웹 항목 및 페이지 감지

웹 감지는 이미지에 대한 웹 참조를 감지하는 기능입니다.

카니발 이미지
이미지 크레딧: 퀸텐 데 그라프, Unsplash

카테고리 응답
웹 항목
  • 항목 ID: /m/02p7_j8, 점수: 1.3225499, 설명: 리우데자네이루의 카니발
  • 항목 ID: /m/06gmr, 점수: 1.1684971, 설명: 리우데자네이루
  • 항목 ID: /m/04cx88, 점수: 1.05945, 설명: 브라질 카니발
...
전체 일치 이미지
  • 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
...
부분 일치 이미지
  • 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
...
일치하는 이미지가 포함된 페이지
  • 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}]
...
유사한 이미지
  • 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
...
최선의 추측 라벨 리우 카니발 2019 댄서

웹 감지 요청

GCP 프로젝트 및 인증 설정

로컬 이미지를 사용하는 웹 항목 감지

Vision API는 이미지 파일의 콘텐츠를 요청 본문에 base64로 인코딩된 문자열로 전송하여 로컬 이미지 파일에서 기능 감지를 수행할 수 있습니다.

REST 및 명령줄

아래의 요청 데이터를 사용하기 전에 다음을 바꿉니다.

  • base64-encoded-image: 바이너리 이미지 데이터의 base64 표현(ASCII 문자열)입니다. 이 문자열은 다음 문자열과 비슷해야 합니다.
    • /9j/4QAYRXhpZgAA...9tAVx/zDQDlGxn//2Q==
    자세한 내용은 base64 인코딩 주제를 참조하세요.

HTTP 메서드 및 URL: 

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

JSON 요청 본문:

{
  "requests": [
    {
      "image": {
        "content": "base64-encoded-image"
      },
      "features": [
        {
          "maxResults": 10,
          "type": "WEB_DETECTION"
        },
      ]
    }
  ]
}

요청을 보내려면 다음 옵션 중 하나를 선택합니다.

curl

요청 본문을 request.json 파일에 저장하고 다음 명령어를 실행합니다.

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

요청 본문을 request.json 파일에 저장하고 다음 명령어를 실행합니다.

$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

요청이 성공하면 서버가 200 OK HTTP 상태 코드와 응답을 JSON 형식으로 반환합니다.

응답:

C#

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 C# 설정 안내를 따르세요. 자세한 내용은 Vision C# API 참조 문서를 참조하세요. 

// Load an image from a local file.
var image = Image.FromFile(filePath);
var client = ImageAnnotatorClient.Create();
WebDetection annotation = client.DetectWebInformation(image);
foreach (var matchingImage in annotation.FullMatchingImages)
{
    Console.WriteLine("MatchingImage Score:\t{0}\tUrl:\t{1}",
        matchingImage.Score, matchingImage.Url);
}
foreach (var page in annotation.PagesWithMatchingImages)
{
    Console.WriteLine("PageWithMatchingImage Score:\t{0}\tUrl:\t{1}",
        page.Score, page.Url);
}
foreach (var matchingImage in annotation.PartialMatchingImages)
{
    Console.WriteLine("PartialMatchingImage Score:\t{0}\tUrl:\t{1}",
        matchingImage.Score, matchingImage.Url);
}
foreach (var entity in annotation.WebEntities)
{
    Console.WriteLine("WebEntity Score:\t{0}\tId:\t{1}\tDescription:\t{2}",
        entity.Score, entity.EntityId, entity.Description);
}

Go

이 샘플을 시도하기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Go 설정 안내를 따르세요. 자세한 내용은 Vision Go API 참조 문서를 참조하세요. 


// 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
}

자바

이 샘플을 시도하기 전에 Vision API 빠른 시작: 클라이언트 라이브러리 사용의 자바 설정 안내를 따르세요. 자세한 내용은 Vision API 자바 API 참조 문서를 확인하세요.


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

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Node.js 설정 안내를 따르세요. 자세한 내용은 Vision Node.js API 참조 문서를 참조하세요. 


