private void detectFaces()

in mlkit/app/src/main/java/com/google/firebase/example/mlkit/FaceDetectionActivity.java [29:94]
44 lines of code
6 McCabe index (conditional complexity)

    private void detectFaces(FirebaseVisionImage image) {
        // [START set_detector_options]
        FirebaseVisionFaceDetectorOptions options =
                new FirebaseVisionFaceDetectorOptions.Builder()
                        .setClassificationMode(FirebaseVisionFaceDetectorOptions.ACCURATE)
                        .setLandmarkMode(FirebaseVisionFaceDetectorOptions.ALL_LANDMARKS)
                        .setClassificationMode(FirebaseVisionFaceDetectorOptions.ALL_CLASSIFICATIONS)
                        .setMinFaceSize(0.15f)
                        .enableTracking()
                        .build();
        // [END set_detector_options]

        // [START get_detector]
        FirebaseVisionFaceDetector detector = FirebaseVision.getInstance()
                .getVisionFaceDetector(options);
        // [END get_detector]

        // [START fml_run_detector]
        Task<List<FirebaseVisionFace>> result =
                detector.detectInImage(image)
                        .addOnSuccessListener(
                                new OnSuccessListener<List<FirebaseVisionFace>>() {
                                    @Override
                                    public void onSuccess(List<FirebaseVisionFace> faces) {
                                        // Task completed successfully
                                        // [START_EXCLUDE]
                                        // [START get_face_info]
                                        for (FirebaseVisionFace face : faces) {
                                            Rect bounds = face.getBoundingBox();
                                            float rotY = face.getHeadEulerAngleY();  // Head is rotated to the right rotY degrees
                                            float rotZ = face.getHeadEulerAngleZ();  // Head is tilted sideways rotZ degrees

                                            // If landmark detection was enabled (mouth, ears, eyes, cheeks, and
                                            // nose available):
                                            FirebaseVisionFaceLandmark leftEar = face.getLandmark(FirebaseVisionFaceLandmark.LEFT_EAR);
                                            if (leftEar != null) {
                                                FirebaseVisionPoint leftEarPos = leftEar.getPosition();
                                            }

                                            // If classification was enabled:
                                            if (face.getSmilingProbability() != FirebaseVisionFace.UNCOMPUTED_PROBABILITY) {
                                                float smileProb = face.getSmilingProbability();
                                            }
                                            if (face.getRightEyeOpenProbability() != FirebaseVisionFace.UNCOMPUTED_PROBABILITY) {
                                                float rightEyeOpenProb = face.getRightEyeOpenProbability();
                                            }

                                            // If face tracking was enabled:
                                            if (face.getTrackingId() != FirebaseVisionFace.INVALID_ID) {
                                                int id = face.getTrackingId();
                                            }
                                        }
                                        // [END get_face_info]
                                        // [END_EXCLUDE]
                                    }
                                })
                        .addOnFailureListener(
                                new OnFailureListener() {
                                    @Override
                                    public void onFailure(@NonNull Exception e) {
                                        // Task failed with an exception
                                        // ...
                                    }
                                });
        // [END fml_run_detector]
    }