Android पर, पसंद के मुताबिक बनाए गए क्लासिफ़िकेशन मॉडल की मदद से, चीज़ों का पता लगाएं, उन्हें ट्रैक करें, और उनकी कैटगरी तय करें

// Specify the name you assigned in the Firebase console.
val remoteModel =
    CustomRemoteModel
        .Builder(FirebaseModelSource.Builder("your_model_name").build())
        .build()

// Specify the name you assigned in the Firebase console.
CustomRemoteModel remoteModel =
    new CustomRemoteModel
        .Builder(new FirebaseModelSource.Builder("your_model_name").build())
        .build();

val downloadConditions = DownloadConditions.Builder()
    .requireWifi()
    .build()
RemoteModelManager.getInstance().download(remoteModel, downloadConditions)
    .addOnSuccessListener {
        // Success.
    }

DownloadConditions downloadConditions = new DownloadConditions.Builder()
        .requireWifi()
        .build();
RemoteModelManager.getInstance().download(remoteModel, downloadConditions)
        .addOnSuccessListener(new OnSuccessListener() {
            @Override
            public void onSuccess(@NonNull Task task) {
                // Success.
            }
        });

// Live detection and tracking
val customObjectDetectorOptions =
        CustomObjectDetectorOptions.Builder(localModel)
        .setDetectorMode(CustomObjectDetectorOptions.STREAM_MODE)
        .enableClassification()
        .setClassificationConfidenceThreshold(0.5f)
        .setMaxPerObjectLabelCount(3)
        .build()

// Multiple object detection in static images
val customObjectDetectorOptions =
        CustomObjectDetectorOptions.Builder(localModel)
        .setDetectorMode(CustomObjectDetectorOptions.SINGLE_IMAGE_MODE)
        .enableMultipleObjects()
        .enableClassification()
        .setClassificationConfidenceThreshold(0.5f)
        .setMaxPerObjectLabelCount(3)
        .build()

val objectDetector =
        ObjectDetection.getClient(customObjectDetectorOptions)

// Live detection and tracking
CustomObjectDetectorOptions customObjectDetectorOptions =
        new CustomObjectDetectorOptions.Builder(localModel)
                .setDetectorMode(CustomObjectDetectorOptions.STREAM_MODE)
                .enableClassification()
                .setClassificationConfidenceThreshold(0.5f)
                .setMaxPerObjectLabelCount(3)
                .build();

// Multiple object detection in static images
CustomObjectDetectorOptions customObjectDetectorOptions =
        new CustomObjectDetectorOptions.Builder(localModel)
                .setDetectorMode(CustomObjectDetectorOptions.SINGLE_IMAGE_MODE)
                .enableMultipleObjects()
                .enableClassification()
                .setClassificationConfidenceThreshold(0.5f)
                .setMaxPerObjectLabelCount(3)
                .build();

ObjectDetector objectDetector =
    ObjectDetection.getClient(customObjectDetectorOptions);

RemoteModelManager.getInstance().isModelDownloaded(remoteModel)
    .addOnSuccessListener { isDownloaded ->
    val optionsBuilder =
        if (isDownloaded) {
            CustomObjectDetectorOptions.Builder(remoteModel)
        } else {
            CustomObjectDetectorOptions.Builder(localModel)
        }
    val customObjectDetectorOptions = optionsBuilder
            .setDetectorMode(CustomObjectDetectorOptions.SINGLE_IMAGE_MODE)
            .enableClassification()
            .setClassificationConfidenceThreshold(0.5f)
            .setMaxPerObjectLabelCount(3)
            .build()
    val objectDetector =
        ObjectDetection.getClient(customObjectDetectorOptions)
}

RemoteModelManager.getInstance().isModelDownloaded(remoteModel)
    .addOnSuccessListener(new OnSuccessListener() {
        @Override
        public void onSuccess(Boolean isDownloaded) {
            CustomObjectDetectorOptions.Builder optionsBuilder;
            if (isDownloaded) {
                optionsBuilder = new CustomObjectDetectorOptions.Builder(remoteModel);
            } else {
                optionsBuilder = new CustomObjectDetectorOptions.Builder(localModel);
            }
            CustomObjectDetectorOptions customObjectDetectorOptions = optionsBuilder
                .setDetectorMode(CustomObjectDetectorOptions.SINGLE_IMAGE_MODE)
                .enableClassification()
                .setClassificationConfidenceThreshold(0.5f)
                .setMaxPerObjectLabelCount(3)
                .build();
            ObjectDetector objectDetector =
                ObjectDetection.getClient(customObjectDetectorOptions);
        }
});

RemoteModelManager.getInstance().download(remoteModel, conditions)
    .addOnSuccessListener {
        // Download complete. Depending on your app, you could enable the ML
        // feature, or switch from the local model to the remote model, etc.
    }

