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‎.idea/modules.xml

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‎CHANGELOG.md

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## 0.0.1
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* TODO: Describe initial release.
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* Initial Release

‎LICENSE

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TODO: Add your license here.
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pytorch_mobile
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Copyright (c) 2020, Fynn Maarten Belderink
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions
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are met:
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* Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above
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copyright notice, this list of conditions and the following
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disclaimer in the documentation and/or other materials provided
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with the distribution.
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* Neither the name of Fynn Maarten Belderink nor the names of its
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contributors may be used to endorse or promote products derived
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from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
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CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
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INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
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MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS
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BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
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TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR
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TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF
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THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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SUCH DAMAGE.
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--------------------------------------------------------------------------------
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path_provider
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Copyright 2017, the Flutter project authors. All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are
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met:
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* Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above
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copyright notice, this list of conditions and the following
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disclaimer in the documentation and/or other materials provided
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with the distribution.
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* Neither the name of Google Inc. nor the names of its
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contributors may be used to endorse or promote products derived
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from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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--------------------------------------------------------------------------------
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path
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Copyright 2014, the Dart project authors. All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are
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met:
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* Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above
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copyright notice, this list of conditions and the following
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disclaimer in the documentation and/or other materials provided
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with the distribution.
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* Neither the name of Google Inc. nor the names of its
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contributors may be used to endorse or promote products derived
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from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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‎README.md

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# torch_mobile
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# pytorch_mobile
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A new flutter plugin project.
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A flutter plugin for pytorch model inference.
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Since this is still being developed, the plugin is only supported for Android.
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An iOS version is going to come soon
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## Getting Started
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## Usage
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This project is a starting point for a Flutter
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[plug-in package](https://flutter.dev/developing-packages/),
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a specialized package that includes platform-specific implementation code for
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Android and/or iOS.
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### Installation
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For help getting started with Flutter, view our
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[online documentation](https://flutter.dev/docs), which offers tutorials,
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samples, guidance on mobile development, and a full API reference.
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To use this plugin, add `pytorch_mobile` as a [dependency in your pubspec.yaml file](https://flutter.dev/docs/development/packages-and-plugins/using-packages).
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Create a `assets` folder with your pytorch model and labels if needed. Modify `pubspec.yaml` accoringly.
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```yaml
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assets:
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- assets/models/model.pt
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- assets/labels.csv
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```
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Run `flutter pub get`
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### Import the library
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```dart
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import 'package:pytorch_mobile/pytorch_mobile.dart';
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```
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### Load model
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Either custom model:
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```dart
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Model customModel = await PyTorchMobile.loadModel(model: 'assets/models/custom_model.pt');
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```
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Or image model:
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```dart
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Model imageModel = await PyTorchMobile.loadModel(model: 'assets/models/resnet18.pt');
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```
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### Get custom prediction
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```dart
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List prediction = await customModel.getPrediction([1, 2, 3, 4], [1, 2, 2], DType.float32);
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```
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### Get prediction for image
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```dart
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String prediction = await _imageModel.getImagePrediction(image, 224, 224, "assets/labels/labels.csv");
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```

‎android/.project

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<?xml version="1.0" encoding="UTF-8"?>
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<projectDescription>
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<name>torch_mobile</name>
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<comment>Project torch_mobile created by Buildship.</comment>
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<name>pytorch_mobile</name>
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<comment>Project pytorch_mobile created by Buildship.</comment>
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<projects>
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</projects>
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<buildSpec>

‎android/.settings/org.eclipse.buildship.core.prefs

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auto.sync=false
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build.scans.enabled=false
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connection.gradle.distribution=GRADLE_DISTRIBUTION(VERSION(6.3))
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connection.project.dir=../example/android
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connection.project.dir=
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eclipse.preferences.version=1
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gradle.user.home=
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java.home=/usr/lib/jvm/java-11-openjdk-amd64

‎android/build.gradle

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group 'io.fynn.torch_mobile'
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group 'io.fynn.pytorch_mobile'
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version '1.0'
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buildscript {

