRedactionConfigs = [{redactAllText: true}];

  // Load image
  const fileTypeConstant =
    ['image/jpeg', 'image/bmp', 'image/png', 'image/svg'].indexOf(
      mime.getType(filepath)
    ) + 1;
  const fileBytes = Buffer.from(fs.readFileSync(filepath)).toString('base64');

  // Construct the Redact request to be sent by the client.
  // Do not specify the type of info to redact.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    byteItem: {
      type: fileTypeConstant,
      data: fileBytes,
    },
    imageRedactionConfigs: imageRedactionConfigs,
  };

  // Run image redaction request
  const [response] = await dlp.redactImage(request);

  // Parse the response and process results.
  const image = response.redactedImage;
  fs.writeFileSync(outputPath, image);
  console.log(`Saved image redaction results to path: ${outputPath}`);
}
redactImageAllText();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

use Google\Cloud\Dlp\V2\ByteContentItem;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\RedactImageRequest;
use Google\Cloud\Dlp\V2\RedactImageRequest\ImageRedactionConfig;

/**
 * Redact all detected text in an image.
 *
 * @param string $callingProjectId    The project ID to run the API call under.
 * @param string $imagePath           The local filepath of the image to redact.
 * @param string $outputPath          The local filepath to save the resulting image to.
 */
function redact_image_all_text(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $imagePath = './test/data/test.png',
    string $outputPath = './test/data/redact_image_all_text.png'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Read image file into a buffer.
    $imageRef = fopen($imagePath, 'rb');
    $imageBytes = fread($imageRef, filesize($imagePath));
    fclose($imageRef);

    // Get the image's content type.
    $typeConstant = (int) array_search(
        mime_content_type($imagePath),
        [false, 'image/jpeg', 'image/bmp', 'image/png', 'image/svg']
    );

    // Create the byte-storing object.
    $byteContent = (new ByteContentItem())
        ->setType($typeConstant)
        ->setData($imageBytes);

    // Enable redaction of all text.
    $imageRedactionConfig = (new ImageRedactionConfig())
        ->setRedactAllText(true);

    $parent = "projects/$callingProjectId/locations/global";

    // Run request.
    $redactImageRequest = (new RedactImageRequest())
        ->setParent($parent)
        ->setByteItem($byteContent)
        ->setImageRedactionConfigs([$imageRedactionConfig]);
    $response = $dlp->redactImage($redactImageRequest);

    // Save result to file.
    file_put_contents($outputPath, $response->getRedactedImage());

    // Print completion message.
    printf('Redacted image saved to %s' . PHP_EOL, $outputPath);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import google.cloud.dlp


def redact_image_all_text(
    project: str,
    filename: str,
    output_filename: str,
) -> None:
    """Uses the Data Loss Prevention API to redact all text in an image.

    Args:
        project: The Google Cloud project id to use as a parent resource.
        filename: The path to the file to inspect.
        output_filename: The path to which the redacted image will be written.

    Returns:
        None; the response from the API is printed to the terminal.
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the image_redaction_configs, indicating to DLP that all text in
    # the input image should be redacted.
    image_redaction_configs = [{"redact_all_text": True}]

    # Construct the byte_item, containing the file's byte data.
    with open(filename, mode="rb") as f:
        byte_item = {"type_": google.cloud.dlp_v2.FileType.IMAGE, "data": f.read()}

    # Convert the project id into a full resource id.
    parent = f"projects/{project}"

    # Call the API.
    response = dlp.redact_image(
        request={
            "parent": parent,
            "image_redaction_configs": image_redaction_configs,
            "byte_item": byte_item,
        }
    )

    # Write out the results.
    with open(output_filename, mode="wb") as f:
        f.write(response.redacted_image)

    print(
        "Wrote {byte_count} to {filename}".format(
            byte_count=len(response.redacted_image), filename=output_filename
        )
    )

REST

    {
      "byteItem": {
        "data": "[BASE64-ENCODED-IMAGE]",
        "type": "IMAGE_PNG"
      },
      "imageRedactionConfigs": [
        {
          "redactAllText": true
        }
      ]
    }

