检测剪裁提示

剪裁提示会确定图片的建议剪裁区域顶点。

剪裁前的图片
图片来源: Unsplash 用户 Yasmin Dangor(显示原始图片和剪裁后的图片)。

已应用剪裁提示(比例为 2:1)

剪裁后的图片

剪裁提示检测请求

设置您的 GCP 项目和身份验证

检测本地图片中的剪裁提示

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

在使用下面的任何请求数据之前,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。

具体字段的注意事项

  • cropHintsParams.aspectRatios - 一个浮点数,对应于图片的指定比例(宽高比)。您最多可以提供 16 个剪裁比例。

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": [
        {
          "type": "CROP_HINTS"
        }
      ],
      "imageContext": {
        "cropHintsParams": {
          "aspectRatios": [
             2.0
          ]
        }
      }
    }
  ]
}

如需发送请求,请选择以下方式之一:

curl

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

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

{
  "responses": [
    {
      "cropHintsAnnotation": {
        "cropHints": [
          {
            "boundingPoly": {
              "vertices": [
                {
                  "y": 520
                },
                {
                  "x": 2369,
                  "y": 520
                },
                {
                  "x": 2369,
                  "y": 1729
                },
                {
                  "y": 1729
                }
              ]
            },
            "confidence": 0.79999995,
            "importanceFraction": 0.66999996
          }
        ]
      }
    }
  ]
}

Go

在试用此示例之前,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


// detectCropHints gets suggested croppings the Vision API for an image at the given file path.
func detectCropHints(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
	}
	res, err := client.CropHints(ctx, image, nil)
	if err != nil {
		return err
	}

	fmt.Fprintln(w, "Crop hints:")
	for _, hint := range res.CropHints {
		for _, v := range hint.BoundingPoly.Vertices {
			fmt.Fprintf(w, "(%d,%d)\n", v.X, v.Y)
		}
	}

	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


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.CropHint;
import com.google.cloud.vision.v1.CropHintsAnnotation;
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 DetectCropHints {
  public static void detectCropHints() throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String filePath = "path/to/your/image/file.jpg";
    detectCropHints(filePath);
  }

  // Suggests a region to crop to for a local file.
  public static void detectCropHints(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.CROP_HINTS).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
        CropHintsAnnotation annotation = res.getCropHintsAnnotation();
        for (CropHint hint : annotation.getCropHintsList()) {
          System.out.println(hint.getBoundingPoly());
        }
      }
    }
  }
}

Node.js

在试用此示例之前,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


// 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';

// Find crop hints for the local file
const [result] = await client.cropHints(fileName);
const cropHints = result.cropHintsAnnotation;
cropHints.cropHints.forEach((hintBounds, hintIdx) => {
  console.log(`Crop Hint ${hintIdx}:`);
  hintBounds.boundingPoly.vertices.forEach((bound, boundIdx) => {
    console.log(`  Bound ${boundIdx}: (${bound.x}, ${bound.y})`);
  });
});

Python

在试用此示例之前,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

def detect_crop_hints(path):
    """Detects crop hints in 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)

    crop_hints_params = vision.CropHintsParams(aspect_ratios=[1.77])
    image_context = vision.ImageContext(
        crop_hints_params=crop_hints_params)

    response = client.crop_hints(image=image, image_context=image_context)
    hints = response.crop_hints_annotation.crop_hints

    for n, hint in enumerate(hints):
        print('\nCrop Hint: {}'.format(n))

        vertices = (['({},{})'.format(vertex.x, vertex.y)
                    for vertex in hint.bounding_poly.vertices])

        print('bounds: {}'.format(','.join(vertices)))

    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。

检测远程图片中的剪裁提示

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。

REST 和命令行

在使用下面的任何请求数据之前,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/crop_hints/bubble.jpeg

