偵測網路實體和頁面

網路偵測功能會偵測圖片的網路參照。

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嘉年華圖片 — *圖片來源*： Quinten de Graaf (Unsplash)。

類別	回應
網路實體	*entityId：/m/02p7_j8、score：1.3225499、description：里約熱內盧嘉年華 entityId：/m/06gmr、score：1.1684971、description：里約熱內盧 entityId：/m/04cx88、score：1.05945、description*：巴西嘉年華 ...
完全相符的圖片	*url：https://1000lugaresparair.files.wordpress.com/2017/11/quinten-de-graaf-278848.jpg url*：https://freewalkingtourrotterdam.com/wp-content/uploads/2017/07/quinten-de-graaf-278848.jpg ...
部分相符的圖片	*url：https://www.linnanneito.fi/wp-content/uploads/sambakarnevaali-riossa.jpg url*：https://static.airhelp.com/wp-content/uploads/2019/02/26105557/two-women-in-carnival-costumes.jpg ...
含有相符圖片的頁面	*url: https://travelnoire.com/best-carnival-celebrations-around-the-world/, pageTitle: Best \u003cb\u003eCarnival\u003c/b\u003e Celebrations Around The World - Travel Noire, fullMatchingImages: [{url: https://travelnoire.com/wp-content/uploads/2019/02/quinten-de-graaf-278848-unsplash.jpg}] url：https://bespokebrazil.com/rio-carnival-2019/， pageTitle：Visit \u003cb\u003eRio Carnival 2019\u003c/b\u003e with the Brazil Specialists - Bespoke Brazil， partialMatchingImages：[{ url*：https://bespoke-brazil-2018-bespokebrazil.netdna-ssl.com/wp-content/uploads/2019/01/Carnival-1.jpg}] ...
外觀相似的圖片	*url：https://www.brazilbookers.com/_images/photos/rio-carnival-images/rio-carnival-2016-carnival-date.jpg url*：https://image.redbull.com/rbcom/010/2017-02-08/1331843859949_3/0100/0/1/watch-rio-carnival-2017-live-on-red-bull-tv.jpg ...
最佳猜測標籤	rio carnival 2019 dancers

網路偵測要求

設定 Google Cloud 專案和驗證

如果您尚未建立 Google Cloud 專案，請立即建立。展開這個部分即可查看操作說明。

登入 Google Cloud 帳戶。如果您是 Google Cloud新手，歡迎建立帳戶，親自評估產品在實際工作環境中的成效。新客戶還能獲得價值 $300 美元的免費抵免額，可用於執行、測試及部署工作負載。

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Roles required to select or create a project

Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Go to project selector

Verify that billing is enabled for your Google Cloud project.

Enable the Vision API.

Roles required to enable APIs

To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

Enable the API

安裝 Google Cloud CLI。

若您採用的是外部識別資訊提供者 (IdP)，請先使用聯合身分登入 gcloud CLI。

執行下列指令，初始化 gcloud CLI：

gcloud init

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Roles required to select or create a project

Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Go to project selector

Verify that billing is enabled for your Google Cloud project.

Enable the Vision API.

Roles required to enable APIs

To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

Enable the API

安裝 Google Cloud CLI。

若您採用的是外部識別資訊提供者 (IdP)，請先使用聯合身分登入 gcloud CLI。

執行下列指令，初始化 gcloud CLI：

gcloud init

使用本機圖片偵測網路實體

您可以使用 Vision API 對本機圖片檔執行特徵偵測。

如果是 REST 要求，請在要求主體中，以 base64 編碼字串的形式傳送圖片檔案內容。

如果是 gcloud 和用戶端程式庫要求，請在要求中指定本機圖片的路徑。

REST

使用任何要求資料之前，請先修改下列項目的值：

BASE64_ENCODED_IMAGE：二進位圖片資料的 Base64 表示法 (ASCII 字串)。這個字串應類似下列字串：
- /9j/4QAYRXhpZgAA...9tAVx/zDQDlGxn//2Q==
詳情請參閱「base64 編碼」主題。
RESULTS_INT：(選填) 要傳回的結果整數值。如果省略 "maxResults" 欄位及其值，API 會傳回預設值 (10 個結果)。這個欄位不適用於下列特徵類型：TEXT_DETECTION、DOCUMENT_TEXT_DETECTION 或 CROP_HINTS。
PROJECT_ID： Google Cloud 專案 ID。