Sensitive Data Protection 會傳回下列項目：

    {
      "redactedImage": "[BASE64-ENCODED-IMAGE]"
    }

解碼 Base64 編碼的圖片。

API 會傳回您提供的同一張圖片，但依據您的條件識別為含有機密資訊的任何文字則會受到遮蓋。

產生的圖片如下所示：



設定可能性值的程式碼範例

這個範例與從圖片中遮蓋特定 infoType 類似。此外，這項範例也會示範如何指定最低可能性。

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Protobuf;
using System;
using System.IO;

public class RedactImage
{
    public static RedactImageResponse Redact(string projectId, string originalImagePath, string redactedImagePath)
    {
        var request = new RedactImageRequest
        {
            Parent = new LocationName(projectId, "global").ToString(),
            InspectConfig = new InspectConfig
            {
                MinLikelihood = Likelihood.Likely,
                IncludeQuote = true,
                InfoTypes =
                {
                    new InfoType { Name = "PHONE_NUMBER" },
                    new InfoType { Name = "EMAIL_ADDRESS" },
                    new InfoType { Name = "CREDIT_CARD_NUMBER" }
                }
            },
            ByteItem = new ByteContentItem
            {
                Type = ByteContentItem.Types.BytesType.ImagePng,
                Data = ByteString.FromStream(new FileStream(originalImagePath, FileMode.Open))
            },
        };

        var client = DlpServiceClient.Create();
        var response = client.RedactImage(request);

        Console.WriteLine($"Extracted text: {response.ExtractedText}");

        // Writes redacted image into file
        response.RedactedImage.WriteTo(new FileStream(redactedImagePath, FileMode.Create, FileAccess.Write));

        return response;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import (
	"context"
	"fmt"
	"io"
	"os"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// redactImage blacks out the identified portions of the input image (with type bytesType)
// and stores the result in outputPath.
func redactImage(w io.Writer, projectID string, infoTypeNames []string, bytesType dlppb.ByteContentItem_BytesType, inputPath, outputPath string) error {
	// projectID := "my-project-id"
	// infoTypeNames := []string{"US_SOCIAL_SECURITY_NUMBER"}
	// bytesType := dlppb.ByteContentItem_IMAGE_PNG
	// inputPath := /tmp/input
	// outputPath := /tmp/output

	ctx := context.Background()

	client, err := dlp.NewClient(ctx)
	if err != nil {
		return fmt.Errorf("dlp.NewClient: %w", err)
	}
	defer client.Close()

	// Convert the info type strings to a list of InfoTypes.
	var infoTypes []*dlppb.InfoType
	for _, it := range infoTypeNames {
		infoTypes = append(infoTypes, &dlppb.InfoType{Name: it})
	}

	// Convert the info type strings to a list of types to redact in the image.
	var redactInfoTypes []*dlppb.RedactImageRequest_ImageRedactionConfig
	for _, it := range infoTypeNames {
		redactInfoTypes = append(redactInfoTypes, &dlppb.RedactImageRequest_ImageRedactionConfig{
			Target: &dlppb.RedactImageRequest_ImageRedactionConfig_InfoType{
				InfoType: &dlppb.InfoType{Name: it},
			},
		})
	}

	// Read the input file.
	b, err := os.ReadFile(inputPath)
	if err != nil {
		return fmt.Errorf("os.ReadFile: %w", err)
	}

	// Create a configured request.
	req := &dlppb.RedactImageRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		InspectConfig: &dlppb.InspectConfig{
			InfoTypes:     infoTypes,
			MinLikelihood: dlppb.Likelihood_POSSIBLE,
		},
		// The item to analyze.
		ByteItem: &dlppb.ByteContentItem{
			Type: bytesType,
			Data: b,
		},
		ImageRedactionConfigs: redactInfoTypes,
	}
	// Send the request.
	resp, err := client.RedactImage(ctx, req)
	if err != nil {
		return fmt.Errorf("RedactImage: %w", err)
	}
	// Write the output file.
	if err := os.WriteFile(outputPath, resp.GetRedactedImage(), 0644); err != nil {
		return fmt.Errorf("os.WriteFile: %w", err)
	}
	fmt.Fprintf(w, "Wrote output to %s", outputPath)
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.RedactImageRequest;
import com.google.privacy.dlp.v2.RedactImageResponse;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

class RedactImageFile {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "my-project-id";
    String inputPath = "src/test/resources/test.png";
    String outputPath = "redacted.png";
    redactImageFile(projectId, inputPath, outputPath);
  }

  static void redactImageFile(String projectId, String inputPath, String outputPath)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify the content to be inspected.
      ByteString fileBytes = ByteString.readFrom(new FileInputStream(inputPath));
      ByteContentItem byteItem =
          ByteContentItem.newBuilder().setType(BytesType.IMAGE).setData(fileBytes).build();