具体字段的注意事项

  • cropHintsParams.aspectRatios - 一个浮点数,对应于图片的指定比例(宽高比)。您最多可以提供 16 个剪裁比例。

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": "CROP_HINTS"
        }
      ],
      "imageContext": {
        "cropHintsParams": {
          "aspectRatios": [
             2.0
          ]
        }
      }
    }
  ]
}

如需发送请求,请选择以下方式之一:

curl

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

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

{
  "responses": [
    {
      "cropHintsAnnotation": {
        "cropHints": [
          {
            "boundingPoly": {
              "vertices": [
                {
                  "y": 520
                },
                {
                  "x": 2369,
                  "y": 520
                },
                {
                  "x": 2369,
                  "y": 1729
                },
                {
                  "y": 1729
                }
              ]
            },
            "confidence": 0.79999995,
            "importanceFraction": 0.66999996
          }
        ]
      }
    }
  ]
}

Java

在试用此示例之前,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


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.CropHint;
import com.google.cloud.vision.v1.CropHintsAnnotation;
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 DetectCropHintsGcs {

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

  // Suggests a region to crop to for a remote file on Google Cloud Storage.
  public static void detectCropHintsGcs(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.CROP_HINTS).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
        CropHintsAnnotation annotation = res.getCropHintsAnnotation();
        for (CropHint hint : annotation.getCropHintsList()) {
          System.out.println(hint.getBoundingPoly());
        }
      }
    }
  }
}

Go

在试用此示例之前,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


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

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

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

	fmt.Fprintln(w, "Crop hints:")
	for _, hint := range res.CropHints {
		for _, v := range hint.BoundingPoly.Vertices {
			fmt.Fprintf(w, "(%d,%d)\n", v.X, v.Y)
		}
	}

	return nil
}

Node.js

在试用此示例之前,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


// 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';

// Find crop hints for the remote file
const [result] = await client.cropHints(`gs://${bucketName}/${fileName}`);
const cropHints = result.cropHintsAnnotation;
cropHints.cropHints.forEach((hintBounds, hintIdx) => {
  console.log(`Crop Hint ${hintIdx}:`);
  hintBounds.boundingPoly.vertices.forEach((bound, boundIdx) => {
    console.log(`  Bound ${boundIdx}: (${bound.x}, ${bound.y})`);
  });
});

Python

在试用此示例之前,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

def detect_crop_hints_uri(uri):
    """Detects crop hints in the file located in Google Cloud Storage."""
    from google.cloud import vision
    client = vision.ImageAnnotatorClient()
    image = vision.Image()
    image.source.image_uri = uri

    crop_hints_params = vision.CropHintsParams(aspect_ratios=[1.77])
    image_context = vision.ImageContext(
        crop_hints_params=crop_hints_params)

    response = client.crop_hints(image=image, image_context=image_context)
    hints = response.crop_hints_annotation.crop_hints

    for n, hint in enumerate(hints):
        print('\nCrop Hint: {}'.format(n))

        vertices = (['({},{})'.format(vertex.x, vertex.y)
                    for vertex in hint.bounding_poly.vertices])

        print('bounds: {}'.format(','.join(vertices)))

    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

如需执行文本检测,请使用 gcloud ml vision suggest-crop 命令,如以下示例所示:

gcloud ml vision suggest-crop gs://cloud-samples-data/vision/crop_hints/bubble.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

请尝试以下剪裁提示检测。您可以使用已指定的图片 (gs://cloud-samples-data/vision/crop_hints/bubble.jpeg) 或指定您自己的图片。选择执行来发送请求。

剪裁前的图片
图片来源:Unsplash 用户 Yasmin Dangor

请求正文:

{
  "requests": [
    {
      "image": {
        "source": {
          "gcsImageUri": "gs://cloud-samples-data/vision/crop_hints/bubble.jpeg"
        }
      },
      "features": [
        {
          "type": "CROP_HINTS"
        }
      ],
      "imageContext": {
        "cropHintsParams": {
          "aspectRatios": [
            2
          ]
        }
      }
    }
  ]
}