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This project is a multi-AI app that features πŸ”’ digit recognition, πŸ•΅οΈ object detection, and ⚑ real-time detection using Flutter and TensorFlow Lite.

License: MIT License

Java 0.20% Ruby 4.15% Objective-C 0.97% Dart 94.69%
artificial-intelligence flutter mobile-design mobile-development yolov2-tiny digit-recognition object-detection real-time-object-detection

smartlensai's Introduction

πŸ€– AI Flutter Application

Welcome to my AI Flutter Application, a cutting-edge mobile app designed to showcase multiple artificial intelligence capabilities within a single, user-friendly interface. This application leverages Flutter, Google's UI toolkit, for crafting beautiful, natively compiled applications for mobile, web, and desktop from a single codebase. My app features several AI functionalities, including digit recognition, object detection, and real-time detection, making it a versatile tool for users interested in AI technologies.

✨ Features

  • πŸ”’ Digit Recognition: Utilizes a trained model to accurately recognize digits from images or real-time camera feeds.
  • πŸ•΅οΈ Object Detection: Capable of identifying and labeling objects within a static image or through the camera in real-time.
  • ⚑ Real-Time Detection: Offers the ability to detect and classify objects or digits in real-time, providing instant feedback to the user.

πŸ“ΈScreenshots

Screenshot 1 Screenshot 2 Screenshot 3
Screenshot 4 Screenshot 5 Screenshot 6
Screenshot 7 Screenshot 8 Screenshot 9

πŸš€ Getting Started

To get started with the AI Flutter Application, ensure you have Flutter 2.2.3 installed on your system. Follow the steps below to set up the project locally:

  1. πŸ“₯ Clone the repository to your local machine.
  2. πŸ–₯️ Open the terminal and navigate to the project directory.
  3. πŸ“¦ Run flutter pub get to install the necessary dependencies.
  4. πŸ“± Launch an emulator or connect a physical device.
  5. ▢️ Run flutter run to start the application.

πŸ“š Dependencies

  • Flutter: For building the application's UI and logic.
  • TensorFlow Lite: Used for integrating AI models into the application.
  • Camera: To access real-time camera feeds for detection.

🧠 Models

The application includes the following pre-trained TensorFlow Lite models:

  • Digit Recognition: converted_mnist_model.tflite
  • Object Detection: yolov2_tiny.tflite, ssd_mobilenet.tflite and mobilenet_v1_1.0_224.tflite (Placeholder name, replace with the actual model name)

These models are located in the assets directory and are automatically loaded by the application at runtime.

🀝 Contributing

I welcome contributions to the AI Flutter Application! If you have suggestions for improvements or new features, feel free to open an issue or submit a pull request.

πŸ“œ License

This project is licensed under the MIT License .

Thank you for exploring my AI Flutter Application. I hope it serves as a valuable tool for your interest or work in artificial intelligence.

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