Deteksi Web mendeteksi referensi Web pada sebuah gambar.
untuk detailnya
| Kategori | Respons |
|---|---|
| Entitas web |
|
| Gambar cocok yang penuh |
|
| Gambar cocok yang sebagian |
|
| Halaman dengan gambar yang cocok |
|
| Gambar yang mirip secara visual |
|
| Label guess terbaik | penari rio karnaval 2019 |
Permintaan deteksi web
Menyiapkan project dan autentikasi Google Cloud
Jika Anda belum membuat Google Cloud project, lakukan sekarang. Luaskan bagian ini untuk menampilkan petunjuk.
- 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 role
(
roles/resourcemanager.projectCreator), which contains theresourcemanager.projects.createpermission. Learn how to grant roles.
-
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 theserviceusage.services.enablepermission. Learn how to grant roles. -
Install the Google Cloud CLI.
-
Jika Anda menggunakan penyedia identitas (IdP) eksternal, Anda harus login ke gcloud CLI dengan identitas gabungan Anda terlebih dahulu.
-
Untuk melakukan inisialisasi gcloud CLI, jalankan perintah berikut:
gcloud init -
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Roles required to select or create a project
- Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
-
Create a project: To create a project, you need the Project Creator role
(
roles/resourcemanager.projectCreator), which contains theresourcemanager.projects.createpermission. Learn how to grant roles.
-
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 theserviceusage.services.enablepermission. Learn how to grant roles. -
Install the Google Cloud CLI.
-
Jika Anda menggunakan penyedia identitas (IdP) eksternal, Anda harus login ke gcloud CLI dengan identitas gabungan Anda terlebih dahulu.
-
Untuk melakukan inisialisasi gcloud CLI, jalankan perintah berikut:
gcloud init - BASE64_ENCODED_IMAGE: Representasi
base64 (string ASCII) dari data gambar biner Anda. String ini akan terlihat seperti
string berikut:
/9j/4QAYRXhpZgAA...9tAVx/zDQDlGxn//2Q==
- RESULTS_INT: (Opsional) Nilai bilangan bulat dari hasil yang akan
ditampilkan. Jika Anda menghilangkan kolom
"maxResults"dan nilainya, API akan menampilkan nilai default 10 hasil. Kolom ini tidak berlaku untuk jenis fitur berikut:TEXT_DETECTION,DOCUMENT_TEXT_DETECTION, atauCROP_HINTS. - PROJECT_ID: Project ID Google Cloud Anda.
- CLOUD_STORAGE_IMAGE_URI: jalur ke file gambar
yang valid di bucket Cloud Storage. Anda setidaknya harus memiliki hak istimewa baca ke file tersebut.
Contoh:
gs://cloud-samples-data/vision/web/carnaval.jpeg
- RESULTS_INT: (Opsional) Nilai bilangan bulat dari hasil yang akan
ditampilkan. Jika Anda menghilangkan kolom
"maxResults"dan nilainya, API akan menampilkan nilai default 10 hasil. Kolom ini tidak berlaku untuk jenis fitur berikut:TEXT_DETECTION,DOCUMENT_TEXT_DETECTION, atauCROP_HINTS. - PROJECT_ID: Project ID Google Cloud Anda.
Mendeteksi entity Web dengan gambar lokal
Anda dapat menggunakan Vision API untuk melakukan deteksi fitur pada file gambar lokal.
Untuk permintaan REST, kirim konten file gambar sebagai string yang berenkode base64 dalam isi permintaan Anda.
Untuk gcloud dan permintaan library klien, tentukan jalur ke image lokal dalam
permintaan Anda.
