Anda dapat menggunakan ML Kit untuk mengenali landmark dalam gambar.
Sebelum memulai
- Tambahkan Firebase ke project Android jika belum melakukannya.
- Tambahkan dependensi untuk library Android ML Kit ke file Gradle modul (level aplikasi), biasanya
app/build.gradle
:apply plugin: 'com.android.application' apply plugin: 'com.google.gms.google-services' dependencies { // ... implementation 'com.google.firebase:firebase-ml-vision:24.0.3' }
-
Jika belum mengaktifkan API berbasis Cloud untuk project, lakukan sekarang:
- Buka halaman ML Kit API pada Firebase console.
-
Jika belum mengupgrade project ke paket harga Blaze, klik Upgrade untuk melakukannya. (Anda akan diminta untuk mengupgrade hanya jika project tersebut tidak menggunakan paket Blaze.)
Hanya project tingkat Blaze yang dapat menggunakan API berbasis Cloud.
- Jika API berbasis Cloud belum diaktifkan, klik Aktifkan API berbasis Cloud.
Mengonfigurasi detektor bangunan terkenal
Secara default, detektor Cloud menggunakan model
versi STABLE
dan menampilkan hingga 10 hasil. Jika ingin mengubah salah satu setelan ini,
tentukan dengan objek FirebaseVisionCloudDetectorOptions
.
Misalnya, untuk mengubah kedua setelan default, bangun objek FirebaseVisionCloudDetectorOptions
seperti pada contoh berikut:
Java
FirebaseVisionCloudDetectorOptions options = new FirebaseVisionCloudDetectorOptions.Builder() .setModelType(FirebaseVisionCloudDetectorOptions.LATEST_MODEL) .setMaxResults(15) .build();
Kotlin
val options = FirebaseVisionCloudDetectorOptions.Builder() .setModelType(FirebaseVisionCloudDetectorOptions.LATEST_MODEL) .setMaxResults(15) .build()
Untuk menggunakan setelan default, Anda dapat
menggunakan FirebaseVisionCloudDetectorOptions.DEFAULT
pada langkah berikutnya.
Menjalankan detektor tempat terkenal
Untuk mengenali tempat terkenal dalam gambar, buat objekFirebaseVisionImage
dari Bitmap
, media.Image
, ByteBuffer
, array byte, atau file
di perangkat. Lalu, teruskan objek FirebaseVisionImage
ke metode detectInImage
FirebaseVisionCloudLandmarkDetector
.
Buat objek
FirebaseVisionImage
dari gambar Anda.-
Untuk membuat objek
FirebaseVisionImage
dari objekmedia.Image
, seperti saat mengambil gambar dari kamera perangkat, teruskan objekmedia.Image
dan nilai rotasi gambar keFirebaseVisionImage.fromMediaImage()
.Jika Anda menggunakan library CameraX, class
OnImageCapturedListener
danImageAnalysis.Analyzer
menghitung nilai rotasi, sehingga Anda hanya perlu mengonversi rotasi ke salah satu konstantaROTATION_
ML Kit sebelum memanggilFirebaseVisionImage.fromMediaImage()
: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 Kit Vision API // ... } }
Kotlin
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 Kit Vision API // ... } } }
Jika tidak menggunakan library kamera yang memberikan nilai rotasi gambar, Anda dapat menghitungnya dari rotasi perangkat dan orientasi sensor kamera pada perangkat:
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; }
Kotlin
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 }
Lalu, teruskan objek
media.Image
dan nilai rotasi keFirebaseVisionImage.fromMediaImage()
:Java
FirebaseVisionImage image = FirebaseVisionImage.fromMediaImage(mediaImage, rotation);
Kotlin
val image = FirebaseVisionImage.fromMediaImage(mediaImage, rotation)
- Untuk membuat objek
FirebaseVisionImage
dari URI file, teruskan konteks aplikasi dan URI file keFirebaseVisionImage.fromFilePath()