RemoteModelManager.getInstance().download(remoteModel, conditions)
        .addOnSuccessListener(new OnSuccessListener() {
            @Override
            public void onSuccess(Void v) {
              // Download complete. Depending on your app, you could enable
              // the ML feature, or switch from the local model to the remote
              // model, etc.
            }
        });

private class YourImageAnalyzer : ImageAnalysis.Analyzer {

    override fun analyze(imageProxy: ImageProxy) {
        val mediaImage = imageProxy.image
        if (mediaImage != null) {
            val image = InputImage.fromMediaImage(mediaImage, imageProxy.imageInfo.rotationDegrees)
            // Pass image to an ML Kit Vision API
            // ...
        }
    }
}

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
          // ...
        }
    }
}

private val ORIENTATIONS = SparseIntArray()

init {
    ORIENTATIONS.append(Surface.ROTATION_0, 0)
    ORIENTATIONS.append(Surface.ROTATION_90, 90)
    ORIENTATIONS.append(Surface.ROTATION_180, 180)
    ORIENTATIONS.append(Surface.ROTATION_270, 270)
}

/**
 * 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, isFrontFacing: Boolean): 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)

    // Get the device's sensor orientation.
    val cameraManager = activity.getSystemService(CAMERA_SERVICE) as CameraManager
    val sensorOrientation = cameraManager
            .getCameraCharacteristics(cameraId)
            .get(CameraCharacteristics.SENSOR_ORIENTATION)!!

    if (isFrontFacing) {
        rotationCompensation = (sensorOrientation + rotationCompensation) % 360
    } else { // back-facing
        rotationCompensation = (sensorOrientation - rotationCompensation + 360) % 360
    }
    return rotationCompensation
}
MLKitVisionImage.kt

private static final SparseIntArray ORIENTATIONS = new SparseIntArray();
static {
    ORIENTATIONS.append(Surface.ROTATION_0, 0);
    ORIENTATIONS.append(Surface.ROTATION_90, 90);
    ORIENTATIONS.append(Surface.ROTATION_180, 180);
    ORIENTATIONS.append(Surface.ROTATION_270, 270);
}

/**
 * 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, boolean isFrontFacing)
        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);

    // Get the device's sensor orientation.
    CameraManager cameraManager = (CameraManager) activity.getSystemService(CAMERA_SERVICE);
    int sensorOrientation = cameraManager
            .getCameraCharacteristics(cameraId)
            .get(CameraCharacteristics.SENSOR_ORIENTATION);

    if (isFrontFacing) {
        rotationCompensation = (sensorOrientation + rotationCompensation) % 360;
    } else { // back-facing
        rotationCompensation = (sensorOrientation - rotationCompensation + 360) % 360;
    }
    return rotationCompensation;
}

val image = InputImage.fromMediaImage(mediaImage, rotation)
MLKitVisionImage.kt

val image: InputImage
try {
    image = InputImage.fromFilePath(context, uri)
} catch (e: IOException) {
    e.printStackTrace()
}
MLKitVisionImage.kt

val image = InputImage.fromByteBuffer(
        byteBuffer,
        /* image width */ 480,
        /* image height */ 360,
        rotationDegrees,
        InputImage.IMAGE_FORMAT_NV21 // or IMAGE_FORMAT_YV12
)
MLKitVisionImage.kt
// Or:
val image = InputImage.fromByteArray(
        byteArray,
        /* image width */ 480,
        /* image height */ 360,
        rotationDegrees,
        InputImage.IMAGE_FORMAT_NV21 // or IMAGE_FORMAT_YV12
)
MLKitVisionImage.kt

InputImage image = InputImage.fromByteBuffer(byteBuffer,
        /* image width */ 480,
        /* image height */ 360,
        rotationDegrees,
        InputImage.IMAGE_FORMAT_NV21 // or IMAGE_FORMAT_YV12
);
MLKitVisionImage.java
// Or:
InputImage image = InputImage.fromByteArray(
        byteArray,
        /* image width */480,
        /* image height */360,
        rotation,
        InputImage.IMAGE_FORMAT_NV21 // or IMAGE_FORMAT_YV12
);
MLKitVisionImage.java

val image = InputImage.fromBitmap(bitmap, 0)
MLKitVisionImage.kt

objectDetector
    .process(image)
    .addOnFailureListener(e -> {...})
    .addOnSuccessListener(results -> {
        for (detectedObject in results) {
          // ...
        }
    });

objectDetector
    .process(image)
    .addOnFailureListener(e -> {...})
    .addOnSuccessListener(results -> {
        for (DetectedObject detectedObject : results) {
          // ...
        }
    });

// The list of detected objects contains one item if multiple
// object detection wasn't enabled.
for (detectedObject in results) {
    val boundingBox = detectedObject.boundingBox
    val trackingId = detectedObject.trackingId
    for (label in detectedObject.labels) {
      val text = label.text
      val index = label.index
      val confidence = label.confidence
    }
}

// The list of detected objects contains one item if multiple
// object detection wasn't enabled.
for (DetectedObject detectedObject : results) {
  Rect boundingBox = detectedObject.getBoundingBox();
  Integer trackingId = detectedObject.getTrackingId();
  for (Label label : detectedObject.getLabels()) {
    String text = label.getText();
    int index = label.getIndex();
    float confidence = label.getConfidence();
  }
}