Tensorflow Lite Object Detection Demo App 2019 description

Launch the TensorflowLite demo app and start viewing different objects in camera preview to see the bounding boxes and live tracking in action.

TensorFlow Lite provides all the tools you need to convert and run TensorFlow models on mobile, embedded, and IoT devices.

The source code of the app is open source and can be found on Github using the link below:
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/examples

TensorFlow Lite allows you to run TensorFlow models on a wide range of devices. A TensorFlow model is a data structure that contains the logic and knowledge of a machine learning network trained to solve a particular problem.

What is object detection?
Given an image or a video stream, an object detection model can identify which of a known set of objects might be present and provide information about their positions within the image.

An object detection model is trained to detect the presence and location of multiple classes of objects. For example, a model might be trained with images that contain various pieces of fruit, along with a label that specifies the class of fruit they represent (e.g. an apple, a banana, or a strawberry), and data specifying where each object appears in the image.

When we subsequently provide an image to the model, it will output a list of the objects it detects, the location of a bounding box that contains each object, and a score that indicates the confidence that detection was correct.