Fruit Rekog

"??? An intelligent application with the power to accurately classify fruits! ?? Utilizing state-of-the-art TensorFlow Lite models for predictions, this advanced system ensures superior accuracy, making fruit identification a seamless and delightful experience.

Fruit Classifier ???

An intelligent application for accurately classifying fruits using TensorFlow Lite models, with the added convenience of offline functionality.


  1. Offline Capability ??:

    • The application works seamlessly without requiring an internet connection, ensuring reliable performance anytime, anywhere.
  2. High Accuracy Predictions ??:

    • Powered by TensorFlow Lite models, the classifier delivers precise and reliable fruit classifications, enhancing the user experience.
  3. User-Friendly Interface ?️?:

    • The application boasts an intuitive and easy-to-use interface, making fruit identification a simple and enjoyable process.
  4. Wide Range of Fruits ???:

    • Capable of identifying a diverse range of fruits, providing comprehensive support for various fruit types.
  5. Fast and Efficient ?⚡:

    • Swift prediction times ensure a seamless user experience, making the fruit classification process quick and efficient.
  6. Open Source ?️?:

    • The source code is available for exploration and modification, promoting transparency and community collaboration.

Getting Started:

  1. Fork the Repository:
    Fork the repository which will create a copy of this project in your github
  2. Clone the Repository:
    git clone
  3. Open the Fruit-Rekog Folder with Android-Studio:
    Go to android studio and open the Fruit-Rekog folder
  4. Make your own changes:
    Brainstorm and make your own changes in the app

Application Demo


Application Screenshot

? Links

portfolio linkedin twitter

Tech Stack

  • Kotlin
  • XML
  • Android Studio
  • Tensorflow
  • Tensorflow Lite



Contributions are always welcome!

See for ways to get started.

Please adhere to this project's code of conduct.


For support, you can buy me a coffee

Buy Me A Coffee


MIT License


View Github