HTTP 方法和網址：

POST https://vision.googleapis.com/v1/images:annotate

JSON 要求內文：

{
  "requests": [
    {
      "image": {
        "content": "BASE64_ENCODED_IMAGE"
      },
      "features": [
        {
          "maxResults": RESULTS_INT,
          "type": "WEB_DETECTION"
        },
      ]
    }
  ]
}

如要傳送要求，請選擇以下其中一個選項：

curl

注意：下列指令假設您已執行 gcloud init 或 gcloud auth login 透過使用者帳戶登入 gcloud CLI，或是使用 Cloud Shell 自動登入 gcloud CLI。您可以執行 gcloud auth list，查看目前使用的帳戶。

將要求主體儲存在名為 request.json 的檔案中，然後執行下列指令：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "x-goog-user-project: PROJECT_ID" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://vision.googleapis.com/v1/images:annotate"

PowerShell

注意：下列指令假設您已執行 gcloud init 或 gcloud auth login，透過使用者帳戶登入 gcloud CLI。您可以執行 gcloud auth list，查看目前使用的帳戶。

將要求主體儲存在名為 request.json 的檔案中，然後執行下列指令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://vision.googleapis.com/v1/images:annotate" | Select-Object -Expand Content

如果要求成功，伺服器會傳回 200 OK HTTP 狀態碼與 JSON 格式的回應。

回覆：

回應

{
  "responses": [
    {
      "webDetection": {
        "webEntities": [
          {
            "entityId": "/m/02p7_j8",
            "score": 1.44225,
            "description": "Carnival in Rio de Janeiro"
          },
          {
            "entityId": "/m/06gmr",
            "score": 1.2913725,
            "description": "Rio de Janeiro"
          },
          {
            "entityId": "/m/04cx88",
            "score": 0.78465,
            "description": "Brazilian Carnival"
          },
          {
            "entityId": "/m/09l9f",
            "score": 0.7166,
            "description": "Carnival"
          },
          ...
        ],
        "fullMatchingImages": [
          {
            "url": "https://1000lugaresparair.files.wordpress.com/2017/11/quinten-de-graaf-278848.jpg"
          },
          ...
        ],
        "partialMatchingImages": [
          {
            "url": "https://www.linnanneito.fi/wp-content/uploads/sambakarnevaali-riossa.jpg"
          },
          ...
        ],
        "pagesWithMatchingImages": [
          {
            "url": "https://www.intrepidtravel.com/us/brazil/rio-carnival-122873",
            "pageTitle": "\u003cb\u003eRio Carnival\u003c/b\u003e | Intrepid Travel US",
            "partialMatchingImages": [
              {
                "url": "https://www.intrepidtravel.com/sites/intrepid/files/styles/large/public/elements/product/hero/GGSR-Brazil-rio-carnival-ladies.jpg"
              },
              ...
        ],
        "visuallySimilarImages": [
          {
            "url": "https://pbs.twimg.com/media/DVoQOx6WkAIpHKF.jpg"
          },
          ...
        ],
        "bestGuessLabels": [
          {
            "label": "rio carnival",
            "languageCode": "en"
          }
        ]
      }
    }
  ]
}

Go

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vision 快速入門導覽課程」中的 Go 設定說明操作。詳情請參閱 Vision Go API 參考文件。

