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MLKit face detection demo explanation code snippet
implementation 'com.google.firebase:firebase-ml-vision:18.0.1'
implementation 'com.google.firebase:firebase-ml-vision-face-model:17.0.2'
<meta-data
android:name="com.google.firebase.ml.vision.DEPENDENCIES"
android:value="face" />
// To initialise the detector
FirebaseVisionFaceDetectorOptions options =
new FirebaseVisionFaceDetectorOptions.Builder()
.setPerformanceMode(FirebaseVisionFaceDetectorOptions.ACCURATE)
.setClassificationMode(FirebaseVisionFaceDetectorOptions.ALL_CLASSIFICATIONS)
.enableTracking()
.build();
FirebaseVisionFaceDetector detector = FirebaseVision.getInstance()
.getVisionFaceDetector(options);
// To create the FirebaseVisionImage
FirebaseVisionImageMetadata metadata =
new FirebaseVisionImageMetadata.Builder()
.setFormat(FirebaseVisionImageMetadata.IMAGE_FORMAT_NV21)
.setWidth(frameMetadata.getWidth())
.setHeight(frameMetadata.getHeight())
.setRotation(frameMetadata.getRotation())
.build();
Bitmap bitmap = BitmapUtils.getBitmap(data, frameMetadata);
FirebaseVisionImage firebaseVisionImage=FirebaseVisionImage.fromByteBuffer(data, metadata);
// To connect the camera resource with the detector
mCameraSource = new CameraSource(this, barcodeOverlay);
mCameraSource.setFacing(CameraSource.CAMERA_FACING_FRONT);
// To draw only the bounding rect around the face in the canvas
faceDetectionProcessor = new FaceDetectionProcessor(detector);
/* To plot the landmarks of the face in the canvas
For this you have to set ContourMode attribute as ALL_CONTOURS by using
setContourMode(FirebaseVisionFaceDetectorOptions.ALL_CONTOURS) */
faceDetectionProcessor = new FaceContourDetectorProcessor(detector);
// Callback interface to receive the result
faceDetectionProcessor.setFaceDetectionResultListener(getFaceDetectionListener());
mCameraSource.setMachineLearningFrameProcessor(faceDetectionProcessor);
// To detect the faces from the image
@Override
protected Task<List<FirebaseVisionFace>> detectInImage(FirebaseVisionImage image) {
return detector.detectInImage(image);
}
// To decode the face detection results
FaceDetectionResultListener faceDetectionResultListener = new FaceDetectionResultListener() {
@Override
public void onSuccess(@Nullable Bitmap originalCameraImage, @NonNull List<FirebaseVisionFace> faces,
@NonNull FrameMetadata frameMetadata, @NonNull GraphicOverlay graphicOverlay) {
boolean isEnable;
isEnable = faces.size() > 0;
for (FirebaseVisionFace face : faces){
// To get the results
Log.d(TAG, "Face bounds : " + face.getBoundingBox());
// To get this, we have to set the ClassificationMode attribute as ALL_CLASSIFICATIONS
Log.d(TAG, "Left eye open probability : " + face.getLeftEyeOpenProbability());
Log.d(TAG, "Right eye open probability : " + face.getRightEyeOpenProbability());
Log.d(TAG, "Smiling probability : " + face.getSmilingProbability());
// To get this, we have to enableTracking
Log.d(TAG, "Face ID : " + face.getTrackingId());
}
}
@Override
public void onFailure(@NonNull Exception e) {
}
};
// To connect the camera resource with the detector
mCameraSource = new CameraSource(this, barcodeOverlay);
mCameraSource.setFacing(CameraSource.CAMERA_FACING_FRONT);
// Initialise & set the processor
mCameraSource.setMachineLearningFrameProcessor(faceDetectionProcessor);
// To draw only the bounding rect around the face in the canvas
faceDetectionProcessor = new FaceDetectionProcessor(detector);
faceDetectionProcessor.setFaceDetectionResultListener(getFaceDetectionListener());
mCameraSource.setMachineLearningFrameProcessor(faceDetectionProcessor);
/* To plot the landmarks of the face in the canvas
For this you have to set ContourMode attribute as ALL_CONTOURS by using
setContourMode(FirebaseVisionFaceDetectorOptions.ALL_CONTOURS) */
faceDetectionProcessor = new FaceContourDetectorProcessor(detector);
faceDetectionProcessor.setFaceDetectionResultListener(getFaceDetectionListener());
mCameraSource.setMachineLearningFrameProcessor(faceDetectionProcessor);