. Hal ini berguna saat Anda menggunakan intentACTION_GET_CONTENT
untuk meminta pengguna memilih gambar dari aplikasi galeri mereka.Java
FirebaseVisionImage image; try { image = FirebaseVisionImage.fromFilePath(context, uri); } catch (IOException e) { e.printStackTrace(); }
Kotlin
val image: FirebaseVisionImage try { image = FirebaseVisionImage.fromFilePath(context, uri) } catch (e: IOException) { e.printStackTrace() }
- Untuk membuat objek
FirebaseVisionImage
dariByteBuffer
atau array byte, pertama-tama hitung rotasi gambar seperti yang dijelaskan di atas untuk inputmedia.Image
.Lalu, buat objek
FirebaseVisionImageMetadata
yang berisi tinggi, lebar, format encoding warna, dan rotasi gambar: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();
Kotlin
val metadata = FirebaseVisionImageMetadata.Builder() .setWidth(480) // 480x360 is typically sufficient for .setHeight(360) // image recognition .setFormat(FirebaseVisionImageMetadata.IMAGE_FORMAT_NV21) .setRotation(rotation) .build()
Gunakan buffering atau array, dan objek metadata, untuk membuat objek
FirebaseVisionImage
:Java
FirebaseVisionImage image = FirebaseVisionImage.fromByteBuffer(buffer, metadata); // Or: FirebaseVisionImage image = FirebaseVisionImage.fromByteArray(byteArray, metadata);
Kotlin
val image = FirebaseVisionImage.fromByteBuffer(buffer, metadata) // Or: val image = FirebaseVisionImage.fromByteArray(byteArray, metadata)
- Untuk membuat objek
FirebaseVisionImage
dari objekBitmap
:Java
FirebaseVisionImage image = FirebaseVisionImage.fromBitmap(bitmap);
Kotlin
val image = FirebaseVisionImage.fromBitmap(bitmap)
Bitmap
harus berposisi tegak, tanpa perlu rotasi tambahan.
-
Dapatkan instance
FirebaseVisionCloudLandmarkDetector
:Java
FirebaseVisionCloudLandmarkDetector detector = FirebaseVision.getInstance() .getVisionCloudLandmarkDetector(); // Or, to change the default settings: // FirebaseVisionCloudLandmarkDetector detector = FirebaseVision.getInstance() // .getVisionCloudLandmarkDetector(options);
Kotlin
val detector = FirebaseVision.getInstance() .visionCloudLandmarkDetector // Or, to change the default settings: // val detector = FirebaseVision.getInstance() // .getVisionCloudLandmarkDetector(options)
Terakhir, teruskan gambar ke metode
detectInImage
: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 // ... } });
Kotlin
val result = detector.detectInImage(image) .addOnSuccessListener { firebaseVisionCloudLandmarks -> // Task completed successfully // ... } .addOnFailureListener { e -> // Task failed with an exception // ... }
Mendapatkan informasi tentang tempat terkenal yang dikenali
Jika operasi pengenalan tempat terkenal berhasil, daftar objekFirebaseVisionCloudLandmark
akan diteruskan ke pemroses peristiwa sukses. Setiap objek FirebaseVisionCloudLandmark
mewakili tempat terkenal yang dikenali
dalam gambar. Untuk setiap tempat terkenal, Anda bisa mendapatkan koordinat pembatasnya pada gambar input tersebut, nama tempat terkenal tersebut, garis lintang dan bujurnya, ID entity Pustaka Pengetahuannya (jika ada), dan skor keyakinan kecocokannya. Contoh:
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(); } }
Kotlin
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 } }
Langkah berikutnya
- Sebelum men-deploy aplikasi yang menggunakan Cloud API ke lingkungan production, Anda harus mengambil beberapa langkah tambahan untuk mencegah dan mengurangi edampak akses API tanpa izin.