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A Flutter plugin for accessing TensorFlow Lite. Supports both iOS and Android.

tflite #

A Flutter plugin for accessing TensorFlow Lite. Supports both iOS and Android.

Installation #

Add tflite as a dependency in your pubspec.yaml file.

Android #

In android/app/build.gradle file add the following setting in android block.

    aaptOptions {
        noCompress 'tflite'
    }

iOS #

If you get error like "'vector' file not found", please open ios/Runner.xcworkspace in Xcode, click Runner > Tagets > Runner > Build Settings, search Compile Sources As, change the value to Objective-C++;

Usage #

  1. Create a assets folder and place your label file and model file in it. In pubspec.yaml add:
  assets:
   - assets/labels.txt
   - assets/mobilenet_v1_1.0_224.tflite
  1. Import the library:
import 'package:tflite/tflite.dart';
  1. Load the model and labels:
String res = await Tflite.loadModel(
  model: "assets/mobilenet_v1_1.0_224.tflite",
  labels: "assets/labels.txt",
);
  1. Run the model on
  • image file:
var recognitions = await Tflite.runModelOnImage(
  path: filepath,   // required
  inputSize: 224,   // wanted input size, defaults to 224
  numChannels: 3,   // wanted input channels, defaults to 3
  imageMean: 127.5, // defaults to 117.0
  imageStd: 127.5,  // defaults to 1.0
  numResults: 6,    // defaults to 5
  threshold: 0.05,  // defaults to 0.1
  numThreads: 1,    // defaults to 1
);
  • byte list:
var recognitions = await Tflite.runModelOnBinary(
  binary: imageToByteList(image, 224, 127.5, 127.5),// required
  numResults: 6,    // defaults to 5
  threshold: 0.05,  // defaults to 0.1
  numThreads: 1,    // defaults to 1
);

Uint8List imageToByteList(Image image, int inputSize, double mean, double std) {
  var convertedBytes = Float32List(1 * inputSize * inputSize * 3);
  var buffer = Float32List.view(convertedBytes.buffer);
  int pixelIndex = 0;
  for (var i = 0; i < inputSize; i++) {
    for (var j = 0; j < inputSize; j++) {
      var pixel = image.getPixel(i, j);
      buffer[pixelIndex++] = (((pixel >> 16) & 0xFF) - mean) / std;
      buffer[pixelIndex++] = (((pixel >> 8) & 0xFF) - mean) / std;
      buffer[pixelIndex++] = (((pixel) & 0xFF) - mean) / std;
    }
  }
  return convertedBytes.buffer.asUint8List();
}

  1. Release resources:
await Tflite.close();

Demo #

Refer to the example.

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A Flutter plugin for accessing TensorFlow Lite. Supports both iOS and Android.

Repository (GitHub)
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License

Icon for licenses.unknown (LICENSE)

Dependencies

flutter

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