      // Specify the type of info and likelihood necessary to redact.
      List<InfoType> infoTypes = new ArrayList<>();
      // See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
      for (String typeName : new String[] {"PHONE_NUMBER", "EMAIL_ADDRESS", "CREDIT_CARD_NUMBER"}) {
        infoTypes.add(InfoType.newBuilder().setName(typeName).build());
      }
      InspectConfig config =
          InspectConfig.newBuilder()
              .addAllInfoTypes(infoTypes)
              .setMinLikelihood(Likelihood.LIKELY)
              .build();

      // Construct the Redact request to be sent by the client.
      RedactImageRequest request =
          RedactImageRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setByteItem(byteItem)
              .setInspectConfig(config)
              .build();

      // Use the client to send the API request.
      RedactImageResponse response = dlp.redactImage(request);

      // Parse the response and process results.
      FileOutputStream redacted = new FileOutputStream(outputPath);
      redacted.write(response.getRedactedImage().toByteArray());
      redacted.close();
      System.out.println("Redacted image written to " + outputPath);
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Imports required Node.js libraries
const mime = require('mime');
const fs = require('fs');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// The path to a local file to inspect. Can be a JPG or PNG image file.
// const filepath = 'path/to/image.png';

// The minimum likelihood required before redacting a match
// const minLikelihood = 'LIKELIHOOD_UNSPECIFIED';

// The infoTypes of information to redact
// const infoTypes = [{ name: 'EMAIL_ADDRESS' }, { name: 'PHONE_NUMBER' }];

// The local path to save the resulting image to.
// const outputPath = 'result.png';
async function redactImage() {
  const imageRedactionConfigs = infoTypes.map(infoType => {
    return {infoType: infoType};
  });

  // Load image
  const fileTypeConstant =
    ['image/jpeg', 'image/bmp', 'image/png', 'image/svg'].indexOf(
      mime.getType(filepath)
    ) + 1;
  const fileBytes = Buffer.from(fs.readFileSync(filepath)).toString('base64');

  // Construct image redaction request
  const request = {
    parent: `projects/${projectId}/locations/global`,
    byteItem: {
      type: fileTypeConstant,
      data: fileBytes,
    },
    inspectConfig: {
      minLikelihood: minLikelihood,
      infoTypes: infoTypes,
    },
    imageRedactionConfigs: imageRedactionConfigs,
  };

  // Run image redaction request
  const [response] = await dlp.redactImage(request);
  const image = response.redactedImage;
  fs.writeFileSync(outputPath, image);
  console.log(`Saved image redaction results to path: ${outputPath}`);
}
redactImage();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

use Google\Cloud\Dlp\V2\ByteContentItem;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\RedactImageRequest;
use Google\Cloud\Dlp\V2\RedactImageRequest\ImageRedactionConfig;

/**
 * Redact sensitive data from an image.
 *
 * @param string $callingProjectId    The project ID to run the API call under
 * @param string $imagePath           The local filepath of the image to inspect
 * @param string $outputPath          The local filepath to save the resulting image to
 */
function redact_image(
    string $callingProjectId,
    string $imagePath,
    string $outputPath
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // The infoTypes of information to match
    $phoneNumberInfoType = (new InfoType())
        ->setName('PHONE_NUMBER');
    $infoTypes = [$phoneNumberInfoType];

    // The minimum likelihood required before returning a match
    $minLikelihood = likelihood::LIKELIHOOD_UNSPECIFIED;

    // Whether to include the matching string in the response
    $includeQuote = true;

    // Create the configuration object
    $inspectConfig = (new InspectConfig())
        ->setMinLikelihood($minLikelihood)
        ->setInfoTypes($infoTypes);

    // Read image file into a buffer
    $imageRef = fopen($imagePath, 'rb');
    $imageBytes = fread($imageRef, filesize($imagePath));
    fclose($imageRef);

    // Get the image's content type
    $typeConstant = (int) array_search(
        mime_content_type($imagePath),
        [false, 'image/jpeg', 'image/bmp', 'image/png', 'image/svg']
    );

    // Create the byte-storing object
    $byteContent = (new ByteContentItem())
        ->setType($typeConstant)
        ->setData($imageBytes);

    // Create the image redaction config objects
    $imageRedactionConfigs = [];
    foreach ($infoTypes as $infoType) {
        $config = (new ImageRedactionConfig())
            ->setInfoType($infoType);
        $imageRedactionConfigs[] = $config;
    }

    $parent = "projects/$callingProjectId/locations/global";

