检测 Web 实体和页面

网络检测功能可检测对图片的网络引用。

注意：我们最近在 Web 检测功能中新增了一些功能或字段。如需了解详情，请参阅版本说明。

注意：Vision API 现在支持将离线异步批量图片注释用于所有特征。此异步请求支持多达 2000 个图片文件，并返回存储在您的 Google Cloud Storage 存储分区中的响应 JSON 文件。如需详细了解此功能，请参阅离线批量图片注释。

图片来源：Quinten de Graaf (Unsplash)。

类别	响应
Web 实体	entityId：/m/02p7_j8，得分：1.3225499，说明：里约热内卢狂欢节 entityId：/m/06gmr，得分：1.1684971，说明：里约热内卢 entityId：/m/04cx88，得分：1.05945，说明：巴西狂欢节 ...
完全匹配的图片	网址：https://1000lugaresparair.files.wordpress.com/2017/11/quinten-de-graaf-278848.jpg 网址：https://freewalkingtourrotterdam.com/wp-content/uploads/2017/07/quinten-de-graaf-278848.jpg ...
部分匹配的图片	网址：https://www.linnanneito.fi/wp-content/uploads/sambakarnevaali-riossa.jpg 网址：https://static.airhelp.com/wp-content/uploads/2019/02/26105557/two-women-in-carnival-costumes.jpg ...
具有匹配图片的页面	网址：https://travelnoire.com/best-carnival-celebrations-around-the-world/， pageTitle：Best \u003cb\u003eCarnival\u003c/b\u003e Celebrations Around The World - Travel Noire， fullMatchingImages：[{网址：https://travelnoire.com/wp-content/uploads/2019/02/quinten-de-graaf-278848-unsplash.jpg}] 网址：https://bespokebrazil.com/rio-carnival-2019/， pageTitle：Visit \u003cb\u003eRio Carnival 2019\u003c/b\u003e with the Brazil Specialists - Bespoke Brazil， partialMatchingImages：[{网址：https://bespoke-brazil-2018-bespokebrazil.netdna-ssl.com/wp-content/uploads/2019/01/Carnival-1.jpg}] ...
外观类似的图片	网址：https://www.brazilbookers.com/_images/photos/rio-carnival-images/rio-carnival-2016-carnival-date.jpg 网址：https://image.redbull.com/rbcom/010/2017-02-08/1331843859949_3/0100/0/1/watch-rio-carnival-2017-live-on-red-bull-tv.jpg ...
最佳猜测标签	2019 年里约狂欢节舞者

Web 检测请求

设置您的 GCP 项目和身份验证

如果您尚未创建 Google Cloud Platform (GCP) 项目和服务帐号凭据，请立即创建。 展开本部分可查看相关说明。

1. 登录您的 Google Cloud 帐号。如果您是 Google Cloud 新手，请创建一个帐号来评估我们的产品在实际场景中的表现。新客户还可获享 $300 赠金，用于运行、测试和部署工作负载。

2. 设置控制台项目。

   设置项目

   点击即可执行以下操作：

   • 创建或选择项目。
   • 为该项目启用 Vision API。
   • 创建服务帐号。
   • 下载 JSON 格式的私钥。

   您可以随时在控制台中查看和管理这些资源。

3. 将环境变量 GOOGLE_APPLICATION_CREDENTIALS 设置为包含您的服务帐号密钥的 JSON 文件的路径。 此变量仅适用于当前的 shell 会话，因此，如果您打开新的会话，请重新设置该变量。

   示例：Linux 或 macOS

   export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   将 KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

   例如：

   export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"

   示例：Windows

   对于 PowerShell：

   $env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   将 KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

   例如：

   $env:GOOGLE_APPLICATION_CREDENTIALS="C:\Users\username\Downloads\service-account-file.json"

   对于命令提示符：

   set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

   将 KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

4. 安装并初始化 Google Cloud CLI。

5. 设置控制台项目。

   设置项目

   点击即可执行以下操作：

   • 创建或选择项目。
   • 为该项目启用 Vision API。
   • 创建服务帐号。
   • 下载 JSON 格式的私钥。

   您可以随时在控制台中查看和管理这些资源。

6. 将环境变量 GOOGLE_APPLICATION_CREDENTIALS 设置为包含您的服务帐号密钥的 JSON 文件的路径。 此变量仅适用于当前的 shell 会话，因此，如果您打开新的会话，请重新设置该变量。