// 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}`);
  });
}

PHP

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 PHP 설정 안내를 따르세요. 자세한 내용은 Vision PHP API 참조 문서를 참조하세요. 

namespace Google\Cloud\Samples\Vision;

use Google\Cloud\Vision\V1\ImageAnnotatorClient;

// $path = 'path/to/your/image.jpg'

function detect_web($path)
{
    $imageAnnotator = new ImageAnnotatorClient();

    # annotate the image
    $image = file_get_contents($path);
    $response = $imageAnnotator->webDetection($image);
    $web = $response->getWebDetection();

    // Print best guess labels
    printf('%d best guess labels found' . PHP_EOL,
        count($web->getBestGuessLabels()));
    foreach ($web->getBestGuessLabels() as $label) {
        printf('Best guess label: %s' . PHP_EOL, $label->getLabel());
    }
    print(PHP_EOL);

    // Print pages with matching images
    printf('%d pages with matching images found' . PHP_EOL,
        count($web->getPagesWithMatchingImages()));
    foreach ($web->getPagesWithMatchingImages() as $page) {
        printf('URL: %s' . PHP_EOL, $page->getUrl());
    }
    print(PHP_EOL);

    // Print full matching images
    printf('%d full matching images found' . PHP_EOL,
        count($web->getFullMatchingImages()));
    foreach ($web->getFullMatchingImages() as $fullMatchingImage) {
        printf('URL: %s' . PHP_EOL, $fullMatchingImage->getUrl());
    }
    print(PHP_EOL);

    // Print partial matching images
    printf('%d partial matching images found' . PHP_EOL,
        count($web->getPartialMatchingImages()));
    foreach ($web->getPartialMatchingImages() as $partialMatchingImage) {
        printf('URL: %s' . PHP_EOL, $partialMatchingImage->getUrl());
    }
    print(PHP_EOL);

    // Print visually similar images
    printf('%d visually similar images found' . PHP_EOL,
        count($web->getVisuallySimilarImages()));
    foreach ($web->getVisuallySimilarImages() as $visuallySimilarImage) {
        printf('URL: %s' . PHP_EOL, $visuallySimilarImage->getUrl());
    }
    print(PHP_EOL);

    // Print web entities
    printf('%d web entities found' . PHP_EOL,
        count($web->getWebEntities()));
    foreach ($web->getWebEntities() as $entity) {
        printf('Description: %s, Score %s' . PHP_EOL,
            $entity->getDescription(),
            $entity->getScore());
    }

    $imageAnnotator->close();
}

Python

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Python 설정 안내를 따르세요. 자세한 내용은 Vision Python API 참조 문서를 확인하세요. 

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))

Ruby

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Ruby 설정 안내를 따르세요. 자세한 내용은 Vision Ruby API 참조 문서를 참조하세요. 

# image_path = "Path to local image file, eg. './image.png'"

require "google/cloud/vision"

image_annotator = Google::Cloud::Vision.image_annotator

response = image_annotator.web_detection(
  image:       image_path,
  max_results: 15 # optional, defaults to 10
)

response.responses.each do |res|
  res.web_detection.web_entities.each do |entity|
    puts entity.description
  end

  res.web_detection.full_matching_images.each do |match|
    puts match.url
  end
end

원격 이미지의 웹 항목 감지

편의를 위해 Vision API는 요청 본문 안에 이미지 파일의 콘텐츠를 보내지 않고도 Google Cloud Storage 또는 웹에 위치한 이미지 파일에서 바로 특징 감지를 수행할 수 있습니다.

REST 및 명령줄

아래의 요청 데이터를 사용하기 전에 다음을 바꿉니다.

  • cloud-storage-image-uri: Cloud Storage 버킷에 있는 유효한 이미지 파일의 경로입니다. 적어도 파일에 대한 읽기 권한이 있어야 합니다. 예를 들면 다음과 같습니다. 
    • gs://cloud-samples-data/vision/web/carnaval.jpeg

HTTP 메서드 및 URL: 

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

JSON 요청 본문:

{
  "requests": [
    {
      "image": {
        "source": {
          "gcsImageUri": "cloud-storage-image-uri"
        }
      },
      "features": [
        {
          "maxResults": 10,
          "type": "WEB_DETECTION"
        },
      ]
    }
  ]
}

요청을 보내려면 다음 옵션 중 하나를 선택합니다.

curl

요청 본문을 request.json 파일에 저장하고 다음 명령어를 실행합니다.

