I'm a complete beginner to android studio mobile development. and This is the code i've been using so far.
I want to detect if a persons eyes are closed or not real time. I'm using google ml kit. They have provided most of the code but not clear about passing the live camera view into the process(image).
public class EyeDetection extends AppCompatActivity {
private ListenableFuture<ProcessCameraProvider> cameraProviderFuture;
PreviewView previewView;
VideoView videoView;
@Override
protected void onCreate(@Nullable Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_eye_detection);
previewView = findViewById(R.id.previewView);
videoView = findViewById(R.id.video_view);
String videoPath = "android.resource://"+getPackageName()+ "/" + R.raw.videoplayback;
Uri uri = Uri.parse(videoPath);
videoView.setVideoURI(uri);
MediaController mediaController = new MediaController(this);
videoView.setMediaController(mediaController);
mediaController.setAnchorView(videoView);
// FaceDetectorOptions realTimeOpts =
// new FaceDetectorOptions.Builder()
// .setContourMode(FaceDetectorOptions.CONTOUR_MODE_ALL)
// .build();
cameraProviderFuture = ProcessCameraProvider.getInstance(this);
cameraProviderFuture.addListener(() -> {
try {
ProcessCameraProvider cameraProvider = cameraProviderFuture.get();
bindPreview(cameraProvider);
} catch (ExecutionException | InterruptedException e) {
// No errors need to be handled for this Future.
// This should never be reached.
}
}, ContextCompat.getMainExecutor(this));
}
// private class YourAnalyzer implements ImageAnalysis.Analyzer {
//
// @Override
// public void analyze(ImageProxy imageProxy) {
// Image mediaImage = imageProxy.getImage();
// if (mediaImage != null) {
// InputImage image =
// InputImage.fromMediaImage(mediaImage, imageProxy.getImageInfo().getRotationDegrees());
// // Pass image to an ML Kit Vision API
// // ...
// }
// }
//
// }
void bindPreview(@NonNull ProcessCameraProvider cameraProvider) {
Preview preview = new Preview.Builder()
.build();
mlFaceDetector(preview);
CameraSelector cameraSelector = new CameraSelector.Builder()
.requireLensFacing(CameraSelector.LENS_FACING_FRONT)
.build();
preview.setSurfaceProvider(previewView.getSurfaceProvider());
Camera camera = cameraProvider.bindToLifecycle((LifecycleOwner)this, cameraSelector, preview);
// For performing operations that affect all outputs.
CameraControl cameraControl = camera.getCameraControl();
// // For querying information and states.
// CameraInfo cameraInfo = camera.getCameraInfo();
cameraControl.enableTorch(true);
}
void mlFaceDetector(Preview preview) {
FaceDetectorOptions highAccuracyOpts =
new FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_ALL)
.setClassificationMode(FaceDetectorOptions.CLASSIFICATION_MODE_ALL)
.build();
FaceDetector detector = FaceDetection.getClient(highAccuracyOpts);
Task<List<Face>> result =
detector.process(image) // this is where the issue is
.addOnSuccessListener(
new OnSuccessListener<List<Face>>() {
@Override
public void onSuccess(List<Face> faces) {
// Task completed successfully
// ...
}
})
.addOnFailureListener(
new OnFailureListener() {
@Override
public void onFailure(@NonNull Exception e) {
// Task failed with an exception
// ...
}
});
}
}