   示例：Linux 或 macOS

   export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   将 KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

   例如：

   export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"

   示例：Windows

   对于 PowerShell：

   $env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   将 KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

   例如：

   $env:GOOGLE_APPLICATION_CREDENTIALS="C:\Users\username\Downloads\service-account-file.json"

   对于命令提示符：

   set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

   将 KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

7. 安装并初始化 Google Cloud CLI。

使用本地图片检测 Web 实体

Vision API 可以将本地图片文件的内容作为 base64 编码的字符串在请求正文中发送，从而对此图片文件执行特征检测。

REST 和命令行

在使用任何请求数据之前，请先进行以下替换：

• BASE64_ENCODED_IMAGE：二进制图片数据的 base64 表示（ASCII 字符串）。此字符串应类似于以下字符串：
  • /9j/4QAYRXhpZgAA...9tAVx/zDQDlGxn//2Q==
  如需了解详情，请参阅 base64 编码主题。
• RESULTS_INT：（可选）要返回的结果的整数值。如果您省略 "maxResults" 字段及其值，则 API 会默认返回 10 个结果。此字段不适用于以下功能类型：TEXT_DETECTION、DOCUMENT_TEXT_DETECTION 或 CROP_HINTS。

HTTP 方法和网址：

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

请求 JSON 正文：

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

如需发送请求，请选择以下方式之一：

curl

注意：请确保已将 GOOGLE_APPLICATION_CREDENTIALS 环境变量设置为服务帐号私钥文件的路径。

将请求正文保存在名为 request.json 的文件中，然后执行以下命令：

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

PowerShell

注意：请确保已将 GOOGLE_APPLICATION_CREDENTIALS 环境变量设置为服务帐号私钥文件的路径。

将请求正文保存在名为 request.json 的文件中，然后执行以下命令：

$cred = gcloud auth application-default print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

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

如果请求成功，服务器将返回一个 200 OK HTTP 状态代码以及 JSON 格式的响应。

响应：

Note: Zero coordinate values omitted. When the API detects a coordinate ("x" or "y") value of 0, that coordinate is omitted in the JSON response. Thus, a response with a bounding poly around the entire image would be
[{},{"x": 100},{"x": 100,"y": 100},{"y": 100}] for an image that is 100px by 100px. For more information, see the API Reference documentation.

响应

    {
  "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

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Go 设置说明进行操作。如需了解详情，请参阅 Vision Go API 参考文档。

在 GitHub 上查看 反馈

// 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

在试用此示例之前，请按照Vision API 快速入门：使用客户端库中的 Java 设置说明进行操作。如需了解详情，请参阅 Vision API Java API 参考文档。

注意：对于 Java Spring 框架用户，Spring Cloud GCP 提供了一种身份验证设置和客户端对象的自动配置方法来使用 Vision API。

在 GitHub 上查看 反馈

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

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Node.js 设置说明进行操作。如需了解详情，请参阅 Vision Node.js API 参考文档。

在 GitHub 上查看 反馈

// 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

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Python 设置说明进行操作。如需了解详情，请参阅 Vision Python API 参考文档。

在 GitHub 上查看 反馈

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

    with io.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('\nBest guess label: {}'.format(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('\n\tPage url   : {}'.format(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('\t\tImage url  : {}'.format(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('\t\tImage url  : {}'.format(image.url))

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

        for entity in annotations.web_entities:
            print('\n\tScore      : {}'.format(entity.score))
            print(u'\tDescription: {}'.format(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('\tImage url    : {}'.format(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))

