How many steps are involved in using the ML Kit Object Detection API?

The steps involved in using the ML Kit Object Detection API are:

1. Add the ML Kit Android libraries to your app: In your app-level build.gradle file, include the following dependencies.

2. Prepare the input image: ML Kit can use an image from a variety of sources. You can use an image from the device's photo gallery or camera, or an image from a Bitmap, byte array, or a file on the device.

3. Initialize the ObjectDetector: Create an instance of ObjectDetector using the ObjectDetector.Builder class. You can customize the detector's behavior with options such as whether to classify objects, and the detector's mode of operation.

4. Run the detector: Pass the input image to the ObjectDetector's process() method. This method returns a Task object that you can use to determine when the detector has finished processing the image.

5. Get the results: When the Task completes, it returns a list of DetectedObject objects. Each DetectedObject represents an object that was detected in the image.

6. (Optional) Manage detected objects: If you want to track the detected objects across multiple frames, you can use the ObjectTracker class.

7. Release resources: When you are done with the detector, call its close() method to release the resources that it is using.