pytorch_mobile

A flutter plugin for pytorch model inference. Since this is still being developed, the plugin is only supported for Android. An iOS version is going to come soon

Usage

Installation

To use this plugin, add pytorch_mobile as a dependency in your pubspec.yaml file.

Create a assets folder with your pytorch model and labels if needed. Modify pubspec.yaml accoringly.

assets:
 - assets/models/model.pt
 - assets/labels.csv

Run flutter pub get

Import the library

import 'package:pytorch_mobile/pytorch_mobile.dart';

Load model

Either custom model:

Model customModel = await PyTorchMobile
        .loadModel('assets/models/custom_model.pt');

Or image model:

Model imageModel = await PyTorchMobile
        .loadModel('assets/models/resnet18.pt');

Get custom prediction

List prediction = await customModel
        .getPrediction([1, 2, 3, 4], [1, 2, 2], DType.float32);

Get prediction for an image

String prediction = await _imageModel
        .getImagePrediction(image, 224, 224, "assets/labels/labels.csv");

Image prediction for an image with custom mean and std

final mean = [0.5, 0.5, 0.5];
final std = [0.5, 0.5, 0.5];
String prediction = await _imageModel
        .getImagePrediction(image, 224, 224, "assets/labels/labels.csv", mean: mean, std: std);

Detectron2 model [only detection]

List<List>? prediction = await _d2model
        .detectron2(image, 320, 320, "assets/labels/d2go.csv", minScore: 0.4);

// prediction[0] => [left, top, right, bottom, score, label]

Detectron2 model is generated with d2go, using script

Contact

fynnmaarten.business@gmail.com