Overview
The tflite_flutter package enables seamless integration of TensorFlow Lite models into Flutter applications across Android, iOS, macOS, Windows, and Linux. It offers a straightforward Dart API for running on-device machine learning tasks such as image classification, object detection, and speech recognition. Designed for performance and flexibility, it supports model loading, inference, and real-time processing with minimal latency. Ideal for developers building intelligent apps with local AI capabilities without relying on cloud services.
Use cases
- Image classification in mobile apps
- Real-time object detection
- On-device speech recognition
- OCR with local models
- Gesture or motion analysis
Key features
- Cross-platform support
- Low-latency inference
- Simple Dart API
- Model quantization support
- Live model loading
Suitable for
- Mobile and desktop ML apps
- Offline AI functionality
- Privacy-focused applications
- High-performance inference
- Developers using TensorFlow Lite
Considerations
- Requires TFLite model files
- Limited to supported model types
- Memory usage depends on model size
- No built-in model training
- Platform-specific optimizations may be needed