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本頁面由 Cloud Translation API 翻譯而成。

在 Android 上使用 Firebase ML 辨識地標

可以使用 Firebase ML 辨識圖片中的知名地標。

事前準備

如果還沒試過將 Firebase 新增至您的 Android 專案。
在模組 (應用程式層級) Gradle 檔案中 (通常為 <project>/<app-module>/build.gradle.kts 或 <project>/<app-module>/build.gradle)、為 Android 專用的 Firebase ML Vision 程式庫新增依附元件。建議您使用 Firebase Android BoM敬上管理程式庫版本管理
```
dependencies {
    // Import the BoM for the Firebase platform
    implementation(platform("com.google.firebase:firebase-bom:33.2.0"))

    // Add the dependency for the Firebase ML Vision library
    // When using the BoM, you don't specify versions in Firebase library dependencies
    implementation 'com.google.firebase:firebase-ml-vision'
}
```
只要使用 Firebase Android BoM，應用程式一律會使用相容的 Firebase Android 程式庫版本。
(替代做法) 新增 Firebase 程式庫依附元件，「不使用」 BoM

如果選擇不使用 Firebase BoM，請指定各個 Firebase 程式庫版本都屬於依附元件行

請注意，如果您在應用程式中使用多個 Firebase 程式庫，強烈建議您建議使用 BoM 管理程式庫版本，確保所有版本相容。
```
dependencies {
    // Add the dependency for the Firebase ML Vision library
    // When NOT using the BoM, you must specify versions in Firebase library dependencies
    implementation 'com.google.firebase:firebase-ml-vision:24.1.0'
}
```
敬上
在尋找 Kotlin 專用的程式庫模組嗎？距離開始還有 2023 年 10 月 (Firebase BoM 32.5.0)，Kotlin 和 Java 開發人員皆可依附於主要程式庫模組 (詳情請參閱這項計畫的常見問題)。
如果您尚未為專案啟用雲端式 API，請先啟用現在：
1. 開啟 Firebase ML Firebase 控制台的 API 頁面。
2. 如果您尚未將專案升級至 Blaze 定價方案，請按一下如要這麼做，請升級。(只有在您的專案並未採用 Blaze 方案)。
  
  只有 Blaze 層級的專案可以使用以雲端為基礎的 API。
3. 如果尚未啟用雲端式 API，請按一下「Enable Cloud-based API」(啟用雲端式 API) API
，瞭解如何調查及移除這項存取權。
部署至使用 Cloud API 的正式版應用程式之前，您應先完成防範及降低

設定地標偵測工具

根據預設，Cloud 偵測工具會使用 STABLE 版本的最多傳回 10 個結果如果您要變更設定，請使用 FirebaseVisionCloudDetectorOptions 物件。

舉例來說，如要變更這兩項預設設定，請建立 FirebaseVisionCloudDetectorOptions 物件，如下所示範例：

Kotlin+KTX

val options = FirebaseVisionCloudDetectorOptions.Builder()
    .setModelType(FirebaseVisionCloudDetectorOptions.LATEST_MODEL)
    .setMaxResults(15)
    .build()MainActivity.kt

Java

FirebaseVisionCloudDetectorOptions options =
        new FirebaseVisionCloudDetectorOptions.Builder()
                .setModelType(FirebaseVisionCloudDetectorOptions.LATEST_MODEL)
                .setMaxResults(15)
                .build();MainActivity.java

如要使用預設設定，您可以 FirebaseVisionCloudDetectorOptions.DEFAULT。

執行地標偵測工具

如要辨識圖片中的地標，請建立 FirebaseVisionImage 物件從 Bitmap、media.Image、ByteBuffer、位元組陣列或裝置。然後，將 FirebaseVisionImage 物件傳遞至 FirebaseVisionCloudLandmarkDetector 的 detectInImage 方法。

使用圖片建立 FirebaseVisionImage 物件。

要使用 FirebaseVisionImage 物件 media.Image 物件，例如從裝置的相機，請傳遞 media.Image 物件和圖片的旋轉至 FirebaseVisionImage.fromMediaImage()。

如果您使用 CameraX 程式庫、OnImageCapturedListener 和 ImageAnalysis.Analyzer 類別會計算旋轉值因此，您只需將旋轉角度轉換為 Firebase ML 的呼叫前 ROTATION_ 常數 FirebaseVisionImage.fromMediaImage():

