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Flutter plugin for OnnxRuntime provides an easy, flexible, and fast Dart API to integrate Onnx models in flutter apps across mobile and desktop platforms.

OnnxRuntime Plugin #

pub package

Overview #

Flutter plugin for OnnxRuntime with FFI provides an easy, flexible, and fast Dart API to integrate Onnx models in flutter apps across mobile and desktop platforms.

Key Features #

  • Multi-platform Support for Android and iOS
  • Flexibility to use any Onnx Model.
  • Acceleration using multi-threading.
  • Similar structure as OnnxRuntime Java and C# API.
  • Inference speed is not slower than native Android/iOS Apps built using the Java/Objective-C API.
  • Run inference in different isolates to prevent jank in UI thread.

Getting Started #

In your flutter project add the dependency:

dependencies:
  ...
  onnxruntime: x.y.z

Usage example #

Import #

import 'package:onnxruntime/onnxruntime.dart';

Initializing environment #

OrtEnv.instance.init();

Creating the Session #

final sessionOptions = OrtSessionOptions();
const assetFileName = 'assets/models/test.onnx';
final rawAssetFile = await rootBundle.load(assetFileName);
final bytes = rawAssetFile.buffer.asUint8List();
final session = OrtSession.fromBuffer(bytes, sessionOptions!);

Performing inference #

final shape = [1, 2, 3];
final inputOrt = OrtValueTensor.createTensorWithDataList(data, shape);
final inputs = {'input': inputOrt};
final runOptions = OrtRunOptions();
final outputs = await _session?.runAsync(runOptions, inputs);
inputOrt.release();
runOptions.release();
outputs?.forEach((element) {
  element?.release();
});

Releasing environment #

OrtEnv.instance.release();
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Flutter plugin for OnnxRuntime provides an easy, flexible, and fast Dart API to integrate Onnx models in flutter apps across mobile and desktop platforms.

Repository (GitHub)
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Topics

#onnx #tflite #pytorch #ai

License

unknown (license)

Dependencies

ffi, flutter

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