REST
Sebelum menggunakan salah satu data permintaan, buat penggantian berikut:
Metode HTTP dan URL:
POST https://vision.googleapis.com/v1/images:annotate
Meminta isi JSON:
{
"requests": [
{
"image": {
"content": "BASE64_ENCODED_IMAGE"
},
"features": [
{
"maxResults": RESULTS_INT,
"type": "WEB_DETECTION"
},
]
}
]
}
Untuk mengirim permintaan Anda, pilih salah satu opsi berikut:
curl
Simpan isi permintaan dalam file bernama request.json,
dan jalankan perintah berikut:
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
Simpan isi permintaan dalam file bernama request.json,
dan jalankan perintah berikut:
$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
Jika permintaan berhasil, server akan menampilkan kode status HTTP 200 OK dan
respons dalam format JSON.
Respons:
Respons
{
"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
Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Go di Panduan memulai Vision menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi Vision Go API.
Untuk melakukan autentikasi ke Vision, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.
// 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
Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Java di Panduan Memulai Vision API Menggunakan Library Klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi Java 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.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
Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Node.js di Panduan memulai Vision menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi Vision Node.js API.
Untuk melakukan autentikasi ke Vision, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.
// 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
Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Python di Panduan memulai Vision menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi Vision Python API.
Untuk melakukan autentikasi ke Vision, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.
def detect_web(path):
"""Detects web annotations given an image."""
from google.cloud import vision
client = vision.ImageAnnotatorClient()
with open(path, "rb") as image_file:
content = image_file.read()
image = vision.Image(content=content)
response = client.web_detection(image=image)
annotations = response.web_detection
if annotations.best_guess_labels:
for label in annotations.best_guess_labels:
print(f"\nBest guess label: {label.label}")
if annotations.pages_with_matching_images:
print(
"\n{} Pages with matching images found:".format(
len(annotations.pages_with_matching_images)
)
)
for page in annotations.pages_with_matching_images:
print(f"\n\tPage url : {page.url}")
if page.full_matching_images:
print(
"\t{} Full Matches found: ".format(len(page.full_matching_images))
)
for image in page.full_matching_images:
print(f"\t\tImage url : {image.url}")
if page.partial_matching_images:
print(
"\t{} Partial Matches found: ".format(
len(page.partial_matching_images)
)
)
for image in page.partial_matching_images:
print(f"\t\tImage url : {image.url}")
if annotations.web_entities:
print("\n{} Web entities found: ".format(len(annotations.web_entities)))
for entity in annotations.web_entities:
print(f"\n\tScore : {entity.score}")
print(f"\tDescription: {entity.description}")
if annotations.visually_similar_images:
print(
"\n{} visually similar images found:\n".format(
len(annotations.visually_similar_images)
)
)
for image in annotations.visually_similar_images:
print(f"\tImage url : {image.url}")
if response.error.message:
raise Exception(
"{}\nFor more info on error messages, check: "
"https://cloud.google.com/apis/design/errors".format(response.error.message)
)
Bahasa tambahan
C#: Ikuti petunjuk penyiapan C# di halaman library klien, lalu buka dokumentasi referensi Vision untuk .NET.
PHP: Ikuti Petunjuk penyiapan PHP di halaman library klien, lalu buka Dokumentasi referensi Vision untuk PHP.
Ruby: Ikuti Petunjuk penyiapan Ruby di halaman library klien, lalu buka Dokumentasi referensi Vision untuk Ruby.
Mendeteksi entity Web dengan gambar jarak jauh
Anda dapat menggunakan Vision API untuk melakukan deteksi fitur pada file gambar jarak jauh yang terletak di Cloud Storage atau di Web. Untuk mengirim permintaan file jarak jauh, tentukan URL Web atau Cloud Storage URI file dalam isi permintaan.
REST
Sebelum menggunakan salah satu data permintaan, buat penggantian berikut:
Metode HTTP dan URL:
POST https://vision.googleapis.com/v1/images:annotate
Meminta isi JSON:
{
"requests": [
{
"image": {
"source": {
"gcsImageUri": "CLOUD_STORAGE_IMAGE_URI"
}
},
"features": [
{
"maxResults": RESULTS_INT,
"type": "WEB_DETECTION"
},
]
}
]
}
Untuk mengirim permintaan Anda, pilih salah satu opsi berikut:
curl
Simpan isi permintaan dalam file bernama request.json,
dan jalankan perintah berikut:
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
Simpan isi permintaan dalam file bernama request.json,
dan jalankan perintah berikut:
$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
Jika permintaan berhasil, server akan menampilkan kode status HTTP 200 OK dan
respons dalam format JSON.