Kotlin+KTX

private class YourImageAnalyzer : ImageAnalysis.Analyzer {
    private fun degreesToFirebaseRotation(degrees: Int): Int = when(degrees) {
        0 -> FirebaseVisionImageMetadata.ROTATION_0
        90 -> FirebaseVisionImageMetadata.ROTATION_90
        180 -> FirebaseVisionImageMetadata.ROTATION_180
        270 -> FirebaseVisionImageMetadata.ROTATION_270
        else -> throw Exception("Rotation must be 0, 90, 180, or 270.")
    }

    override fun analyze(imageProxy: ImageProxy?, degrees: Int) {
        val mediaImage = imageProxy?.image
        val imageRotation = degreesToFirebaseRotation(degrees)
        if (mediaImage != null) {
            val image = FirebaseVisionImage.fromMediaImage(mediaImage, imageRotation)
            // Pass image to an ML Vision API
            // ...
        }
    }
}

Java

private class YourAnalyzer implements ImageAnalysis.Analyzer {

    private int degreesToFirebaseRotation(int degrees) {
        switch (degrees) {
            case 0:
                return FirebaseVisionImageMetadata.ROTATION_0;
            case 90:
                return FirebaseVisionImageMetadata.ROTATION_90;
            case 180:
                return FirebaseVisionImageMetadata.ROTATION_180;
            case 270:
                return FirebaseVisionImageMetadata.ROTATION_270;
            default:
                throw new IllegalArgumentException(
                        "Rotation must be 0, 90, 180, or 270.");
        }
    }

    @Override
    public void analyze(ImageProxy imageProxy, int degrees) {
        if (imageProxy == null || imageProxy.getImage() == null) {
            return;
        }
        Image mediaImage = imageProxy.getImage();
        int rotation = degreesToFirebaseRotation(degrees);
        FirebaseVisionImage image =
                FirebaseVisionImage.fromMediaImage(mediaImage, rotation);
        // Pass image to an ML Vision API
        // ...
    }
}

如果您沒有使用相機程式庫來提供圖像旋轉角度，可根據裝置旋轉角度和相機方向計算感應器：

Kotlin+KTX

private val ORIENTATIONS = SparseIntArray()

init {
    ORIENTATIONS.append(Surface.ROTATION_0, 90)
    ORIENTATIONS.append(Surface.ROTATION_90, 0)
    ORIENTATIONS.append(Surface.ROTATION_180, 270)
    ORIENTATIONS.append(Surface.ROTATION_270, 180)
}
/**
 * Get the angle by which an image must be rotated given the device's current
 * orientation.
 */
@RequiresApi(api = Build.VERSION_CODES.LOLLIPOP)
@Throws(CameraAccessException::class)
private fun getRotationCompensation(cameraId: String, activity: Activity, context: Context): Int {
    // Get the device's current rotation relative to its "native" orientation.
    // Then, from the ORIENTATIONS table, look up the angle the image must be
    // rotated to compensate for the device's rotation.
    val deviceRotation = activity.windowManager.defaultDisplay.rotation
    var rotationCompensation = ORIENTATIONS.get(deviceRotation)

    // On most devices, the sensor orientation is 90 degrees, but for some
    // devices it is 270 degrees. For devices with a sensor orientation of
    // 270, rotate the image an additional 180 ((270 + 270) % 360) degrees.
    val cameraManager = context.getSystemService(CAMERA_SERVICE) as CameraManager
    val sensorOrientation = cameraManager
        .getCameraCharacteristics(cameraId)
        .get(CameraCharacteristics.SENSOR_ORIENTATION)!!
    rotationCompensation = (rotationCompensation + sensorOrientation + 270) % 360

    // Return the corresponding FirebaseVisionImageMetadata rotation value.
    val result: Int
    when (rotationCompensation) {
        0 -> result = FirebaseVisionImageMetadata.ROTATION_0
        90 -> result = FirebaseVisionImageMetadata.ROTATION_90
        180 -> result = FirebaseVisionImageMetadata.ROTATION_180
        270 -> result = FirebaseVisionImageMetadata.ROTATION_270
        else -> {
            result = FirebaseVisionImageMetadata.ROTATION_0
            Log.e(TAG, "Bad rotation value: $rotationCompensation")
        }
    }
    return result
}VisionImage.kt