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

요청 본문을 request.json 파일에 저장하고 다음 명령어를 실행합니다.

$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

요청이 성공하면 서버가 200 OK HTTP 상태 코드와 응답을 JSON 형식으로 반환합니다.

응답:

C#

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 C# 설정 안내를 따르세요. 자세한 내용은 Vision C# API 참조 문서를 참조하세요. 

// Specify a Google Cloud Storage uri for the image
// or a publicly accessible HTTP or HTTPS uri.
var image = Image.FromUri(uri);
var client = ImageAnnotatorClient.Create();
WebDetection annotation = client.DetectWebInformation(image);
foreach (var matchingImage in annotation.FullMatchingImages)
{
    Console.WriteLine("MatchingImage Score:\t{0}\tUrl:\t{1}",
        matchingImage.Score, matchingImage.Url);
}
foreach (var page in annotation.PagesWithMatchingImages)
{
    Console.WriteLine("PageWithMatchingImage Score:\t{0}\tUrl:\t{1}",
        page.Score, page.Url);
}
foreach (var matchingImage in annotation.PartialMatchingImages)
{
    Console.WriteLine("PartialMatchingImage Score:\t{0}\tUrl:\t{1}",
        matchingImage.Score, matchingImage.Url);
}
foreach (var entity in annotation.WebEntities)
{
    Console.WriteLine("WebEntity Score:\t{0}\tId:\t{1}\tDescription:\t{2}",
        entity.Score, entity.EntityId, entity.Description);
}

Go

이 샘플을 시도하기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Go 설정 안내를 따르세요. 자세한 내용은 Vision Go API 참조 문서를 참조하세요. 


// 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
}

자바

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 자바 설정 안내를 따르세요. 자세한 내용은 Vision 자바 API 참조 문서를 확인하세요. 


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

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Node.js 설정 안내를 따르세요. 자세한 내용은 Vision Node.js API 참조 문서를 참조하세요. 


// 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}`);
  });
}

PHP

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 PHP 설정 안내를 따르세요. 자세한 내용은 Vision PHP API 참조 문서를 참조하세요. 

namespace Google\Cloud\Samples\Vision;

use Google\Cloud\Vision\V1\ImageAnnotatorClient;

// $path = 'gs://path/to/your/image.jpg'

function detect_web_gcs($path)
{
    $imageAnnotator = new ImageAnnotatorClient();

    # annotate the image
    $response = $imageAnnotator->webDetection($path);
    $web = $response->getWebDetection();

    if ($web) {
        printf('%d best guess labels found' . PHP_EOL,
            count($web->getPagesWithMatchingImages()));
        foreach ($web->getBestGuessLabels() as $label) {
            printf('Best guess label: %s' . PHP_EOL, $label->getLabel());
        }
        print(PHP_EOL);

        // Print pages with matching images
        printf('%d pages with matching images found' . PHP_EOL,
            count($web->getPagesWithMatchingImages()));
        foreach ($web->getPagesWithMatchingImages() as $page) {
            printf('URL: %s' . PHP_EOL, $page->getUrl());
        }
        print(PHP_EOL);

        // Print full matching images
        printf('%d full matching images found' . PHP_EOL,
            count($web->getFullMatchingImages()));
        foreach ($web->getFullMatchingImages() as $fullMatchingImage) {
            printf('URL: %s' . PHP_EOL, $fullMatchingImage->getUrl());
        }
        print(PHP_EOL);

        // Print partial matching images
        printf('%d partial matching images found' . PHP_EOL,
            count($web->getPartialMatchingImages()));
        foreach ($web->getPartialMatchingImages() as $partialMatchingImage) {
            printf('URL: %s' . PHP_EOL, $partialMatchingImage->getUrl());
        }
        print(PHP_EOL);

