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A personal project showcasing object detection using TensorFlow and integration with Flutter. TensorFlow Vision provides a powerful solution for building and deploying object detection models, while leveraging the capabilities of Flutter to implement it on mobile devices.

1. Introduction
2. Functionality
3. Project Stack
4. Examples

Object detection is a fundamental task in computer vision, enabling machines to identify and locate objects within an image or video. This project explores the application of TensorFlow, a popular deep learning framework, for object detection tasks. By leveraging TensorFlow Lite and TensorFlow Custom Model Maker, this project demonstrates how to build and deploy object detection models efficiently.

• Train custom object detection models using TensorFlow Custom Model Maker
• Convert trained models to TensorFlow Lite format for deployment on mobile devices
• Perform real-time object detection on videos

TensorFlow Lite: a lightweight solution for deploying machine learning models on mobile and IoT devices.
TensorFlow Custom Model Maker: a library that simplifies the process of training a custom machine learning model for image classification or object detection.
Python: a popular programming language widely used for data science and machine learning applications.
Annotation Tool: a tool used for annotating images to create datasets for training machine learning models.
Flutter: a mobile app SDK for building high-performance, high-fidelity, apps for iOS and Android.

Here are some screenshots of the Flutter application with real-time object detection: