Internal error has occurred when executing ML Kit tasks

Question

I'm trying to integrate ARCore with ML Kit in Android Studio as suggested in ARCore documentation official. This is my JAVA code:

ObjectDetector objectDetector = createObjectDetector();
  Image cameraImage = null;
  try {
    cameraImage = frame.acquireCameraImage();
        // Process `cameraImage` using your ML inference model.
        objectDetector.process(InputImage.fromMediaImage(cameraImage, getRotationCompensation("1", this, false)))
                .addOnSuccessListener(
                        new OnSuccessListener<List<DetectedObject>>() {
                          @Override
                          public void onSuccess(List<DetectedObject> detectedObjects) {
                            // Task completed successfully
                            // The list of detected objects contains one item if multiple
                            // object detection wasn't enabled.
                            for (DetectedObject detectedObject : detectedObjects) {
                            Rect boundingBox = detectedObject.getBoundingBox();
                            Integer trackingId = detectedObject.getTrackingId();
                            for (DetectedObject.Label label : detectedObject.getLabels()) {
                              String text = label.getText();
                              if (PredefinedCategory.FOOD.equals(text)) {
                              }
                              int index = label.getIndex();
                              if (PredefinedCategory.FOOD_INDEX == index) {
                              }
                              float confidence = label.getConfidence();
                            }
                            }
                          }
                        })
                .addOnFailureListener(
                        new OnFailureListener() {
                          @Override
                          public void onFailure(@NonNull Exception e) {
                            // Task failed with an exception
                            Log.e("Failure Listener", e.getMessage());
                          }
                        });
      } catch (NotYetAvailableException e) {
        // NotYetAvailableException is an exception that can be expected when the camera is not ready
        // yet. The image may become available on a next frame.
      } catch (RuntimeException e) {
        // A different exception occurred, e.g. DeadlineExceededException, ResourceExhaustedException.
        // Handle this error appropriately.
        Log.e("Error", e.toString());
      } catch (CameraAccessException e) {
        e.printStackTrace();
      } finally {
        if (cameraImage != null) {
          cameraImage.close();
        }
      }

I'm getting the following errors:

Internal error has occurred when executing ML Kit tasks Fatal signal 11 (SIGSEGV), code 1 (SEGV_MAPERR), fault addr 0x4faee70000000 in tid 14906 ...

The error appears because of objectDetector.process(...) but I'm not sure what I did wrong

Answer 1

It worked when I commented the initial closing of the image and closed the image in the OnCompleteListener instead. This is my modified code:

ObjectDetector objectDetector = createObjectDetector();
  Image cameraImage = null;
  try {
    cameraImage = frame.acquireCameraImage();
        // Process `cameraImage` using your ML inference model.
        Image finalCameraImage = cameraImage;
        objectDetector.process(InputImage.fromMediaImage(finalCameraImage, getRotationCompensation("1", this, false)))
                .addOnSuccessListener(
                        new OnSuccessListener<List<DetectedObject>>() {
                          @Override
                          public void onSuccess(List<DetectedObject> detectedObjects) {
                            // Task completed successfully
                            // The list of detected objects contains one item if multiple
                            // object detection wasn't enabled.
                            for (DetectedObject detectedObject : detectedObjects) {
                            Rect boundingBox = detectedObject.getBoundingBox();
                            Log.d("Bounding Box", boundingBox.toString());
                            Integer trackingId = detectedObject.getTrackingId();
                            for (DetectedObject.Label label : detectedObject.getLabels()) {
                              String text = label.getText();
                              if (PredefinedCategory.FOOD.equals(text)) {
                              }
                              int index = label.getIndex();
                              if (PredefinedCategory.FOOD_INDEX == index) {
                              }
                              float confidence = label.getConfidence();
                            }
                            }
                          }
                        })
                .addOnFailureListener(
                        new OnFailureListener() {
                          @Override
                          public void onFailure(@NonNull Exception e) {
                            // Task failed with an exception
                            Log.e("Failure Listener", e.getMessage());
                          }
                        }).addOnCompleteListener(new OnCompleteListener<List<DetectedObject>>() {
      @Override
      public void onComplete(@NonNull Task<List<DetectedObject>> task) {
        finalCameraImage.close();
      }
    });
  } catch (NotYetAvailableException e) {
    // NotYetAvailableException is an exception that can be expected when the camera is not ready
    // yet. The image may become available on a next frame.
  } catch (RuntimeException e) {
    // A different exception occurred, e.g. DeadlineExceededException, ResourceExhaustedException.
    // Handle this error appropriately.
    Log.e("Error", e.toString());
  } catch (CameraAccessException e) {
    e.printStackTrace();
  } finally {
//  if (cameraImage != null) {
//          cameraImage.close();
//        }
      }