Image Classification with on-device AI model

First, Sample Results!

Overview

Image Classification with On-Device Inference is a Flutter app that performs image classification using a pre-trained machine learning model running directly on the device. This ensures fast inference and data privacy, with no cloud dependencies for model processing.

📋 Features

• On-device inference: The pre-trained ONNX model runs entirely on your device
• Customizable file picker: Upload images in supported formats: .jpg, .jpeg, .png, .bmp
• Real-time predictions: Displays the predicted class along with the probabilities
• Error handling: Validates file type, size (max 10MB), and ensures seamless user experience
• Cross-platform: Works on both Android and iOS devices

🛠️ Tech Stack

• Framework: Flutter
• Model Framework: ONNX Runtime
• Packages:
  • file_picker: For selecting image files
  • onnxruntime: For running the model locally

🚀 How It Works

1. Select an Image: Tap the "Upload Image for Inference" button to choose an image file
2. Run Inference: The app preprocesses the image and runs it through the ONNX model
3. View Results: The app displays the predicted class and confidence probabilities
4. Error Handling: If any issues occur (invalid file, processing error), a helpful error message will be shown

🖥️ Setup Instructions

Prerequisites

• Flutter SDK installed
• ONNX Runtime for Flutter added to your pubspec.yaml

Clone the Repository

git clone https://github.com/ThatLinuxGuyYouKnow/Flutter-Image-Classification
cd Flutter-Image-Classification

Install Dependencies

flutter pub get

Run the App

flutter run

Limitations

• File size limit: Max image size is 10MB
• Supported formats: Only .jpg, .jpeg, .png, and .bmp files are accepted
• Device compatibility: Requires devices with ONNX Runtime compatibility

[!] Labels Txt is currently minimized during a production build

License

This project is licensed under the MIT License. See the LICENSE file for details.