如要向 Vision 進行驗證，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機制」。


// detectWeb gets image properties from the Vision API for an image at the given file path.
func detectWeb(w io.Writer, file string) error {
	ctx := context.Background()

	client, err := vision.NewImageAnnotatorClient(ctx)
	if err != nil {
		return err
	}

	f, err := os.Open(file)
	if err != nil {
		return err
	}
	defer f.Close()

	image, err := vision.NewImageFromReader(f)
	if err != nil {
		return err
	}
	web, err := client.DetectWeb(ctx, image, nil)
	if err != nil {
		return err
	}

	fmt.Fprintln(w, "Web properties:")
	if len(web.FullMatchingImages) != 0 {
		fmt.Fprintln(w, "\tFull image matches:")
		for _, full := range web.FullMatchingImages {
			fmt.Fprintf(w, "\t\t%s\n", full.Url)
		}
	}
	if len(web.PagesWithMatchingImages) != 0 {
		fmt.Fprintln(w, "\tPages with this image:")
		for _, page := range web.PagesWithMatchingImages {
			fmt.Fprintf(w, "\t\t%s\n", page.Url)
		}
	}
	if len(web.WebEntities) != 0 {
		fmt.Fprintln(w, "\tEntities:")
		fmt.Fprintln(w, "\t\tEntity\t\tScore\tDescription")
		for _, entity := range web.WebEntities {
			fmt.Fprintf(w, "\t\t%-14s\t%-2.4f\t%s\n", entity.EntityId, entity.Score, entity.Description)
		}
	}
	if len(web.BestGuessLabels) != 0 {
		fmt.Fprintln(w, "\tBest guess labels:")
		for _, label := range web.BestGuessLabels {
			fmt.Fprintf(w, "\t\t%s\n", label.Label)
		}
	}

	return nil
}

Java

在試用這個範例之前，請先按照使用用戶端程式庫的 Vision API 快速入門導覽課程中的 Java 設定操作說明進行操作。詳情請參閱 Vision API Java 參考文件。


import com.google.cloud.vision.v1.AnnotateImageRequest;
import com.google.cloud.vision.v1.AnnotateImageResponse;
import com.google.cloud.vision.v1.BatchAnnotateImagesResponse;
import com.google.cloud.vision.v1.Feature;
import com.google.cloud.vision.v1.Feature.Type;
import com.google.cloud.vision.v1.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.cloud.vision.v1.WebDetection;
import com.google.cloud.vision.v1.WebDetection.WebEntity;
import com.google.cloud.vision.v1.WebDetection.WebImage;
import com.google.cloud.vision.v1.WebDetection.WebLabel;
import com.google.cloud.vision.v1.WebDetection.WebPage;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

public class DetectWebDetections {

  public static void detectWebDetections() throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String filePath = "path/to/your/image/file.jpg";
    detectWebDetections(filePath);
  }

  // Finds references to the specified image on the web.
  public static void detectWebDetections(String filePath) throws IOException {
    List<AnnotateImageRequest> requests = new ArrayList<>();

    ByteString imgBytes = ByteString.readFrom(new FileInputStream(filePath));

    Image img = Image.newBuilder().setContent(imgBytes).build();
    Feature feat = Feature.newBuilder().setType(Type.WEB_DETECTION).build();
    AnnotateImageRequest request =
        AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
    requests.add(request);

    // 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 (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
      BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
      List<AnnotateImageResponse> responses = response.getResponsesList();

      for (AnnotateImageResponse res : responses) {
        if (res.hasError()) {
          System.out.format("Error: %s%n", res.getError().getMessage());
          return;
        }