        // Print visually similar images
        printf('%d visually similar images found' . PHP_EOL,
            count($web->getVisuallySimilarImages()));
        foreach ($web->getVisuallySimilarImages() as $visuallySimilarImage) {
            printf('URL: %s' . PHP_EOL, $visuallySimilarImage->getUrl());
        }
        print(PHP_EOL);

        // Print web entities
        printf('%d web entities found' . PHP_EOL,
            count($web->getWebEntities()));
        foreach ($web->getWebEntities() as $entity) {
            printf('Description: %s, Score: %f' . PHP_EOL,
                $entity->getDescription(),
                $entity->getScore());
        }
    } else {
        print('No Results.' . PHP_EOL);
    }

    $imageAnnotator->close();
}

Python

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Python 설정 안내를 따르세요. 자세한 내용은 Vision Python API 참조 문서를 확인하세요. 

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))

Ruby

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Ruby 설정 안내를 따르세요. 자세한 내용은 Vision Ruby API 참조 문서를 참조하세요. 

# image_path = "Google Cloud Storage URI, eg. 'gs://my-bucket/image.png'"

require "google/cloud/vision"

image_annotator = Google::Cloud::Vision.image_annotator

response = image_annotator.web_detection(
  image:       image_path,
  max_results: 15 # optional, defaults to 10
)

response.responses.each do |res|
  res.web_detection.web_entities.each do |entity|
    puts entity.description
  end

  res.web_detection.full_matching_images.each do |match|
    puts match.url
  end
end

gcloud

웹 감지를 수행하려면 다음 예시와 같이 gcloud ml vision detect-web 명령어를 사용합니다.

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

로컬 이미지에 지리정보 메타데이터 사용

Vision API는 이미지 파일의 위치정보 태그 메타데이터에 액세스하여 더 관련성 높은 웹 항목 및 페이지를 반환할 수 있습니다. 위치정보 태그를 사용하도록 허용하려면 요청에 'includeGeoResults': true를 지정합니다.

REST 및 명령줄

아래의 요청 데이터를 사용하기 전에 다음을 바꿉니다.

  • cloud-storage-image-uri: Cloud Storage 버킷에 있는 유효한 이미지 파일의 경로입니다. 적어도 파일에 대한 읽기 권한이 있어야 합니다. 예를 들면 다음과 같습니다. 
    • gs://cloud-samples-data/vision/web/carnaval.jpeg

HTTP 메서드 및 URL: 

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

JSON 요청 본문:

{
  "requests": [
    {
      "image": {
        "source": {
          "gcsImageUri": "cloud-storage-image-uri"
        }
      },
      "features": [
        {
          "type": "WEB_DETECTION"
        }
      ],
      "imageContext": {
        "webDetectionParams": {
          "includeGeoResults": true
          }
        }
    }
  ]
}

요청을 보내려면 다음 옵션 중 하나를 선택합니다.

curl

요청 본문을 request.json 파일에 저장하고 다음 명령어를 실행합니다.

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

요청 본문을 request.json 파일에 저장하고 다음 명령어를 실행합니다.

$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

요청이 성공하면 서버가 200 OK HTTP 상태 코드와 응답을 JSON 형식으로 반환합니다.

응답:

Go

이 샘플을 시도하기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Go 설정 안내를 따르세요. 자세한 내용은 Vision Go API 참조 문서를 참조하세요. 


// 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
}

자바

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 자바 설정 안내를 따르세요. 자세한 내용은 Vision 자바 API 참조 문서를 확인하세요. 


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

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Node.js 설정 안내를 따르세요. 자세한 내용은 Vision Node.js API 참조 문서를 참조하세요. 

