检测图片属性

图片属性功能可检测图片的一般属性，如主色。

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 2,000 个图片文件，并返回存储在您的 Cloud Storage 存储桶中的响应 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：Unsplash 用户 Jeremy Bishop。

检测到主色：

图片属性检测请求

设置您的 Google Cloud 项目和身份验证

如果您尚未创建 Google Cloud 项目，请立即创建。展开本部分可查看相关说明。

Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

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 (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

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

Install the Google Cloud CLI.

如果您使用的是外部身份提供方 (IdP)，则必须先使用联合身份登录 gcloud CLI。

如需初始化 gcloud CLI，请运行以下命令：

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 (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

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

Install the Google Cloud CLI.

如果您使用的是外部身份提供方 (IdP)，则必须先使用联合身份登录 gcloud CLI。

如需初始化 gcloud CLI，请运行以下命令：

gcloud init

检测本地图片中的图片属性

您可以使用 Vision API 对本地图片文件执行特征检测。

对于 REST 请求，请将图片文件的内容作为 base64 编码的字符串在请求正文中发送。

对于 gcloud 和客户端库请求，请在请求中指定本地图片的路径。

ColorInfo 字段不包含用于解释 RGB 值的绝对颜色空间（例如 sRGB、Adobe RGB、DCI-P3、BT.2020 等等）的相关信息。默认情况下，应用应采用 sRGB 颜色空间。

REST

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。
• PROJECT_ID：您的 Google Cloud 项目 ID。

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": "IMAGE_PROPERTIES"
        },
      ]
    }
  ]
}

如需发送请求，请选择以下方式之一：

curl

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

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 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：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

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 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 100 pixels by 100 pixels. For more information, see the API Reference documentation.

响应

{
  "responses": [
    {
      "imagePropertiesAnnotation": {
        "dominantColors": {
          "colors": [
            {
              "color": {
                "red": 243,
                "green": 177,
                "blue": 133
              },
              "score": 0.18074834,
              "pixelFraction": 0.013533333
            },
            {
              "color": {
                "red": 204,
                "green": 205,
                "blue": 213
              },
              "score": 0.092455424,
              "pixelFraction": 0.19266666
            },
            {
              "color": {
                "red": 114,
                "green": 77,
                "blue": 64
              },
              "score": 0.090447456,
              "pixelFraction": 0.034133334
            },
            {
              "color": {
                "red": 224,
                "green": 57,
                "blue": 64
              },
              "score": 0.010952942,
              "pixelFraction": 0.014266667
            },
            {
              "color": {
                "red": 248,
                "green": 125,
                "blue": 130
              },
              "score": 0.006984347,
              "pixelFraction": 0.0057333335
            },
            {
              "color": {
                "red": 150,
                "green": 107,
                "blue": 92
              },
              "score": 0.081589326,
              "pixelFraction": 0.019666666
            },
            {
              "color": {
                "red": 233,
                "green": 185,
                "blue": 158
              },
              "score": 0.08035342,
              "pixelFraction": 0.0122
            },
            {
              "color": {
                "red": 221,
                "green": 221,
                "blue": 226
              },
              "score": 0.045200635,
              "pixelFraction": 0.202
            },
            {
              "color": {
                "red": 105,
                "green": 77,
                "blue": 75
              },
              "score": 0.030223774,
              "pixelFraction": 0.013866667
            },
            {
              "color": {
                "red": 189,
                "green": 145,
                "blue": 123
              },
              "score": 0.028689377,
              "pixelFraction": 0.0069333334
            }
          ]
        }
      },
      "cropHintsAnnotation": {
        "cropHints": [
          {
            "boundingPoly": {
              "vertices": [
                {},
                {
                  "x": 2549
                },
                {
                  "x": 2549,
                  "y": 1699
                },
                {
                  "y": 1699
                }
              ]
            },
            "confidence": 0.79999995,
            "importanceFraction": 1
          }
        ]
      }
    }
  ]
}