implementation 'com.google.firebase:firebase-ml-vision:18.0.1'
implementation 'com.google.firebase:firebase-ml-vision-face-model:17.0.2'
<meta-data
android:name="com.google.firebase.ml.vision.DEPENDENCIES"
android:value="face" />
// To initialise the detector
FirebaseVisionFaceDetectorOptions options =
new FirebaseVisionFaceDetectorOptions.Builder()
.setPerformanceMode(FirebaseVisionFaceDetectorOptions.ACCURATE)
.setClassificationMode(FirebaseVisionFaceDetectorOptions.ALL_CLASSIFICATIONS)
.enableTracking()
.build();
FirebaseVisionFaceDetector detector = FirebaseVision.getInstance()
.getVisionFaceDetector(options);
// To create the FirebaseVisionImage
FirebaseVisionImageMetadata metadata =
new FirebaseVisionImageMetadata.Builder()
.setFormat(FirebaseVisionImageMetadata.IMAGE_FORMAT_NV21)
.setWidth(frameMetadata.getWidth())
.setHeight(frameMetadata.getHeight())
.setRotation(frameMetadata.getRotation())
.build();
Bitmap bitmap = BitmapUtils.getBitmap(data, frameMetadata);
FirebaseVisionImage firebaseVisionImage=FirebaseVisionImage.fromByteBuffer(data, metadata);
// To connect the camera resource with the detector
mCameraSource = new CameraSource(this, barcodeOverlay);
mCameraSource.setFacing(CameraSource.CAMERA_FACING_FRONT);
// To draw only the bounding rect around the face in the canvas
faceDetectionProcessor = new FaceDetectionProcessor(detector);
/* To plot the landmarks of the face in the canvas
For this you have to set ContourMode attribute as ALL_CONTOURS by using
setContourMode(FirebaseVisionFaceDetectorOptions.ALL_CONTOURS) */
faceDetectionProcessor = new FaceContourDetectorProcessor(detector);
// Callback interface to receive the result
faceDetectionProcessor.setFaceDetectionResultListener(getFaceDetectionListener());
mCameraSource.setMachineLearningFrameProcessor(faceDetectionProcessor);
// To detect the faces from the image
@Override
protected Task<List<FirebaseVisionFace>> detectInImage(FirebaseVisionImage image) {
return detector.detectInImage(image);
}
// To decode the face detection results
FaceDetectionResultListener faceDetectionResultListener = new FaceDetectionResultListener() {
@Override
public void onSuccess(@Nullable Bitmap originalCameraImage, @NonNull List<FirebaseVisionFace> faces,
@NonNull FrameMetadata frameMetadata, @NonNull GraphicOverlay graphicOverlay) {
boolean isEnable;
isEnable = faces.size() > 0;
for (FirebaseVisionFace face : faces){
// To get the results
Log.d(TAG, "Face bounds : " + face.getBoundingBox());
// To get this, we have to set the ClassificationMode attribute as ALL_CLASSIFICATIONS
Log.d(TAG, "Left eye open probability : " + face.getLeftEyeOpenProbability());
Log.d(TAG, "Right eye open probability : " + face.getRightEyeOpenProbability());
Log.d(TAG, "Smiling probability : " + face.getSmilingProbability());
// To get this, we have to enableTracking
Log.d(TAG, "Face ID : " + face.getTrackingId());
}
}
@Override
public void onFailure(@NonNull Exception e) {
}
};
// To connect the camera resource with the detector
mCameraSource = new CameraSource(this, barcodeOverlay);
mCameraSource.setFacing(CameraSource.CAMERA_FACING_FRONT);
// Initialise & set the processor
mCameraSource.setMachineLearningFrameProcessor(faceDetectionProcessor);
// To draw only the bounding rect around the face in the canvas
faceDetectionProcessor = new FaceDetectionProcessor(detector);
faceDetectionProcessor.setFaceDetectionResultListener(getFaceDetectionListener());
mCameraSource.setMachineLearningFrameProcessor(faceDetectionProcessor);
/* To plot the landmarks of the face in the canvas
For this you have to set ContourMode attribute as ALL_CONTOURS by using
setContourMode(FirebaseVisionFaceDetectorOptions.ALL_CONTOURS) */
faceDetectionProcessor = new FaceContourDetectorProcessor(detector);
faceDetectionProcessor.setFaceDetectionResultListener(getFaceDetectionListener());
mCameraSource.setMachineLearningFrameProcessor(faceDetectionProcessor);
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