// 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}`);
});

PHP

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 PHP 설정 안내를 따르세요. 자세한 내용은 Vision PHP API 참조 문서를 참조하세요. 

namespace Google\Cloud\Samples\Vision;

use Google\Cloud\Vision\V1\ImageAnnotatorClient;
use Google\Cloud\Vision\V1\ImageContext;
use Google\Cloud\Vision\V1\WebDetectionParams;

// $path = 'path/to/your/image.jpg'

/**
 * Detect web entities on an image and include the image's geo metadata
 * to improve the quality of the detection.
 */
function detect_web_with_geo_metadata($path)
{
    $imageAnnotator = new ImageAnnotatorClient();

    # enable include geo results
    $params = new WebDetectionParams();
    $params->setIncludeGeoResults(true);
    $imageContext = new ImageContext();
    $imageContext-> setWebDetectionParams($params);

    # annotate the image
    $image = file_get_contents($path);
    $response = $imageAnnotator->webDetection($image, ['imageContext' => $imageContext]);
    $web = $response->getWebDetection();

    if ($web && $web->getWebEntities()) {
        printf('%d web entities found:' . PHP_EOL,
            count($web->getWebEntities()));
        foreach ($web->getWebEntities() as $entity) {
            printf('Description: %s ' . PHP_EOL, $entity->getDescription());
            printf('Score: %f' . PHP_EOL, $entity->getScore());
            print(PHP_EOL);
        }
    }

    $imageAnnotator->close();
}

Python

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Python 설정 안내를 따르세요. 자세한 내용은 Vision Python API 참조 문서를 확인하세요. 

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

웹 감지를 수행하려면 다음 예시와 같이 gcloud ml vision detect-web 명령어를 사용합니다.

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

원격 이미지에 지리정보 메타데이터 사용

Go

이 샘플을 시도하기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Go 설정 안내를 따르세요. 자세한 내용은 Vision Go API 참조 문서를 참조하세요. 


// 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
}

자바

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 자바 설정 안내를 따르세요. 자세한 내용은 Vision 자바 API 참조 문서를 확인하세요. 


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

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Node.js 설정 안내를 따르세요. 자세한 내용은 Vision Node.js API 참조 문서를 참조하세요. 

// 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}`);
});

PHP

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 PHP 설정 안내를 따르세요. 자세한 내용은 Vision PHP API 참조 문서를 참조하세요. 

namespace Google\Cloud\Samples\Vision;

use Google\Cloud\Vision\V1\ImageAnnotatorClient;
use Google\Cloud\Vision\V1\ImageContext;
use Google\Cloud\Vision\V1\WebDetectionParams;

// $path = 'gs://path/to/your/image.jpg'

/**
 * Detect web entities on an image and include the image's geo metadata
 * to improve the quality of the detection.
 */
function detect_web_with_geo_metadata_gcs($path)
{
    $imageAnnotator = new ImageAnnotatorClient();

    # enable include geo results
    $params = new WebDetectionParams();
    $params->setIncludeGeoResults(true);
    $imageContext = new ImageContext();
    $imageContext-> setWebDetectionParams($params);

    # annotate the image
    $response = $imageAnnotator->webDetection($path, ['imageContext' => $imageContext]);
    $web = $response->getWebDetection();

    if ($web) {
        printf('%d web entities found:' . PHP_EOL,
            count($web->getWebEntities()));
        foreach ($web->getWebEntities() as $entity) {
            printf('Description: %s ' . PHP_EOL, $entity->getDescription());
            printf('Score: %f' . PHP_EOL, $entity->getScore());
            print(PHP_EOL);
        }
    } else {
        print('No Results.' . PHP_EOL);
    }

    $imageAnnotator->close();
}

Python

이 샘플을 시도해 보기 전에 클라이언트 라이브러리를 사용하는 Vision 빠른 시작의 Python 설정 안내를 따르세요. 자세한 내용은 Vision Python API 참조 문서를 확인하세요. 

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))

사용해 보기

아래와 같이 웹 항목 감지를 사용해 봅니다. 이미 지정된 이미지(gs://cloud-samples-data/vision/web/carnaval.jpeg)를 사용하거나 자체 이미지를 대신 지정할 수도 있습니다. 실행을 선택하여 요청을 보냅니다.

includeGeoResults를 false로 설정하고 요청을 반복해 봅니다.

카니발 이미지
이미지 크레딧: 퀸텐 데 그라프, Unsplash