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。

如需向 Vision 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。

// detectProperties gets image properties from the Vision API for an image at the given file path.
func detectProperties(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
	}
	props, err := client.DetectImageProperties(ctx, image, nil)
	if err != nil {
		return err
	}

	fmt.Fprintln(w, "Dominant colors:")
	for _, quantized := range props.DominantColors.Colors {
		color := quantized.Color
		r := int(color.Red) & 0xff
		g := int(color.Green) & 0xff
		b := int(color.Blue) & 0xff
		fmt.Fprintf(w, "%2.1f%% - #%02x%02x%02x\n", quantized.PixelFraction*100, r, g, b)
	}

	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 参考文档。

注意：对于 Java Spring 框架用户，Spring Cloud Google Cloud 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。

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.ColorInfo;
import com.google.cloud.vision.v1.DominantColorsAnnotation;
import com.google.cloud.vision.v1.Feature;
import com.google.cloud.vision.v1.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

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

  // Detects image properties such as color frequency from the specified local image.
  public static void detectProperties(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(Feature.Type.IMAGE_PROPERTIES).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;
        }

        // For full list of available annotations, see http://g.co/cloud/vision/docs
        DominantColorsAnnotation colors = res.getImagePropertiesAnnotation().getDominantColors();
        for (ColorInfo color : colors.getColorsList()) {
          System.out.format(
              "fraction: %f%nr: %f, g: %f, b: %f%n",
              color.getPixelFraction(),
              color.getColor().getRed(),
              color.getColor().getGreen(),
              color.getColor().getBlue());
        }
      }
    }
  }
}

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。

如需向 Vision 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。

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';

// Performs property detection on the local file
const [result] = await client.imageProperties(fileName);
const colors = result.imagePropertiesAnnotation.dominantColors.colors;
colors.forEach(color => console.log(color));

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。

如需向 Vision 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。

def detect_properties(path):
    """Detects image properties in the file."""
    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.image_properties(image=image)
    props = response.image_properties_annotation
    print("Properties:")

    for color in props.dominant_colors.colors:
        print(f"fraction: {color.pixel_fraction}")
        print(f"\tr: {color.color.red}")
        print(f"\tg: {color.color.green}")
        print(f"\tb: {color.color.blue}")
        print(f"\ta: {color.color.alpha}")

    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。

检测远程图片中的图片属性

您可以使用 Vision API 对位于 Cloud Storage 或网络中的远程图片文件执行特征检测。如需发送远程文件请求，请在请求正文中指定文件的网址或 Cloud Storage URI。

ColorInfo 字段不包含用于解释 RGB 值的绝对颜色空间（例如 sRGB、Adobe RGB、DCI-P3、BT.2020 等等）的相关信息。默认情况下，应用应采用 sRGB 颜色空间。

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。最佳实践是，对于生产应用不要依赖外部托管的图片。

REST

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 存储桶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/image_properties/bali.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。
• PROJECT_ID：您的 Google Cloud 项目 ID。

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": "IMAGE_PROPERTIES"
        },
      ]
    }
  ]
}

如需发送请求，请选择以下方式之一：

curl

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

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 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：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

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 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 100 pixels by 100 pixels. For more information, see the API Reference documentation.

响应

{
  "responses": [
    {
      "imagePropertiesAnnotation": {
        "dominantColors": {
          "colors": [
            {
              "color": {
                "red": 243,
                "green": 177,
                "blue": 133
              },
              "score": 0.18074834,
              "pixelFraction": 0.013533333
            },
            {
              "color": {
                "red": 204,
                "green": 205,
                "blue": 213
              },
              "score": 0.092455424,
              "pixelFraction": 0.19266666
            },
            {
              "color": {
                "red": 114,
                "green": 77,
                "blue": 64
              },
              "score": 0.090447456,
              "pixelFraction": 0.034133334
            },
            {
              "color": {
                "red": 224,
                "green": 57,
                "blue": 64
              },
              "score": 0.010952942,
              "pixelFraction": 0.014266667
            },
            {
              "color": {
                "red": 248,
                "green": 125,
                "blue": 130
              },
              "score": 0.006984347,
              "pixelFraction": 0.0057333335
            },
            {
              "color": {
                "red": 150,
                "green": 107,
                "blue": 92
              },
              "score": 0.081589326,
              "pixelFraction": 0.019666666
            },
            {
              "color": {
                "red": 233,
                "green": 185,
                "blue": 158
              },
              "score": 0.08035342,
              "pixelFraction": 0.0122
            },
            {
              "color": {
                "red": 221,
                "green": 221,
                "blue": 226
              },
              "score": 0.045200635,
              "pixelFraction": 0.202
            },
            {
              "color": {
                "red": 105,
                "green": 77,
                "blue": 75
              },
              "score": 0.030223774,
              "pixelFraction": 0.013866667
            },
            {
              "color": {
                "red": 189,
                "green": 145,
                "blue": 123
              },
              "score": 0.028689377,
              "pixelFraction": 0.0069333334
            }
          ]
        }
      },
      "cropHintsAnnotation": {
        "cropHints": [
          {
            "boundingPoly": {
              "vertices": [
                {},
                {
                  "x": 2549
                },
                {
                  "x": 2549,
                  "y": 1699
                },
                {
                  "y": 1699
                }
              ]
            },
            "confidence": 0.79999995,
            "importanceFraction": 1
          }
        ]
      }
    }
  ]
}