其他语言

C#： 请按照客户端库页面上的 C# 设置说明操作，然后访问 .NET 版 Vision 参考文档。

PHP： 请按照客户端库页面上的 PHP 设置说明操作，然后访问 PHP 版 Vision 参考文档。

Ruby 版： 请按照客户端库页面上的 Ruby 设置说明操作，然后访问 Ruby 版 Vision 参考文档。

使用远程图片检测 Web 实体

为方便起见，Vision API 可以直接对位于 Google Cloud Storage 或网络中的图片文件执行特征检测，无需在请求正文中发送图片文件的内容。

警告：从 HTTP/HTTPS 网址提取图片时，Google 无法保证请求会完成。如果指定的主机拒绝请求（例如，由于请求限制或 DOS 攻击防范），或者如果 Google 为了防止滥用而限制对网站的请求，则您的请求可能会失败。对于生产应用，您不应依赖外部托管的图片。

REST 和命令行

在使用任何请求数据之前，请先进行以下替换：

• CLOUD_STORAGE_IMAGE_URI：Cloud Storage 存储分区中有效图片文件的路径。您必须至少拥有该文件的读取权限。 示例：

  • gs://cloud-samples-data/vision/web/carnaval.jpeg

• RESULTS_INT：（可选）要返回的结果的整数值。如果您省略 "maxResults" 字段及其值，则 API 会默认返回 10 个结果。此字段不适用于以下功能类型：TEXT_DETECTION、DOCUMENT_TEXT_DETECTION 或 CROP_HINTS。

HTTP 方法和网址：

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

请求 JSON 正文：

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

如需发送请求，请选择以下方式之一：

curl

注意：请确保已将 GOOGLE_APPLICATION_CREDENTIALS 环境变量设置为服务帐号私钥文件的路径。

将请求正文保存在名为 request.json 的文件中，然后执行以下命令：

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

PowerShell

注意：请确保已将 GOOGLE_APPLICATION_CREDENTIALS 环境变量设置为服务帐号私钥文件的路径。

将请求正文保存在名为 request.json 的文件中，然后执行以下命令：

$cred = gcloud auth application-default print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

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

如果请求成功，服务器将返回一个 200 OK HTTP 状态代码以及 JSON 格式的响应。

响应：

Note: Zero coordinate values omitted. When the API detects a coordinate ("x" or "y") value of 0, that coordinate is omitted in the JSON response. Thus, a response with a bounding poly around the entire image would be
[{},{"x": 100},{"x": 100,"y": 100},{"y": 100}] for an image that is 100px by 100px. For more information, see the API Reference documentation.

响应

    {
  "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

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Go 设置说明进行操作。如需了解详情，请参阅 Vision Go API 参考文档。

在 GitHub 上查看 反馈

// 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

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Java 设置说明进行操作。如需了解详情，请参阅 Vision Java API 参考文档。

在 GitHub 上查看 反馈

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

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Node.js 设置说明进行操作。如需了解详情，请参阅 Vision Node.js API 参考文档。

在 GitHub 上查看 反馈

// 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

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Python 设置说明进行操作。如需了解详情，请参阅 Vision Python API 参考文档。

在 GitHub 上查看 反馈

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('\nBest guess label: {}'.format(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('\n\tPage url   : {}'.format(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('\t\tImage url  : {}'.format(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('\t\tImage url  : {}'.format(image.url))

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

        for entity in annotations.web_entities:
            print('\n\tScore      : {}'.format(entity.score))
            print(u'\tDescription: {}'.format(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('\tImage url    : {}'.format(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

如需执行 Web 检测，请使用 gcloud ml vision detect-web 命令，如以下示例所示：

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

其他语言

C#： 请按照客户端库页面上的 C# 设置说明操作，然后访问 .NET 版 Vision 参考文档。

PHP： 请按照客户端库页面上的 PHP 设置说明操作，然后访问 PHP 版 Vision 参考文档。

Ruby 版： 请按照客户端库页面上的 Ruby 设置说明操作，然后访问 Ruby 版 Vision 参考文档。

在本地图片中使用地理元数据

Vision API 可以访问图片文件中的地理标记元数据，以返回更多相关的网络实体和页面。如需允许使用地理标记，请在请求中指定 'includeGeoResults': true。

警告：从 HTTP/HTTPS 网址提取图片时，Google 无法保证请求会完成。如果指定的主机拒绝请求（例如，由于请求限制或 DOS 攻击防范），或者如果 Google 为了防止滥用而限制对网站的请求，则您的请求可能会失败。对于生产应用，您不应依赖外部托管的图片。

