裁剪提示會建議圖片裁剪區域的端點。

已套用裁剪提示 (顯示比例 2:1):

裁剪提示偵測要求
設定 Google Cloud 專案和驗證
如果您尚未建立 Google Cloud 專案,請立即建立。展開這個部分即可查看操作說明。
- Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Verify that billing is enabled for your Google Cloud project.
-
Enable the Vision API.
-
Install the Google Cloud CLI.
-
如果您使用外部識別資訊提供者 (IdP),請先 使用聯合身分登入 gcloud CLI。
-
如要初始化 gcloud CLI,請執行下列指令:
gcloud init
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Verify that billing is enabled for your Google Cloud project.
-
Enable the Vision API.
-
Install the Google Cloud CLI.
-
如果您使用外部識別資訊提供者 (IdP),請先 使用聯合身分登入 gcloud CLI。
-
如要初始化 gcloud CLI,請執行下列指令:
gcloud init
- BASE64_ENCODED_IMAGE:二進位圖片資料的 Base64 表示法 (ASCII 字串)。這個字串應類似下列字串:
/9j/4QAYRXhpZgAA...9tAVx/zDQDlGxn//2Q==
- PROJECT_ID:您的 Google Cloud 專案 ID。
cropHintsParams.aspectRatios
- 對應至圖片指定比例 (寬度:高度) 的浮點數。你最多可以提供 16 個裁剪比例。- CLOUD_STORAGE_IMAGE_URI:Cloud Storage 值區中有效圖片檔案的路徑。您必須至少擁有檔案的讀取權限。
範例:
gs://cloud-samples-data/vision/crop_hints/bubble.jpeg
- PROJECT_ID:您的 Google Cloud 專案 ID。
cropHintsParams.aspectRatios
- 對應至圖片指定比例 (寬度:高度) 的浮點數。你最多可以提供 16 個裁剪比例。
偵測本機圖片的裁剪提示
您可以使用 Vision API 對本機圖片檔執行特徵偵測。
如果是 REST 要求,請在要求主體中,以 base64 編碼字串的形式傳送圖片檔案內容。
如果是 gcloud
和用戶端程式庫要求,請在要求中指定本機圖片的路徑。
REST
使用任何要求資料之前,請先替換以下項目:
欄位專屬注意事項:
HTTP 方法和網址:
POST https://vision.googleapis.com/v1/images:annotate
JSON 要求主體:
{ "requests": [ { "image": { "content": "BASE64_ENCODED_IMAGE" }, "features": [ { "type": "CROP_HINTS" } ], "imageContext": { "cropHintsParams": { "aspectRatios": [ 2.0 ] } } } ] }
如要傳送要求,請選擇以下其中一個選項:
curl
將要求主體儲存在名為 request.json
的檔案中,然後執行下列指令:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: PROJECT_ID" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://vision.googleapis.com/v1/images:annotate"
PowerShell
將要求主體儲存在名為 request.json
的檔案中,然後執行下列指令:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }
Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://vision.googleapis.com/v1/images:annotate" | Select-Object -Expand Content
如果要求成功,伺服器會傳回 200 OK
HTTP 狀態碼與 JSON 格式的回應。
回覆:
{ "responses": [ { "cropHintsAnnotation": { "cropHints": [ { "boundingPoly": { "vertices": [ { "y": 520 }, { "x": 2369, "y": 520 }, { "x": 2369, "y": 1729 }, { "y": 1729 } ] }, "confidence": 0.79999995, "importanceFraction": 0.66999996 } ] } } ] }
Go
在試用這個範例之前,請先按照Go「使用用戶端程式庫的 Vision 快速入門導覽課程」中的設定說明操作。詳情請參閱 Vision Go API 參考說明文件。
如要向 Vision 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。
// 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
在試用這個範例之前,請先按照使用用戶端程式庫的 Vision API 快速入門導覽課程中的 Java 設定操作說明進行操作。詳情請參閱 Vision API Java 參考說明文件。
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
在試用這個範例之前,請先按照Node.js「使用用戶端程式庫的 Vision 快速入門導覽課程」中的設定說明操作。詳情請參閱 Vision Node.js API 參考說明文件。
如要向 Vision 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。
// 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
在試用這個範例之前,請先按照Python「使用用戶端程式庫的 Vision 快速入門導覽課程」中的設定說明操作。詳情請參閱 Vision Python API 參考說明文件。
如要向 Vision 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。
def detect_crop_hints(path):