‎android/settings.gradle

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rootProject.name = 'torch_mobile'
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rootProject.name = 'pytorch_mobile'

‎android/src/main/AndroidManifest.xml

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<manifest xmlns:android="http://schemas.android.com/apk/res/android"
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package="com.example.torch_mobile">
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package="com.example.pytorch_mobile">
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</manifest>

‎android/src/main/java/io/fynn/torch_mobile/Convert.java renamed to ‎android/src/main/java/io/fynn/pytorch_mobile/Convert.java

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package io.fynn.torch_mobile;
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package io.fynn.pytorch_mobile;
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public class Convert {
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‎android/src/main/java/io/fynn/torch_mobile/TorchMobilePlugin.java renamed to ‎android/src/main/java/io/fynn/pytorch_mobile/PyTorchMobilePlugin.java

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package io.fynn.torch_mobile;
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package io.fynn.pytorch_mobile;
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import android.graphics.Bitmap;
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import android.graphics.BitmapFactory;
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import java.util.List;
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/** TorchMobilePlugin */
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public class TorchMobilePlugin<T> implements FlutterPlugin, MethodCallHandler {
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public class PyTorchMobilePlugin implements FlutterPlugin, MethodCallHandler {
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ArrayList<Module> modules = new ArrayList<>();
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@Override
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public void onAttachedToEngine(@NonNull FlutterPluginBinding flutterPluginBinding) {
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final MethodChannel channel = new MethodChannel(flutterPluginBinding.getFlutterEngine().getDartExecutor(),
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"torch_mobile");
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channel.setMethodCallHandler(new TorchMobilePlugin());
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"pytorch_mobile");
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channel.setMethodCallHandler(new PyTorchMobilePlugin());
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}
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public static void registerWith(Registrar registrar) {
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final MethodChannel channel = new MethodChannel(registrar.messenger(), "torch_mobile");
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channel.setMethodCallHandler(new TorchMobilePlugin());
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final MethodChannel channel = new MethodChannel(registrar.messenger(), "pytorch_mobile");
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channel.setMethodCallHandler(new PyTorchMobilePlugin());
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}
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@Override
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result.success(modules.size() - 1);
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} catch (Exception e) {
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String assetPath = call.argument("assetPath");
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Log.e("TorchMobile", assetPath + " is not a proper model", e);
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Log.e("PyTorchMobile", assetPath + " is not a proper model", e);
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}
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break;
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case "predict":
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data = dataList.toArray(new Double[dataList.size()]);
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}catch(Exception e){
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Log.e("TorchMobile", "error parsing arguments", e);
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Log.e("PyTorchMobile", "error parsing arguments", e);
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}
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//prepare input tensor
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try {
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outputTensor = module.forward(IValue.from(inputTensor)).toTensor();
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}catch(RuntimeException e){
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Log.e("TorchMobile", "Your input type " + dtype.toString().toLowerCase() + " (" + Convert.dtypeAsPrimitive(dtype.toString()) +") " + "does not match with model input type",e);
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Log.e("PyTorchMobile", "Your input type " + dtype.toString().toLowerCase() + " (" + Convert.dtypeAsPrimitive(dtype.toString()) +") " + "does not match with model input type",e);
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result.success(null);
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}
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bitmap = Bitmap.createScaledBitmap(bitmap, width, height, false);
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}catch (Exception e){
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Log.e("PyTorchMobile", "error reading image", e);
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}
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final Tensor imageInputTensor = TensorImageUtils.bitmapToFloat32Tensor(bitmap,

‎example/README.md

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# torch_mobile_example
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# pytorch_mobile_example
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Demonstrates how to use the torch_mobile plugin.
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Demonstrates how to use the pytorch_mobile plugin.
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## Getting Started
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‎example/android/app/build.gradle

