Object Detection Using Tensorflow Lite

Abstract

Object detection is a computer vision and has numerous applications, including autonomous vehicles, security systems, and robotics. TensorFlow is a popular open-source framework for machine learning and deep learning, and it provides pre-trained model tools of object detection. we use TensorFlow for object detection in Android applications. We investigate various pre-trained models, their accuracy, and their performance on mobile devices. We also explore different techniques to optimize the models for mobile devices, such as quantization, pruning, and compression. We implement a demo Android application that uses TensorFlow for object detection and evaluate its performance on different Android devices in the advent of deep learning techniques, object detection has seen significant improvements in accuracy and speed. TensorFlow is a popular used for object detection and Android is the most widely used mobile operating system, and there is a growing demand for object detection in Android applications. In this project, we propose an implementation of object detection using TensorFlow in Android. We- trained the model using the TensorFlow Object Detection API and converted it to a TensorFlow Lite model for deployment on Android. We developed an Android application that can take images from the camera or the device's storage andperform object detection. The application uses the TensorFlow Lite model for object detection and displays the results to the user. The proposed system can be used in various applications such as security cameras, traffic monitoring,