        // Search the web for usages of the image. You could use these signals later
        // for user input moderation or linking external references.
        // For a full list of available annotations, see http://g.co/cloud/vision/docs
        WebDetection annotation = res.getWebDetection();
        System.out.println("Entity:Id:Score");
        System.out.println("===============");
        for (WebEntity entity : annotation.getWebEntitiesList()) {
          System.out.println(
              entity.getDescription() + " : " + entity.getEntityId() + " : " + entity.getScore());
        }
        for (WebLabel label : annotation.getBestGuessLabelsList()) {
          System.out.format("%nBest guess label: %s", label.getLabel());
        }
        System.out.println("%nPages with matching images: Score%n==");
        for (WebPage page : annotation.getPagesWithMatchingImagesList()) {
          System.out.println(page.getUrl() + " : " + page.getScore());
        }
        System.out.println("%nPages with partially matching images: Score%n==");
        for (WebImage image : annotation.getPartialMatchingImagesList()) {
          System.out.println(image.getUrl() + " : " + image.getScore());
        }
        System.out.println("%nPages with fully matching images: Score%n==");
        for (WebImage image : annotation.getFullMatchingImagesList()) {
          System.out.println(image.getUrl() + " : " + image.getScore());
        }
        System.out.println("%nPages with visually similar images: Score%n==");
        for (WebImage image : annotation.getVisuallySimilarImagesList()) {
          System.out.println(image.getUrl() + " : " + image.getScore());
        }
      }
    }
  }
}

Node.js

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vision 快速入門導覽課程」中的 Node.js 設定說明操作。詳情請參閱 Vision Node.js API 參考文件。

如要向 Vision 進行驗證，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機制」。


// Imports the Google Cloud client library
const vision = require('@google-cloud/vision');

// Creates a client
const client = new vision.ImageAnnotatorClient();

/**
 * TODO(developer): Uncomment the following line before running the sample.
 */
// const fileName = 'Local image file, e.g. /path/to/image.png';

// Detect similar images on the web to a local file
const [result] = await client.webDetection(fileName);
const webDetection = result.webDetection;
if (webDetection.fullMatchingImages.length) {
  console.log(
    `Full matches found: ${webDetection.fullMatchingImages.length}`
  );
  webDetection.fullMatchingImages.forEach(image => {
    console.log(`  URL: ${image.url}`);
    console.log(`  Score: ${image.score}`);
  });
}

if (webDetection.partialMatchingImages.length) {
  console.log(
    `Partial matches found: ${webDetection.partialMatchingImages.length}`
  );
  webDetection.partialMatchingImages.forEach(image => {
    console.log(`  URL: ${image.url}`);
    console.log(`  Score: ${image.score}`);
  });
}

if (webDetection.webEntities.length) {
  console.log(`Web entities found: ${webDetection.webEntities.length}`);
  webDetection.webEntities.forEach(webEntity => {
    console.log(`  Description: ${webEntity.description}`);
    console.log(`  Score: ${webEntity.score}`);
  });
}

if (webDetection.bestGuessLabels.length) {
  console.log(
    `Best guess labels found: ${webDetection.bestGuessLabels.length}`
  );
  webDetection.bestGuessLabels.forEach(label => {
    console.log(`  Label: ${label.label}`);
  });
}

Python

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vision 快速入門導覽課程」中的 Python 設定說明操作。詳情請參閱 Vision Python API 參考文件。

如要向 Vision 進行驗證，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機制」。

def detect_web(path):
    """Detects web annotations given an image."""
    from google.cloud import vision

    client = vision.ImageAnnotatorClient()

    with open(path, "rb") as image_file:
        content = image_file.read()

    image = vision.Image(content=content)

    response = client.web_detection(image=image)
    annotations = response.web_detection

    if annotations.best_guess_labels:
        for label in annotations.best_guess_labels:
            print(f"\nBest guess label: {label.label}")

    if annotations.pages_with_matching_images:
        print(
            "\n{} Pages with matching images found:".format(
                len(annotations.pages_with_matching_images)
            )
        )

        for page in annotations.pages_with_matching_images:
            print(f"\n\tPage url   : {page.url}")

            if page.full_matching_images:
                print(
                    "\t{} Full Matches found: ".format(len(page.full_matching_images))
                )

                for image in page.full_matching_images:
                    print(f"\t\tImage url  : {image.url}")

            if page.partial_matching_images:
                print(
                    "\t{} Partial Matches found: ".format(
                        len(page.partial_matching_images)
                    )
                )

                for image in page.partial_matching_images:
                    print(f"\t\tImage url  : {image.url}")

    if annotations.web_entities:
        print("\n{} Web entities found: ".format(len(annotations.web_entities)))

        for entity in annotations.web_entities:
            print(f"\n\tScore      : {entity.score}")
            print(f"\tDescription: {entity.description}")

    if annotations.visually_similar_images:
        print(
            "\n{} visually similar images found:\n".format(
                len(annotations.visually_similar_images)
            )
        )

        for image in annotations.visually_similar_images:
            print(f"\tImage url    : {image.url}")

    if response.error.message:
        raise Exception(
            "{}\nFor more info on error messages, check: "
            "https://cloud.google.com/apis/design/errors".format(response.error.message)
        )

其他語言

C#：請按照用戶端程式庫頁面上的 C# 設定操作說明完成相關步驟，然後參閱「.NET 適用的 Vision 參考文件」。

PHP：請按照用戶端程式庫頁面上的 PHP 設定操作說明完成相關步驟，然後參閱「PHP 適用的 Vision 參考文件」。

Ruby：請按照用戶端程式庫頁面上的 Ruby 設定操作說明完成相關步驟，然後參閱「Ruby 適用的 Vision 參考文件」。

使用遠端圖片偵測網路實體

您可以透過 Vision API，對位於 Cloud Storage 或網路上的遠端圖片檔案執行特徵偵測。如要傳送遠端檔案要求，請在要求內文中指定檔案的網址或 Cloud Storage URI。

REST

使用任何要求資料之前，請先修改下列項目的值：

CLOUD_STORAGE_IMAGE_URI：Cloud Storage bucket 中有效圖片檔案的路徑。您至少必須具備檔案的讀取權限。範例：
- ```
gs://cloud-samples-data/vision/web/carnaval.jpeg
```
RESULTS_INT：(選填) 要傳回的結果整數值。如果省略 "maxResults" 欄位及其值，API 會傳回預設值 (10 個結果)。這個欄位不適用於下列特徵類型：TEXT_DETECTION、DOCUMENT_TEXT_DETECTION 或 CROP_HINTS。
PROJECT_ID： Google Cloud 專案 ID。

HTTP 方法和網址：

POST https://vision.googleapis.com/v1/images:annotate

JSON 要求內文：

{
  "requests": [
    {
      "image": {
        "source": {
          "gcsImageUri": "CLOUD_STORAGE_IMAGE_URI"
        }
      },
      "features": [
        {
          "maxResults": RESULTS_INT,
          "type": "WEB_DETECTION"
        },
      ]
    }
  ]
}

如要傳送要求，請選擇以下其中一個選項：

curl

將要求主體儲存在名為 request.json 的檔案中，然後執行下列指令：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "x-goog-user-project: PROJECT_ID" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://vision.googleapis.com/v1/images:annotate"

PowerShell

注意：下列指令假設您已執行 gcloud init 或 gcloud auth login，透過使用者帳戶登入 gcloud CLI。您可以執行 gcloud auth list，查看目前使用的帳戶。

將要求主體儲存在名為 request.json 的檔案中，然後執行下列指令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://vision.googleapis.com/v1/images:annotate" | Select-Object -Expand Content

如果要求成功，伺服器會傳回 200 OK HTTP 狀態碼與 JSON 格式的回應。

回覆：

回應

{
  "responses": [
    {
      "webDetection": {
        "webEntities": [
          {
            "entityId": "/m/02p7_j8",
            "score": 1.44225,
            "description": "Carnival in Rio de Janeiro"
          },
          {
            "entityId": "/m/06gmr",
            "score": 1.2913725,
            "description": "Rio de Janeiro"
          },
          {
            "entityId": "/m/04cx88",
            "score": 0.78465,
            "description": "Brazilian Carnival"
          },
          {
            "entityId": "/m/09l9f",
            "score": 0.7166,
            "description": "Carnival"
          },
          ...
        ],
        "fullMatchingImages": [
          {
            "url": "https://1000lugaresparair.files.wordpress.com/2017/11/quinten-de-graaf-278848.jpg"
          },
          ...
        ],
        "partialMatchingImages": [
          {
            "url": "https://www.linnanneito.fi/wp-content/uploads/sambakarnevaali-riossa.jpg"
          },
          ...
        ],
        "pagesWithMatchingImages": [
          {
            "url": "https://www.intrepidtravel.com/us/brazil/rio-carnival-122873",
            "pageTitle": "\u003cb\u003eRio Carnival\u003c/b\u003e | Intrepid Travel US",
            "partialMatchingImages": [
              {
                "url": "https://www.intrepidtravel.com/sites/intrepid/files/styles/large/public/elements/product/hero/GGSR-Brazil-rio-carnival-ladies.jpg"
              },
              ...
        ],
        "visuallySimilarImages": [
          {
            "url": "https://pbs.twimg.com/media/DVoQOx6WkAIpHKF.jpg"
          },
          ...
        ],
        "bestGuessLabels": [
          {
            "label": "rio carnival",
            "languageCode": "en"
          }
        ]
      }
    }
  ]
}

Go

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vision 快速入門導覽課程」中的 Go 設定說明操作。詳情請參閱 Vision Go API 參考文件。

如要向 Vision 進行驗證，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機制」。


// detectWeb gets image properties from the Vision API for an image at the given file path.
func detectWebURI(w io.Writer, file string) error {
	ctx := context.Background()

	client, err := vision.NewImageAnnotatorClient(ctx)
	if err != nil {
		return err
	}

	image := vision.NewImageFromURI(file)
	web, err := client.DetectWeb(ctx, image, nil)
	if err != nil {
		return err
	}

	fmt.Fprintln(w, "Web properties:")
	if len(web.FullMatchingImages) != 0 {
		fmt.Fprintln(w, "\tFull image matches:")
		for _, full := range web.FullMatchingImages {
			fmt.Fprintf(w, "\t\t%s\n", full.Url)
		}
	}
	if len(web.PagesWithMatchingImages) != 0 {
		fmt.Fprintln(w, "\tPages with this image:")
		for _, page := range web.PagesWithMatchingImages {
			fmt.Fprintf(w, "\t\t%s\n", page.Url)
		}
	}
	if len(web.WebEntities) != 0 {
		fmt.Fprintln(w, "\tEntities:")
		fmt.Fprintln(w, "\t\tEntity\t\tScore\tDescription")
		for _, entity := range web.WebEntities {
			fmt.Fprintf(w, "\t\t%-14s\t%-2.4f\t%s\n", entity.EntityId, entity.Score, entity.Description)
		}
	}
	if len(web.BestGuessLabels) != 0 {
		fmt.Fprintln(w, "\tBest guess labels:")
		for _, label := range web.BestGuessLabels {
			fmt.Fprintf(w, "\t\t%s\n", label.Label)
		}
	}

	return nil
}

Java

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vision 快速入門導覽課程」中的 Java 設定說明操作。詳情請參閱 Vision Java API 參考文件。

如要向 Vision 進行驗證，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機制」。


import com.google.cloud.vision.v1.AnnotateImageRequest;
import com.google.cloud.vision.v1.AnnotateImageResponse;
import com.google.cloud.vision.v1.BatchAnnotateImagesResponse;
import com.google.cloud.vision.v1.Feature;
import com.google.cloud.vision.v1.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.cloud.vision.v1.ImageSource;
import com.google.cloud.vision.v1.WebDetection;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

public class DetectWebDetectionsGcs {

  public static void detectWebDetectionsGcs() throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String filePath = "gs://your-gcs-bucket/path/to/image/file.jpg";
    detectWebDetectionsGcs(filePath);
  }

  // Detects whether the remote image on Google Cloud Storage has features you would want to
  // moderate.
  public static void detectWebDetectionsGcs(String gcsPath) throws IOException {
    List<AnnotateImageRequest> requests = new ArrayList<>();