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。

如需向 Vision 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。

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

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

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

	fmt.Fprintln(w, "Dominant colors:")
	for _, quantized := range props.DominantColors.Colors {
		color := quantized.Color
		r := int(color.Red) & 0xff
		g := int(color.Green) & 0xff
		b := int(color.Blue) & 0xff
		fmt.Fprintf(w, "%2.1f%% - #%02x%02x%02x\n", quantized.PixelFraction*100, r, g, b)
	}

	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。

如需向 Vision 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。

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.ColorInfo;
import com.google.cloud.vision.v1.DominantColorsAnnotation;
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 java.io.IOException;
import java.util.ArrayList;
import java.util.List;

public class DetectPropertiesGcs {

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

  // Detects image properties such as color frequency from the specified remote image on Google
  // Cloud Storage.
  public static void detectPropertiesGcs(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.IMAGE_PROPERTIES).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;
        }

        // For full list of available annotations, see http://g.co/cloud/vision/docs
        DominantColorsAnnotation colors = res.getImagePropertiesAnnotation().getDominantColors();
        for (ColorInfo color : colors.getColorsList()) {
          System.out.format(
              "fraction: %f%nr: %f, g: %f, b: %f%n",
              color.getPixelFraction(),
              color.getColor().getRed(),
              color.getColor().getGreen(),
              color.getColor().getBlue());
        }
      }
    }
  }
}

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。

如需向 Vision 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。

// 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';

// Performs property detection on the gcs file
const [result] = await client.imageProperties(
  `gs://${bucketName}/${fileName}`
);
const colors = result.imagePropertiesAnnotation.dominantColors.colors;
colors.forEach(color => console.log(color));

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。

如需向 Vision 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。

def detect_properties_uri(uri):
    """Detects image properties in the file located in Google Cloud Storage or
    on the Web."""
    from google.cloud import vision

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

    response = client.image_properties(image=image)
    props = response.image_properties_annotation
    print("Properties:")

    for color in props.dominant_colors.colors:
        print(f"frac: {color.pixel_fraction}")
        print(f"\tr: {color.color.red}")
        print(f"\tg: {color.color.green}")
        print(f"\tb: {color.color.blue}")
        print(f"\ta: {color.color.alpha}")

    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

如需执行图片属性检测操作，请使用 gcloud ml vision detect-image-properties 命令，如以下示例所示：

gcloud ml vision detect-image-properties gs://cloud-samples-data/vision/image_properties/bali.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。

试用

接下来，请尝试执行图片属性检测。您可以使用已指定的图片 (gs://cloud-samples-data/vision/image_properties/bali.jpeg) 或指定您自己的图片。选择执行即可发送请求。



图片来源：Unsplash 用户 Jeremy Bishop。

请求正文：

{
  "requests": [
    {
      "features": [
        {
          "maxResults": 10,
          "type": "IMAGE_PROPERTIES"
        }
      ],
      "image": {
        "source": {
          "imageUri": "gs://cloud-samples-data/vision/image_properties/bali.jpeg"
        }
      }
    }
  ]
}