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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 a 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
);
  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

unknown (LICENSE)

Dependencies

flutter

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