    // Run request
    $redactImageRequest = (new RedactImageRequest())
        ->setParent($parent)
        ->setInspectConfig($inspectConfig)
        ->setByteItem($byteContent)
        ->setImageRedactionConfigs($imageRedactionConfigs);
    $response = $dlp->redactImage($redactImageRequest);

    // Save result to file
    file_put_contents($outputPath, $response->getRedactedImage());

    // Print completion message
    print('Redacted image saved to ' . $outputPath . PHP_EOL);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱這篇文章。

如要驗證 Sensitive Data Protection，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import mimetypes
from typing import List

import google.cloud.dlp


def redact_image(
    project: str,
    filename: str,
    output_filename: str,
    info_types: List[str],
    min_likelihood: str = None,
    mime_type: str = None,
) -> None:
    """Uses the Data Loss Prevention API to redact protected data in an image.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        filename: The path to the file to inspect.
        output_filename: The path to which the redacted image will be written.
        info_types: A list of strings representing info types to look for.
            A full list of info type categories can be fetched from the API.
        min_likelihood: A string representing the minimum likelihood threshold
            that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
            'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
        mime_type: The MIME type of the file. If not specified, the type is
            inferred via the Python standard library's mimetypes module.
    Returns:
        None; the response from the API is printed to the terminal.
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Prepare info_types by converting the list of strings into a list of
    # dictionaries (protos are also accepted).
    info_types = [{"name": info_type} for info_type in info_types]

    # Prepare image_redaction_configs, a list of dictionaries. Each dictionary
    # contains an info_type and optionally the color used for the replacement.
    # The color is omitted in this sample, so the default (black) will be used.
    image_redaction_configs = []

    if info_types is not None:
        for info_type in info_types:
            image_redaction_configs.append({"info_type": info_type})

    # Construct the configuration dictionary. Keys which are None may
    # optionally be omitted entirely.
    inspect_config = {
        "min_likelihood": min_likelihood,
        "info_types": info_types,
    }

    # If mime_type is not specified, guess it from the filename.
    if mime_type is None:
        mime_guess = mimetypes.MimeTypes().guess_type(filename)
        mime_type = mime_guess[0] or "application/octet-stream"

    # Select the content type index from the list of supported types.
    # https://github.com/googleapis/googleapis/blob/master/google/privacy/dlp/v2/dlp.proto / message ByteContentItem
    supported_content_types = {
        None: 0,  # "Unspecified" or BYTES_TYPE_UNSPECIFIED
        "image/jpeg": 1,  # IMAGE_JPEG
        "image/bmp": 2,  # IMAGE_BMP
        "image/png": 3,  # IMAGE_PNG
        "image/svg": 4,  # IMAGE_SVG - Adjusted to "image/svg+xml" for correct MIME type
        "text/plain": 5,  # TEXT_UTF8
        # Note: No specific MIME type for general "image", mapping to IMAGE for any image type not specified
        "image": 6,  # IMAGE - Any image type
        "application/msword": 7,  # WORD_DOCUMENT
        "application/pdf": 8,  # PDF
        "application/powerpoint": 9,  # POWERPOINT_DOCUMENT
        "application/msexcel": 10,  # EXCEL_DOCUMENT
        "application/avro": 11,  # AVRO
        "text/csv": 12,  # CSV
        "text/tsv": 13,  # TSV
    }
    content_type_index = supported_content_types.get(mime_type, 0)

    # Construct the byte_item, containing the file's byte data.
    with open(filename, mode="rb") as f:
        byte_item = {"type_": content_type_index, "data": f.read()}

    # Convert the project id into a full resource id.
    parent = f"projects/{project}"

    # Call the API.
    response = dlp.redact_image(
        request={
            "parent": parent,
            "inspect_config": inspect_config,
            "image_redaction_configs": image_redaction_configs,
            "byte_item": byte_item,
        }
    )

    # Write out the results.
    with open(output_filename, mode="wb") as f:
        f.write(response.redacted_image)
    print(
        "Wrote {byte_count} to {filename}".format(
            byte_count=len(response.redacted_image), filename=output_filename
        )
    )

立即體驗

您可以在 image.redact 的參考資料頁面中，使用 APIs Explorer 試用這個頁面上的每個範例，或使用自己的圖片進行實驗：

前往 API Explorer

後續步驟

• 進一步瞭解圖片檢查和遮蓋。
• 完成使用 Sensitive Data Protection 遮蓋機密資料程式碼研究室。
• 瞭解如何檢查圖片是否含有機密資料。
• 進一步瞭解如何在儲存空間中建立去識別化資料副本。