Java

private static final SparseIntArray ORIENTATIONS = new SparseIntArray();
static {
    ORIENTATIONS.append(Surface.ROTATION_0, 90);
    ORIENTATIONS.append(Surface.ROTATION_90, 0);
    ORIENTATIONS.append(Surface.ROTATION_180, 270);
    ORIENTATIONS.append(Surface.ROTATION_270, 180);
}

/**
 * Get the angle by which an image must be rotated given the device's current
 * orientation.
 */
@RequiresApi(api = Build.VERSION_CODES.LOLLIPOP)
private int getRotationCompensation(String cameraId, Activity activity, Context context)
        throws CameraAccessException {
    // Get the device's current rotation relative to its "native" orientation.
    // Then, from the ORIENTATIONS table, look up the angle the image must be
    // rotated to compensate for the device's rotation.
    int deviceRotation = activity.getWindowManager().getDefaultDisplay().getRotation();
    int rotationCompensation = ORIENTATIONS.get(deviceRotation);

    // On most devices, the sensor orientation is 90 degrees, but for some
    // devices it is 270 degrees. For devices with a sensor orientation of
    // 270, rotate the image an additional 180 ((270 + 270) % 360) degrees.
    CameraManager cameraManager = (CameraManager) context.getSystemService(CAMERA_SERVICE);
    int sensorOrientation = cameraManager
            .getCameraCharacteristics(cameraId)
            .get(CameraCharacteristics.SENSOR_ORIENTATION);
    rotationCompensation = (rotationCompensation + sensorOrientation + 270) % 360;

    // Return the corresponding FirebaseVisionImageMetadata rotation value.
    int result;
    switch (rotationCompensation) {
        case 0:
            result = FirebaseVisionImageMetadata.ROTATION_0;
            break;
        case 90:
            result = FirebaseVisionImageMetadata.ROTATION_90;
            break;
        case 180:
            result = FirebaseVisionImageMetadata.ROTATION_180;
            break;
        case 270:
            result = FirebaseVisionImageMetadata.ROTATION_270;
            break;
        default:
            result = FirebaseVisionImageMetadata.ROTATION_0;
            Log.e(TAG, "Bad rotation value: " + rotationCompensation);
    }
    return result;
}VisionImage.java

然後，請傳遞 media.Image 物件和將旋轉值轉換為 FirebaseVisionImage.fromMediaImage()：

Kotlin+KTX

val image = FirebaseVisionImage.fromMediaImage(mediaImage, rotation)VisionImage.kt

Java

FirebaseVisionImage image = FirebaseVisionImage.fromMediaImage(mediaImage, rotation);VisionImage.java

如要從檔案 URI 建立 FirebaseVisionImage 物件，請傳遞應用程式環境和檔案 URI FirebaseVisionImage.fromFilePath()。如果您要使用 ACTION_GET_CONTENT 意圖提示使用者選取取自圖片庫應用程式中的圖片。

Kotlin+KTX

val image: FirebaseVisionImage
try {
    image = FirebaseVisionImage.fromFilePath(context, uri)
} catch (e: IOException) {
    e.printStackTrace()
}VisionImage.kt

Java

FirebaseVisionImage image;
try {
    image = FirebaseVisionImage.fromFilePath(context, uri);
} catch (IOException e) {
    e.printStackTrace();
}VisionImage.java

要使用 FirebaseVisionImage 物件 ByteBuffer 或位元組陣列，請先計算圖片旋轉 (方法如上所述) media.Image 輸入欄位。

接著建立 FirebaseVisionImageMetadata 物件包含圖片的高度、寬度、色彩編碼格式和輪替金鑰

Kotlin+KTX

val metadata = FirebaseVisionImageMetadata.Builder()
    .setWidth(480) // 480x360 is typically sufficient for
    .setHeight(360) // image recognition
    .setFormat(FirebaseVisionImageMetadata.IMAGE_FORMAT_NV21)
    .setRotation(rotation)
    .build()VisionImage.kt

Java

FirebaseVisionImageMetadata metadata = new FirebaseVisionImageMetadata.Builder()
        .setWidth(480)   // 480x360 is typically sufficient for
        .setHeight(360)  // image recognition
        .setFormat(FirebaseVisionImageMetadata.IMAGE_FORMAT_NV21)
        .setRotation(rotation)
        .build();VisionImage.java