REST 和命令行

在使用任何请求数据之前，请先进行以下替换：

• CLOUD_STORAGE_IMAGE_URI：Cloud Storage 存储分区中有效图片文件的路径。您必须至少拥有该文件的读取权限。 示例：

  • gs://cloud-samples-data/vision/web/carnaval.jpeg

HTTP 方法和网址：

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

请求 JSON 正文：

{
  "requests": [
    {
      "image": {
        "source": {
          "gcsImageUri": "CLOUD_STORAGE_IMAGE_URI"
        }
      },
      "features": [
        {
          "type": "WEB_DETECTION"
        }
      ],
      "imageContext": {
        "webDetectionParams": {
          "includeGeoResults": true
          }
        }
    }
  ]
}

如需发送请求，请选择以下方式之一：

curl

注意：请确保已将 GOOGLE_APPLICATION_CREDENTIALS 环境变量设置为服务帐号私钥文件的路径。

将请求正文保存在名为 request.json 的文件中，然后执行以下命令：

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

PowerShell

注意：请确保已将 GOOGLE_APPLICATION_CREDENTIALS 环境变量设置为服务帐号私钥文件的路径。

将请求正文保存在名为 request.json 的文件中，然后执行以下命令：

$cred = gcloud auth application-default print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

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

如果请求成功，服务器将返回一个 200 OK HTTP 状态代码以及 JSON 格式的响应。

响应：

Note: Zero coordinate values omitted. When the API detects a coordinate ("x" or "y") value of 0, that coordinate is omitted in the JSON response. Thus, a response with a bounding poly around the entire image would be
[{},{"x": 100},{"x": 100,"y": 100},{"y": 100}] for an image that is 100px by 100px. For more information, see the API Reference documentation.

响应

    {
  "responses": [
    {
      "webDetection": {
        "webEntities": [
          {
            "entityId": "/m/02p7_j8",
            "score": 1.3293,
            "description": "Carnival in Rio de Janeiro"
          },
          {
            "entityId": "/m/06gmr",
            "score": 1.1842875,
            "description": "Rio de Janeiro"
          },
        ...
        ],
        "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://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"
              }
            ]
          },
        ...
        ],
        "visuallySimilarImages": [
          {
            "url": "https://www.brazilbookers.com/_images/photos/rio-carnival-images/rio-carnival-2016-carnival-date.jpg"
          },
        ...
        ],
        "bestGuessLabels": [
          {
            "label": "rio carnival 2019 dancers",
            "languageCode": "en"
          }
        ]
      }
    }
  ]
}

Go

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Go 设置说明进行操作。如需了解详情，请参阅 Vision Go API 参考文档。

在 GitHub 上查看 反馈

// detectWebGeo detects geographic metadata from the Vision API for an image at the given file path.
func detectWebGeo(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
	}
	imageContext := &visionpb.ImageContext{
		WebDetectionParams: &visionpb.WebDetectionParams{
			IncludeGeoResults: true,
		},
	}
	web, err := client.DetectWeb(ctx, image, imageContext)
	if err != nil {
		return err
	}

	if len(web.WebEntities) != 0 {
		fmt.Fprintln(w, "Entities:")
		fmt.Fprintln(w, "\tEntity\t\tScore\tDescription")
		for _, entity := range web.WebEntities {
			fmt.Fprintf(w, "\t%-14s\t%-2.4f\t%s\n", entity.EntityId, entity.Score, entity.Description)
		}
	}

	return nil
}

Java

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Java 设置说明进行操作。如需了解详情，请参阅 Vision Java API 参考文档。

在 GitHub 上查看 反馈

import com.google.cloud.vision.v1.AnnotateImageRequest;
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.ImageContext;
import com.google.cloud.vision.v1.WebDetectionParams;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.Arrays;

public class DetectWebEntitiesIncludeGeoResults {

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

  // Find web entities given a local image.
  public static void detectWebEntitiesIncludeGeoResults(String filePath) 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 (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
      // Read in the local image
      ByteString contents = ByteString.readFrom(new FileInputStream(filePath));