"""Detects crop hints in 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)
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(f"\nCrop Hint: {n}")
vertices = [
f"({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)
)
其他語言
C#: 請按照用戶端程式庫頁面上的 C# 設定說明操作, 然後前往 .NET 適用的 Vision 參考說明文件。
PHP: 請按照用戶端程式庫頁面的 PHP 設定說明操作, 然後前往 PHP 適用的 Vision 參考文件。
Ruby: 請按照用戶端程式庫頁面的 Ruby 設定說明操作, 然後前往 Ruby 適用的 Vision 參考說明文件。
偵測遠端圖片的裁剪提示
您可以透過 Vision API,對位於 Cloud Storage 或網路上的遠端圖片檔案執行特徵偵測。如要傳送遠端檔案要求,請在要求內文中指定檔案的網頁網址或 Cloud Storage URI。
REST
使用任何要求資料之前,請先替換以下項目:
欄位專屬注意事項:
HTTP 方法和網址:
POST https://vision.googleapis.com/v1/images:annotate
JSON 要求主體:
{ "requests": [ { "image": { "source": { "gcsImageUri": "CLOUD_STORAGE_IMAGE_URI" } }, "features": [ { "type": "CROP_HINTS" } ], "imageContext": { "cropHintsParams": { "aspectRatios": [ 2.0 ] } } } ] }
如要傳送要求,請選擇以下其中一個選項:
curl
將要求主體儲存在名為 request.json
的檔案中,然後執行下列指令:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: PROJECT_ID" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://vision.googleapis.com/v1/images:annotate"
PowerShell
將要求主體儲存在名為 request.json
的檔案中,然後執行下列指令:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }
Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://vision.googleapis.com/v1/images:annotate" | Select-Object -Expand Content
如果要求成功,伺服器會傳回 200 OK
HTTP 狀態碼與 JSON 格式的回應。
回覆:
{ "responses": [ { "cropHintsAnnotation": { "cropHints": [ { "boundingPoly": { "vertices": [ { "y": 520 }, { "x": 2369, "y": 520 }, { "x": 2369, "y": 1729 }, { "y": 1729 } ] }, "confidence": 0.79999995, "importanceFraction": 0.66999996 } ] } } ] }
Java
在試用這個範例之前,請先按照Java「使用用戶端程式庫的 Vision 快速入門導覽課程」中的設定說明操作。詳情請參閱 Vision Java API 參考說明文件。
如要向 Vision 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。
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
在試用這個範例之前,請先按照Go「使用用戶端程式庫的 Vision 快速入門導覽課程」中的設定說明操作。詳情請參閱 Vision Go API 參考說明文件。
如要向 Vision 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。
// 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
在試用這個範例之前,請先按照Node.js「使用用戶端程式庫的 Vision 快速入門導覽課程」中的設定說明操作。詳情請參閱 Vision Node.js API 參考說明文件。
如要向 Vision 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。
// 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
在試用這個範例之前,請先按照Python「使用用戶端程式庫的 Vision 快速入門導覽課程」中的設定說明操作。詳情請參閱 Vision Python API 參考說明文件。
如要向 Vision 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。
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(f"\nCrop Hint: {n}")
vertices = [
f"({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
如要執行文字偵測,請使用 gcloud ml vision suggest-crop
指令,如下列範例所示:
gcloud ml vision suggest-crop gs://cloud-samples-data/vision/crop_hints/bubble.jpeg
其他語言
C#: 請按照用戶端程式庫頁面上的 C# 設定說明操作, 然後前往 .NET 適用的 Vision 參考說明文件。
PHP: 請按照用戶端程式庫頁面的 PHP 設定說明操作, 然後前往 PHP 適用的 Vision 參考文件。
Ruby: 請按照用戶端程式庫頁面的 Ruby 設定說明操作, 然後前往 Ruby 適用的 Vision 參考說明文件。
立即試用
請試試下方的裁剪提示偵測功能。你可以使用已指定的圖片 (gs://cloud-samples-data/vision/crop_hints/bubble.jpeg
),也可以指定自己的圖片。選取「Execute」,傳送要求。

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