使用緩衝區或陣列和中繼資料物件 FirebaseVisionImage 物件：

Kotlin+KTX

val image = FirebaseVisionImage.fromByteBuffer(buffer, metadata)
// Or: val image = FirebaseVisionImage.fromByteArray(byteArray, metadata)VisionImage.kt

Java

FirebaseVisionImage image = FirebaseVisionImage.fromByteBuffer(buffer, metadata);
// Or: FirebaseVisionImage image = FirebaseVisionImage.fromByteArray(byteArray, metadata);VisionImage.java

要使用 FirebaseVisionImage 物件 Bitmap 物件：

Kotlin+KTX

val image = FirebaseVisionImage.fromBitmap(bitmap)VisionImage.kt

Java

FirebaseVisionImage image = FirebaseVisionImage.fromBitmap(bitmap);VisionImage.java

Bitmap 物件代表的圖片必須保持直立，不用另外旋轉。

取得 FirebaseVisionCloudLandmarkDetector 的執行個體：

Kotlin+KTX

val detector = FirebaseVision.getInstance()
    .visionCloudLandmarkDetector
// Or, to change the default settings:
// val detector = FirebaseVision.getInstance()
//         .getVisionCloudLandmarkDetector(options)LandmarkRecognitionActivity.kt

Java

FirebaseVisionCloudLandmarkDetector detector = FirebaseVision.getInstance()
        .getVisionCloudLandmarkDetector();
// Or, to change the default settings:
// FirebaseVisionCloudLandmarkDetector detector = FirebaseVision.getInstance()
//         .getVisionCloudLandmarkDetector(options);LandmarkRecognitionActivity.java

最後，將圖片傳遞至 detectInImage 方法：

Kotlin+KTX

val result = detector.detectInImage(image)
    .addOnSuccessListener { firebaseVisionCloudLandmarks ->
        // Task completed successfully
        // ...
    }
    .addOnFailureListener { e ->
        // Task failed with an exception
        // ...
    }LandmarkRecognitionActivity.kt

Java

Task<List<FirebaseVisionCloudLandmark>> result = detector.detectInImage(image)
        .addOnSuccessListener(new OnSuccessListener<List<FirebaseVisionCloudLandmark>>() {
            @Override
            public void onSuccess(List<FirebaseVisionCloudLandmark> firebaseVisionCloudLandmarks) {
                // Task completed successfully
                // ...
            }
        })
        .addOnFailureListener(new OnFailureListener() {
            @Override
            public void onFailure(@NonNull Exception e) {
                // Task failed with an exception
                // ...
            }
        });LandmarkRecognitionActivity.java

取得可辨識的地標相關資訊

如果地標辨識作業成功，系統會顯示 FirebaseVisionCloudLandmark 物件會傳遞到成功事件監聽器。每項 FirebaseVisionCloudLandmark 物件代表圖片。您可以在輸入圖片中取得每個地標的邊界座標地標名稱、經緯度、知識圖譜實體 ID 以及比對結果的可信度分數。例如：

Kotlin+KTX

for (landmark in firebaseVisionCloudLandmarks) {
    val bounds = landmark.boundingBox
    val landmarkName = landmark.landmark
    val entityId = landmark.entityId
    val confidence = landmark.confidence

    // Multiple locations are possible, e.g., the location of the depicted
    // landmark and the location the picture was taken.
    for (loc in landmark.locations) {
        val latitude = loc.latitude
        val longitude = loc.longitude
    }
}LandmarkRecognitionActivity.kt

Java

for (FirebaseVisionCloudLandmark landmark: firebaseVisionCloudLandmarks) {

    Rect bounds = landmark.getBoundingBox();
    String landmarkName = landmark.getLandmark();
    String entityId = landmark.getEntityId();
    float confidence = landmark.getConfidence();

    // Multiple locations are possible, e.g., the location of the depicted
    // landmark and the location the picture was taken.
    for (FirebaseVisionLatLng loc: landmark.getLocations()) {
        double latitude = loc.getLatitude();
        double longitude = loc.getLongitude();
    }
}LandmarkRecognitionActivity.java

後續步驟

部署至使用 Cloud API 的正式版應用程式之前，您應先完成防範及減少未經授權 API 存取的影響