TensorFlow Vision: Object Detection and Flutter Integration

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.

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Table of contents

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

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Introduction

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.

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Functionality

• 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

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ProjectStack

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.

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Examples

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

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