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defaultConfig {
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// TODO: Specify your own unique Application ID (https://developer.android.com/studio/build/application-id.html).
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applicationId "io.fynn.torch_mobile_example"
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applicationId "io.fynn.pytorch_mobile_example"
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minSdkVersion 21
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targetSdkVersion 28
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versionCode flutterVersionCode.toInteger()

‎example/android/app/src/debug/AndroidManifest.xml

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<manifest xmlns:android="http://schemas.android.com/apk/res/android"
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package="com.example.torch_mobile_example">
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package="com.example.pytorch_mobile_example">
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<!-- Flutter needs it to communicate with the running application
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to allow setting breakpoints, to provide hot reload, etc.
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-->

‎example/android/app/src/main/AndroidManifest.xml

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<manifest xmlns:android="http://schemas.android.com/apk/res/android"
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package="com.example.torch_mobile_example">
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package="com.example.pytorch_mobile_example">
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<!-- io.flutter.app.FlutterApplication is an android.app.Application that
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calls FlutterMain.startInitialization(this); in its onCreate method.
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In most cases you can leave this as-is, but you if you want to provide
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additional functionality it is fine to subclass or reimplement
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FlutterApplication and put your custom class here. -->
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<application
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android:name="io.flutter.app.FlutterApplication"
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android:label="torch_mobile_example"
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android:label="pytorch_mobile_example"
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android:icon="@mipmap/ic_launcher">
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<activity
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android:name=".MainActivity"

‎example/android/app/src/main/java/com/example/torch_mobile_example/MainActivity.java

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package com.example.torch_mobile_example;
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package com.example.pytorch_mobile_example;
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import androidx.annotation.NonNull;
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import io.flutter.embedding.android.FlutterActivity;

‎example/android/app/src/profile/AndroidManifest.xml

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<manifest xmlns:android="http://schemas.android.com/apk/res/android"
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package="com.example.torch_mobile_example">
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package="com.example.pytorch_mobile_example">
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<!-- Flutter needs it to communicate with the running application
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to allow setting breakpoints, to provide hot reload, etc.
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-->

‎example/ios/Runner.xcodeproj/project.pbxproj

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"$(inherited)",
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"$(PROJECT_DIR)/Flutter",
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);
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PRODUCT_BUNDLE_IDENTIFIER = com.example.torchMobileExample;
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PRODUCT_BUNDLE_IDENTIFIER = com.example.pytorchMobileExample;
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PRODUCT_NAME = "$(TARGET_NAME)";
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SWIFT_OBJC_BRIDGING_HEADER = "Runner/Runner-Bridging-Header.h";
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SWIFT_VERSION = 5.0;
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"$(inherited)",
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"$(PROJECT_DIR)/Flutter",
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);
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PRODUCT_BUNDLE_IDENTIFIER = com.example.torchMobileExample;
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PRODUCT_BUNDLE_IDENTIFIER = com.example.pytorchMobileExample;
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PRODUCT_NAME = "$(TARGET_NAME)";
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SWIFT_OBJC_BRIDGING_HEADER = "Runner/Runner-Bridging-Header.h";
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SWIFT_OPTIMIZATION_LEVEL = "-Onone";
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"$(inherited)",
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"$(PROJECT_DIR)/Flutter",
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);
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PRODUCT_BUNDLE_IDENTIFIER = com.example.torchMobileExample;
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PRODUCT_BUNDLE_IDENTIFIER = com.example.pytorchMobileExample;
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PRODUCT_NAME = "$(TARGET_NAME)";
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SWIFT_OBJC_BRIDGING_HEADER = "Runner/Runner-Bridging-Header.h";
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SWIFT_VERSION = 5.0;

‎example/ios/Runner/Info.plist

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<key>CFBundleInfoDictionaryVersion</key>
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<string>6.0</string>
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<key>CFBundleName</key>
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<string>torch_mobile_example</string>
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<string>pytorch_mobile_example</string>
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<key>CFBundlePackageType</key>
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<string>APPL</string>
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<key>CFBundleShortVersionString</key>

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