Respons:
Respons
{
"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
Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Go di Panduan memulai Vision menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi Vision Go API.
Untuk melakukan autentikasi ke Vision, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.
// 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
Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Java di Panduan memulai Vision menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi Vision Java API.
Untuk melakukan autentikasi ke Vision, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.
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
Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Node.js di Panduan memulai Vision menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi Vision Node.js API.
Untuk melakukan autentikasi ke Vision, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.
// 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
Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Python di Panduan memulai Vision menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi Vision Python API.
Untuk melakukan autentikasi ke Vision, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.
def detect_web_uri(uri):
"""Detects web annotations in the file located in Google Cloud Storage."""
from google.cloud import vision
client = vision.ImageAnnotatorClient()
image = vision.Image()
image.source.image_uri = uri
response = client.web_detection(image=image)
annotations = response.web_detection
if annotations.best_guess_labels:
for label in annotations.best_guess_labels:
print(f"\nBest guess label: {label.label}")
if annotations.pages_with_matching_images:
print(
"\n{} Pages with matching images found:".format(
len(annotations.pages_with_matching_images)
)
)
for page in annotations.pages_with_matching_images:
print(f"\n\tPage url : {page.url}")
if page.full_matching_images:
print(
"\t{} Full Matches found: ".format(len(page.full_matching_images))
)
for image in page.full_matching_images:
print(f"\t\tImage url : {image.url}")
if page.partial_matching_images:
print(
"\t{} Partial Matches found: ".format(
len(page.partial_matching_images)
)
)
for image in page.partial_matching_images:
print(f"\t\tImage url : {image.url}")
if annotations.web_entities:
print("\n{} Web entities found: ".format(len(annotations.web_entities)))
for entity in annotations.web_entities:
print(f"\n\tScore : {entity.score}")
print(f"\tDescription: {entity.description}")
if annotations.visually_similar_images:
print(
"\n{} visually similar images found:\n".format(
len(annotations.visually_similar_images)
)
)
for image in annotations.visually_similar_images:
print(f"\tImage url : {image.url}")
if response.error.message:
raise Exception(
"{}\nFor more info on error messages, check: "
"https://cloud.google.com/apis/design/errors".format(response.error.message)
)
gcloud
Untuk melakukan deteksi Web, gunakan
perintah gcloud ml vision detect-web
seperti yang ditunjukkan pada contoh berikut:
gcloud ml vision detect-web gs://cloud-samples-data/vision/web/carnaval.jpeg
Bahasa tambahan
C#: Ikuti petunjuk penyiapan C# di halaman library klien, lalu buka dokumentasi referensi Vision untuk .NET.
PHP: Ikuti Petunjuk penyiapan PHP di halaman library klien, lalu buka Dokumentasi referensi Vision untuk PHP.
Ruby: Ikuti Petunjuk penyiapan Ruby di halaman library klien, lalu buka Dokumentasi referensi Vision untuk Ruby.
Cobalah
Coba deteksi entitas Web di bawah ini. Anda dapat menggunakan
gambar yang sudah ditetapkan (gs://cloud-samples-data/vision/web/carnaval.jpeg)
atau menentukan gambar Anda sendiri sebagai gantinya. Kirim permintaan dengan memilih
Jalankan.
Isi permintaan:
{
"requests": [
{
"features": [
{
"type": "WEB_DETECTION"
}
],
"image": {
"source": {
"gcsImageUri": "gs://cloud-samples-data/vision/web/carnaval.jpeg"
}
}
}
]
}