This project is the implementation of on-device machine learning using tflite_flutter which takes in input from the user to predict the probability of having a cardiovascular disease.
Linux and Mac users
Copy the install.sh file in the root folder of your app, and execute the command, sh install.sh in the root folder
Windows users
Copy the install.bat file in the root folder of your app, and execute the command, install.bat in the root folder.
This will automatically download the latest binaries from release assets and place them in appropriate folders for you.
github_demo_1.mp4
The following packages are used in this project:
Package Description: The get_it package is a simple service locator for Dart and Flutter projects. It allows for the easy management of dependency injection and provides a way to locate and retrieve instances of registered services or objects.
Usage:
dependencies:
get_it: ^version_numberPackage description: The flutter_bloc package is a state management library for Flutter applications. It provides a predictable state management pattern, known as BLoC (Business Logic Component), which separates the presentation layer from the business logic and state management. It helps in building reactive and maintainable applications.
Usage:
dependencies:
flutter_bloc: ^version_numberPackage description: The tflite package provides Flutter bindings for TensorFlow Lite, a lightweight machine learning framework designed for mobile and embedded devices. It allows developers to run pre-trained machine learning models on the Flutter platform, enabling tasks such as image classification, object detection, and more.
Usage:
dependencies:
tflite: ^version_number-
Clone the repository:
git clone https://github.com/your/repository.git
-
Change to the project directory:
cd project_directory -
Install the required packages:
flutter pub get
No additional configuration steps are required for the packages mentioned above.
See Demo