    ImageSource imgSource = ImageSource.newBuilder().setGcsImageUri(gcsPath).build();
    Image img = Image.newBuilder().setSource(imgSource).build();
    Feature feat = Feature.newBuilder().setType(Feature.Type.WEB_DETECTION).build();
    AnnotateImageRequest request =
        AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
    requests.add(request);

    // 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 (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
      BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
      List<AnnotateImageResponse> responses = response.getResponsesList();

      for (AnnotateImageResponse res : responses) {
        if (res.hasError()) {
          System.out.format("Error: %s%n", res.getError().getMessage());
          return;
        }

        // Search the web for usages of the image. You could use these signals later
        // for user input moderation or linking external references.
        // For a full list of available annotations, see http://g.co/cloud/vision/docs
        WebDetection annotation = res.getWebDetection();
        System.out.println("Entity:Id:Score");
        System.out.println("===============");
        for (WebDetection.WebEntity entity : annotation.getWebEntitiesList()) {
          System.out.println(
              entity.getDescription() + " : " + entity.getEntityId() + " : " + entity.getScore());
        }
        for (WebDetection.WebLabel label : annotation.getBestGuessLabelsList()) {
          System.out.format("%nBest guess label: %s", label.getLabel());
        }
        System.out.println("%nPages with matching images: Score%n==");
        for (WebDetection.WebPage page : annotation.getPagesWithMatchingImagesList()) {
          System.out.println(page.getUrl() + " : " + page.getScore());
        }
        System.out.println("%nPages with partially matching images: Score%n==");
        for (WebDetection.WebImage image : annotation.getPartialMatchingImagesList()) {
          System.out.println(image.getUrl() + " : " + image.getScore());
        }
        System.out.println("%nPages with fully matching images: Score%n==");
        for (WebDetection.WebImage image : annotation.getFullMatchingImagesList()) {
          System.out.println(image.getUrl() + " : " + image.getScore());
        }
        System.out.println("%nPages with visually similar images: Score%n==");
        for (WebDetection.WebImage image : annotation.getVisuallySimilarImagesList()) {
          System.out.println(image.getUrl() + " : " + image.getScore());
        }
      }
    }
  }
}

Node.js

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vision 快速入門導覽課程」中的 Node.js 設定說明操作。詳情請參閱 Vision Node.js API 參考文件。

如要向 Vision 進行驗證，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機制」。


// Imports the Google Cloud client libraries
const vision = require('@google-cloud/vision');

// Creates a client
const client = new vision.ImageAnnotatorClient();

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const bucketName = 'Bucket where the file resides, e.g. my-bucket';
// const fileName = 'Path to file within bucket, e.g. path/to/image.png';

// Detect similar images on the web to a remote file
const [result] = await client.webDetection(`gs://${bucketName}/${fileName}`);
const webDetection = result.webDetection;
if (webDetection.fullMatchingImages.length) {
  console.log(
    `Full matches found: ${webDetection.fullMatchingImages.length}`
  );
  webDetection.fullMatchingImages.forEach(image => {
    console.log(`  URL: ${image.url}`);
    console.log(`  Score: ${image.score}`);
  });
}

if (webDetection.partialMatchingImages.length) {
  console.log(
    `Partial matches found: ${webDetection.partialMatchingImages.length}`
  );
  webDetection.partialMatchingImages.forEach(image => {
    console.log(`  URL: ${image.url}`);
    console.log(`  Score: ${image.score}`);
  });
}

if (webDetection.webEntities.length) {
  console.log(`Web entities found: ${webDetection.webEntities.length}`);
  webDetection.webEntities.forEach(webEntity => {
    console.log(`  Description: ${webEntity.description}`);
    console.log(`  Score: ${webEntity.score}`);
  });
}

if (webDetection.bestGuessLabels.length) {
  console.log(
    `Best guess labels found: ${webDetection.bestGuessLabels.length}`
  );
  webDetection.bestGuessLabels.forEach(label => {
    console.log(`  Label: ${label.label}`);
  });
}

Python

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vision 快速入門導覽課程」中的 Python 設定說明操作。詳情請參閱 Vision Python API 參考文件。

如要向 Vision 進行驗證，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機制」。

def detect_web_uri(uri):
    """Detects web annotations in the file located in Google Cloud Storage."""
    from google.cloud import vision

    client = vision.ImageAnnotatorClient()
    image = vision.Image()
    image.source.image_uri = uri

    response = client.web_detection(image=image)
    annotations = response.web_detection

    if annotations.best_guess_labels:
        for label in annotations.best_guess_labels:
            print(f"\nBest guess label: {label.label}")

    if annotations.pages_with_matching_images:
        print(
            "\n{} Pages with matching images found:".format(
                len(annotations.pages_with_matching_images)
            )
        )

        for page in annotations.pages_with_matching_images:
            print(f"\n\tPage url   : {page.url}")

            if page.full_matching_images:
                print(
                    "\t{} Full Matches found: ".format(len(page.full_matching_images))
                )

                for image in page.full_matching_images:
                    print(f"\t\tImage url  : {image.url}")

            if page.partial_matching_images:
                print(
                    "\t{} Partial Matches found: ".format(
                        len(page.partial_matching_images)
                    )
                )

                for image in page.partial_matching_images:
                    print(f"\t\tImage url  : {image.url}")

    if annotations.web_entities:
        print("\n{} Web entities found: ".format(len(annotations.web_entities)))

        for entity in annotations.web_entities:
            print(f"\n\tScore      : {entity.score}")
            print(f"\tDescription: {entity.description}")

    if annotations.visually_similar_images:
        print(
            "\n{} visually similar images found:\n".format(
                len(annotations.visually_similar_images)
            )
        )

        for image in annotations.visually_similar_images:
            print(f"\tImage url    : {image.url}")

    if response.error.message:
        raise Exception(
            "{}\nFor more info on error messages, check: "
            "https://cloud.google.com/apis/design/errors".format(response.error.message)
        )

gcloud

如要執行網頁偵測，請使用 gcloud ml vision detect-web 指令，如下列範例所示：

gcloud ml vision detect-web gs://cloud-samples-data/vision/web/carnaval.jpeg

其他語言

C#：請按照用戶端程式庫頁面上的 C# 設定操作說明完成相關步驟，然後參閱「.NET 適用的 Vision 參考文件」。

PHP：請按照用戶端程式庫頁面上的 PHP 設定操作說明完成相關步驟，然後參閱「PHP 適用的 Vision 參考文件」。

Ruby：請按照用戶端程式庫頁面上的 Ruby 設定操作說明完成相關步驟，然後參閱「Ruby 適用的 Vision 參考文件」。

試試看

請試試下方的網路實體偵測功能。你可以使用已指定的圖片 (gs://cloud-samples-data/vision/web/carnaval.jpeg)，也可以指定自己的圖片。選取「Execute」傳送要求。

Carnaval 圖片 — *圖片來源*： Quinten de Graaf (Unsplash)。

要求主體：

{
  "requests": [
    {
      "features": [
        {
          "type": "WEB_DETECTION"
        }
      ],
      "image": {
        "source": {
          "gcsImageUri": "gs://cloud-samples-data/vision/web/carnaval.jpeg"
        }
      }
    }
  ]
}

偵測網路實體和頁面 透過集合功能整理內容 你可以依據偏好儲存及分類內容。

網路偵測要求

設定 Google Cloud 專案和驗證

使用本機圖片偵測網路實體

REST

curl

PowerShell

回應

Go

Java

Node.js

Python

其他語言

使用遠端圖片偵測網路實體

REST

curl

PowerShell

回應

Go

Java

Node.js

Python

gcloud

其他語言

試試看

偵測網路實體和頁面