      // Build the image
      Image image = Image.newBuilder().setContent(contents).build();

      // Enable `IncludeGeoResults`
      WebDetectionParams webDetectionParams =
          WebDetectionParams.newBuilder().setIncludeGeoResults(true).build();

      // Set the parameters for the image
      ImageContext imageContext =
          ImageContext.newBuilder().setWebDetectionParams(webDetectionParams).build();

      // Create the request with the image, imageContext, and the specified feature: web detection
      AnnotateImageRequest request =
          AnnotateImageRequest.newBuilder()
              .addFeatures(Feature.newBuilder().setType(Type.WEB_DETECTION))
              .setImage(image)
              .setImageContext(imageContext)
              .build();

      // Perform the request
      BatchAnnotateImagesResponse response = client.batchAnnotateImages(Arrays.asList(request));

      // Display the results
      response.getResponsesList().stream()
          .forEach(
              r ->
                  r.getWebDetection().getWebEntitiesList().stream()
                      .forEach(
                          entity -> {
                            System.out.format("Description: %s%n", entity.getDescription());
                            System.out.format("Score: %f%n", entity.getScore());
                          }));
    }
  }
}

Node.js

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Node.js 设置说明进行操作。如需了解详情，请参阅 Vision Node.js API 参考文档。

在 GitHub 上查看 反馈

// 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';

const request = {
  image: {
    source: {
      filename: fileName,
    },
  },
  imageContext: {
    webDetectionParams: {
      includeGeoResults: true,
    },
  },
};

// Detect similar images on the web to a local file
const [result] = await client.webDetection(request);
const webDetection = result.webDetection;
webDetection.webEntities.forEach(entity => {
  console.log(`Score: ${entity.score}`);
  console.log(`Description: ${entity.description}`);
});

Python

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Python 设置说明进行操作。如需了解详情，请参阅 Vision Python API 参考文档。

在 GitHub 上查看 反馈

def web_entities_include_geo_results(path):
    """Detects web annotations given an image, using the geotag metadata
    in the image to detect web entities."""
    from google.cloud import vision
    import io
    client = vision.ImageAnnotatorClient()

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

    image = vision.Image(content=content)

    web_detection_params = vision.WebDetectionParams(
        include_geo_results=True)
    image_context = vision.ImageContext(
        web_detection_params=web_detection_params)

    response = client.web_detection(image=image, image_context=image_context)

    for entity in response.web_detection.web_entities:
        print('\n\tScore      : {}'.format(entity.score))
        print(u'\tDescription: {}'.format(entity.description))

    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

如需执行 Web 检测，请使用 gcloud ml vision detect-web 命令，如以下示例所示：

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

其他语言

C#： 请按照客户端库页面上的 C# 设置说明操作，然后访问 .NET 版 Vision 参考文档。

PHP： 请按照客户端库页面上的 PHP 设置说明操作，然后访问 PHP 版 Vision 参考文档。

Ruby 版： 请按照客户端库页面上的 Ruby 设置说明操作，然后访问 Ruby 版 Vision 参考文档。

在远程图片中使用地理元数据

Go

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Go 设置说明进行操作。如需了解详情，请参阅 Vision Go API 参考文档。

在 GitHub 上查看 反馈

// detectWebGeo detects geographic metadata from the Vision API for an image at the given file path.
func detectWebGeoURI(w io.Writer, file string) error {
	ctx := context.Background()

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

	image := vision.NewImageFromURI(file)
	imageContext := &visionpb.ImageContext{
		WebDetectionParams: &visionpb.WebDetectionParams{
			IncludeGeoResults: true,
		},
	}
	web, err := client.DetectWeb(ctx, image, imageContext)
	if err != nil {
		return err
	}

	if len(web.WebEntities) != 0 {
		fmt.Fprintln(w, "Entities:")
		fmt.Fprintln(w, "\tEntity\t\tScore\tDescription")
		for _, entity := range web.WebEntities {
			fmt.Fprintf(w, "\t%-14s\t%-2.4f\t%s\n", entity.EntityId, entity.Score, entity.Description)
		}
	}

	return nil
}

Java

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Java 设置说明进行操作。如需了解详情，请参阅 Vision Java API 参考文档。

