You can use Firebase ML to label objects recognized in an image. See the overview for information about this API's features.
Before you begin
- If you haven't already, add Firebase to your Android project.
-
In your module (app-level) Gradle file
(usually
<project>/<app-module>/build.gradle.kts
or<project>/<app-module>/build.gradle
), add the dependency for the Firebase ML Vision library for Android. We recommend using the Firebase Android BoM to control library versioning.dependencies { // Import the BoM for the Firebase platform implementation(platform("com.google.firebase:firebase-bom:33.4.0")) // 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' }
By using the Firebase Android BoM, your app will always use compatible versions of Firebase Android libraries.
(Alternative) Add Firebase library dependencies without using the BoM
If you choose not to use the Firebase BoM, you must specify each Firebase library version in its dependency line.
Note that if you use multiple Firebase libraries in your app, we strongly recommend using the BoM to manage library versions, which ensures that all versions are compatible.
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' }
-
If you have not already enabled Cloud-based APIs for your project, do so now:
- Open the Firebase ML APIs page of the Firebase console.
-
If you have not already upgraded your project to the Blaze pricing plan, click Upgrade to do so. (You will be prompted to upgrade only if your project isn't on the Blaze plan.)
Only Blaze-level projects can use Cloud-based APIs.
- If Cloud-based APIs aren't already enabled, click Enable Cloud-based APIs.
Now you are ready to label images.
1. Prepare the input image
Create aFirebaseVisionImage
object from your image.
The image labeler runs fastest when you use a Bitmap
or, if you use the
camera2 API, a JPEG-formatted media.Image
, which are recommended when
possible.
-
To create a
FirebaseVisionImage
object from amedia.Image
object, such as when capturing an image from a device's camera, pass themedia.Image
object and the image's rotation toFirebaseVisionImage.fromMediaImage()
.If you use the CameraX library, the
OnImageCapturedListener
andImageAnalysis.Analyzer
classes calculate the rotation value for you, so you just need to convert the rotation to one of Firebase ML'sROTATION_
constants before callingFirebaseVisionImage.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 // ... } }
If you don't use a camera library that gives you the image's rotation, you can calculate it from the device's rotation and the orientation of camera sensor in the device:
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 }
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; }
Then, pass the
media.Image
object and the rotation value toFirebaseVisionImage.fromMediaImage()
:Kotlin+KTX
val image = FirebaseVisionImage.fromMediaImage(mediaImage, rotation)
Java
FirebaseVisionImage image = FirebaseVisionImage.fromMediaImage(mediaImage, rotation);
- To create a
FirebaseVisionImage
object from a file URI, pass the app context and file URI toFirebaseVisionImage.fromFilePath()
. This is useful when you use anACTION_GET_CONTENT
intent to prompt the user to select an image from their gallery app.Kotlin+KTX
val image: FirebaseVisionImage try { image = FirebaseVisionImage.fromFilePath(context, uri) } catch (e: IOException) { e.printStackTrace() }
Java
FirebaseVisionImage image; try { image = FirebaseVisionImage.fromFilePath(context, uri); } catch (IOException e) { e.printStackTrace(); }
- To create a
FirebaseVisionImage
object from aByteBuffer
or a byte array, first calculate the image rotation as described above formedia.Image
input.Then, create a
FirebaseVisionImageMetadata
object that contains the image's height, width, color encoding format, and rotation: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()
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();
Use the buffer or array, and the metadata object, to create a
FirebaseVisionImage
object:Kotlin+KTX
val image = FirebaseVisionImage.fromByteBuffer(buffer, metadata) // Or: val image = FirebaseVisionImage.fromByteArray(byteArray, metadata)
Java
FirebaseVisionImage image = FirebaseVisionImage.fromByteBuffer(buffer, metadata); // Or: FirebaseVisionImage image = FirebaseVisionImage.fromByteArray(byteArray, metadata);
- To create a
FirebaseVisionImage
object from aBitmap
object:Kotlin+KTX
val image = FirebaseVisionImage.fromBitmap(bitmap)
Java
FirebaseVisionImage image = FirebaseVisionImage.fromBitmap(bitmap);
Bitmap
object must be upright, with no additional rotation required.
2. Configure and run the image labeler
To label objects in an image, pass theFirebaseVisionImage
object to the
FirebaseVisionImageLabeler
's processImage
method.
First, get an instance of
FirebaseVisionImageLabeler
.Kotlin+KTX
val labeler = FirebaseVision.getInstance().getCloudImageLabeler() // Or, to set the minimum confidence required: // val options = FirebaseVisionCloudImageLabelerOptions.Builder() // .setConfidenceThreshold(0.7f) // .build() // val labeler = FirebaseVision.getInstance().getCloudImageLabeler(options)
Java
FirebaseVisionImageLabeler labeler = FirebaseVision.getInstance() .getCloudImageLabeler(); // Or, to set the minimum confidence required: // FirebaseVisionCloudImageLabelerOptions options = // new FirebaseVisionCloudImageLabelerOptions.Builder() // .setConfidenceThreshold(0.7f) // .build(); // FirebaseVisionImageLabeler labeler = FirebaseVision.getInstance() // .getCloudImageLabeler(options);
Then, pass the image to the
processImage()
method:Kotlin+KTX
labeler.processImage(image) .addOnSuccessListener { labels -> // Task completed successfully // ... } .addOnFailureListener { e -> // Task failed with an exception // ... }
Java
labeler.processImage(image) .addOnSuccessListener(new OnSuccessListener<List<FirebaseVisionImageLabel>>() { @Override public void onSuccess(List<FirebaseVisionImageLabel> labels) { // Task completed successfully // ... } }) .addOnFailureListener(new OnFailureListener() { @Override public void onFailure(@NonNull Exception e) { // Task failed with an exception // ... } });
3. Get information about labeled objects
If the image labeling operation succeeds, a list ofFirebaseVisionImageLabel
objects will be passed to the
success listener. Each FirebaseVisionImageLabel
object represents something
that was labeled in the image. For each label, you can get the label's text
description, its
Knowledge Graph entity ID
(if available), and the confidence score of the match. For example:
Kotlin+KTX
for (label in labels) {
val text = label.text
val entityId = label.entityId
val confidence = label.confidence
}
Java
for (FirebaseVisionImageLabel label: labels) {
String text = label.getText();
String entityId = label.getEntityId();
float confidence = label.getConfidence();
}
Next steps
- Before you deploy to production an app that uses a Cloud API, you should take some additional steps to prevent and mitigate the effect of unauthorized API access.