The Flutter application utilizes Tensor Flow Lite, a pre-trained machine learning model, to detect and identify objects captured in real-time images. The application employs a bounding box algorithm to identify the object's location and uses a selection logic based on the object's confidence rate when multiple objects are detected.

After detecting the object, the application implements an autozoom feature by utilizing the object's bounding box coordinates. The autozoom logic can vary based on the specific requirements of the application. If a more optimal approach for autozoom is identified, it can be implemented to enhance the application's functionality.