在 GitHub 上查看 反馈

import com.google.cloud.vision.v1.AnnotateImageRequest;
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.ImageContext;
import com.google.cloud.vision.v1.ImageSource;
import com.google.cloud.vision.v1.WebDetectionParams;
import java.io.IOException;
import java.util.Arrays;

public class DetectWebEntitiesIncludeGeoResultsGcs {

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

  // Find web entities given the remote image on Google Cloud Storage.
  public static void detectWebEntitiesIncludeGeoResultsGcs(String gcsPath) 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 (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
      // Set the image source to the given gs uri
      ImageSource imageSource = ImageSource.newBuilder().setGcsImageUri(gcsPath).build();
      // Build the image
      Image image = Image.newBuilder().setSource(imageSource).build();

      // Enable `IncludeGeoResults`
      WebDetectionParams webDetectionParams =
          WebDetectionParams.newBuilder().setIncludeGeoResults(true).build();

      // Set the parameters for the image
      ImageContext imageContext =
          ImageContext.newBuilder().setWebDetectionParams(webDetectionParams).build();

      // Create the request with the image, imageContext, and the specified feature: web detection
      AnnotateImageRequest request =
          AnnotateImageRequest.newBuilder()
              .addFeatures(Feature.newBuilder().setType(Feature.Type.WEB_DETECTION))
              .setImage(image)
              .setImageContext(imageContext)
              .build();

      // Perform the request
      BatchAnnotateImagesResponse response = client.batchAnnotateImages(Arrays.asList(request));

      // Display the results
      response.getResponsesList().stream()
          .forEach(
              r ->
                  r.getWebDetection().getWebEntitiesList().stream()
                      .forEach(
                          entity -> {
                            System.out.format("Description: %s%n", entity.getDescription());
                            System.out.format("Score: %f%n", entity.getScore());
                          }));
    }
  }
}

Node.js

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Node.js 设置说明进行操作。如需了解详情，请参阅 Vision Node.js API 参考文档。

在 GitHub 上查看 反馈

// 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 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';

const request = {
  image: {
    source: {
      imageUri: `gs://${bucketName}/${fileName}`,
    },
  },
  imageContext: {
    webDetectionParams: {
      includeGeoResults: true,
    },
  },
};

// Detect similar images on the web to a remote file
const [result] = await client.webDetection(request);
const webDetection = result.webDetection;
webDetection.webEntities.forEach(entity => {
  console.log(`Score: ${entity.score}`);
  console.log(`Description: ${entity.description}`);
});

Python

试用此示例之前，请按照《Vision 快速入门：使用客户端库》中的 Python 设置说明进行操作。如需了解详情，请参阅 Vision Python API 参考文档。

在 GitHub 上查看 反馈

def web_entities_include_geo_results_uri(uri):
    """Detects web annotations given an image in the file located in
    Google Cloud Storage., using the geotag metadata in the image to
    detect web entities."""
    from google.cloud import vision
    client = vision.ImageAnnotatorClient()

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

    web_detection_params = vision.WebDetectionParams(
        include_geo_results=True)
    image_context = vision.ImageContext(
        web_detection_params=web_detection_params)

    response = client.web_detection(image=image, image_context=image_context)

    for entity in response.web_detection.web_entities:
        print('\n\tScore      : {}'.format(entity.score))
        print(u'\tDescription: {}'.format(entity.description))

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

其他语言

C#： 请按照客户端库页面上的 C# 设置说明操作，然后访问 .NET 版 Vision 参考文档。

PHP： 请按照客户端库页面上的 PHP 设置说明操作，然后访问 PHP 版 Vision 参考文档。

Ruby 版： 请按照客户端库页面上的 Ruby 设置说明操作，然后访问 Ruby 版 Vision 参考文档。

试试看

在下面尝试检测 Web 实体。您可以使用已指定的图片 (gs://cloud-samples-data/vision/web/carnaval.jpeg) 或指定您自己的图片。选择执行即可发送请求。

在 includeGeoResults 设置为 false 的情况下，尝试重复发送请求。

图片来源：Quinten de Graaf (Unsplash)。

请求正文：

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