Tensorflow 向颤振项目发布装载资产

我试图将TFLite模型加载到颤振中，但出现异常“加载模型失败”。我已经通过yaml加载了资产，导入了TFLite插件，并确保文件路径正确，但我一直打印相同的异常。我已经用python测试了这个模型，它可以工作了，所以我现在只是想让它与颤振一起工作

代码：

import 'dart:io';

import 'package:flutter/material.dart';
import 'package:flutter/services.dart';
import 'package:tflite/tflite.dart';
import 'package:image_picker/image_picker.dart';
import 'package:image/image.dart' as img;

void main() {
  runApp(MyApp());
}

const String TF = "image_classifier";
//const String yolo = "Tiny YOLOv2";

class MyApp extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      debugShowCheckedModeBanner: false,
      home: TfliteHome(),
    );
  }
}

class TfliteHome extends StatefulWidget {
  @override
  _TfliteHomeState createState() => _TfliteHomeState();
}

class _TfliteHomeState extends State<TfliteHome> {
  String _model = TF;
  File _image;

  double _imageWidth;
  double _imageHeight;
  bool _busy = false;

  List _recognitions;

  @override
  void initState() {
    super.initState();
    _busy = true;

    loadModel().then((val) {
      setState(() {
        _busy = false;
      });
    });
  }

  loadModel() async {
    Tflite.close();
    try {
      String res;
        res = await Tflite.loadModel(
          model: "assets/image_classifier.tflite",
          labels: "assets/image_labels.txt",
        );
      print(res);
    } on PlatformException {
      print("Failed to load the model");
    }
  }

  selectFromImagePicker() async {
    var image = await ImagePicker.pickImage(source: ImageSource.gallery);
    if (image == null) return;
    setState(() {
      _busy = true;
    });
    predictImage(image);
  }

  predictImage(File image) async {
    if (image == null) return;

    if (_model == TF) {
      await TFModel(image);
    }

    FileImage(image)
        .resolve(ImageConfiguration())
        .addListener((ImageStreamListener((ImageInfo info, bool _) {
          setState(() {
            _imageWidth = info.image.width.toDouble();
            _imageHeight = info.image.height.toDouble();
          });
        })));

    setState(() {
      _image = image;
      _busy = false;
    });
  }

  TFModel(File image) async {
    var recognitions = await Tflite.detectObjectOnImage(
        path: image.path,
        model: "image_classifier",
        threshold: 0.3,
        imageMean: 0.0,
        imageStd: 255.0,
        numResultsPerClass: 3);

    setState(() {
      _recognitions = recognitions;
    });
  }

  List<Widget> renderBoxes(Size screen) {
    if (_recognitions == null) return [];
    if (_imageWidth == null || _imageHeight == null) return [];

    double factorX = screen.width;
    double factorY = _imageHeight / _imageHeight * screen.width;

    Color blue = Colors.red;

    return _recognitions.map((re) {
      return Positioned(
        left: re["rect"]["x"] * factorX,
        top: re["rect"]["y"] * factorY,
        width: re["rect"]["w"] * factorX,
        height: re["rect"]["h"] * factorY,
        child: Container(
          decoration: BoxDecoration(
              border: Border.all(
            color: blue,
            width: 3,
          )),
          child: Text(
            "${re["detectedClass"]} ${(re["confidenceInClass"] * 100).toStringAsFixed(0)}%",
            style: TextStyle(
              background: Paint()..color = blue,
              color: Colors.white,
              fontSize: 15,
            ),
          ),
        ),
      );
    }).toList();
  }

  @override
  Widget build(BuildContext context) {
    Size size = MediaQuery.of(context).size;

    List<Widget> stackChildren = [];

    stackChildren.add(Positioned(
      top: 0.0,
      left: 0.0,
      width: size.width,
      child: _image == null ? Text("No Image Selected") : Image.file(_image),
    ));

    stackChildren.addAll(renderBoxes(size));

    if (_busy) {
      stackChildren.add(Center(
        child: CircularProgressIndicator(),
      ));
    }

    return Scaffold(
      appBar: AppBar(
        title: Text("TFLite Demo"),
      ),
      floatingActionButton: FloatingActionButton(
        child: Icon(Icons.image),
        tooltip: "Pick Image from gallery",
        onPressed: selectFromImagePicker,
      ),
      body: Stack(
        children: stackChildren,
      ),
    );
  }
}

flutter:

  # The following line ensures that the Material Icons font is
  # included with your application, so that you can use the icons in
  # the material Icons class.
  uses-material-design: true

  # To add assets to your application, add an assets section, like this:
  assets:
  - assets/image_classifier.tflite
  - assets/image_labels.txt

文件路径： 安卓 在android/app/build.gradle中，在android块中添加以下设置

  aaptOptions {
    noCompress 'tflite'
    noCompress 'lite'
}

为我工作

Android 在android/app/build.gradle中，在android块中添加以下设置

  aaptOptions {
    noCompress 'tflite'
    noCompress 'lite'
}

---

为我工作

你把它们添加到pubspec.yaml了吗？包括问题中的资产片段。是的，我已经将资产添加到pubspec.yaml中，并且我已经将这部分代码添加到我的原始帖子中。应该有一行缩进，上面写着

-assets/image\u classifier.tflite

和

-assets/image\u labels.txt

。缩进是否存在于

pubspec.yaml

中？因为在上面的代码片段中它不存在。我在pubspec.yaml中缩进了资产，但它仍然不起作用。它仍在打印。加载模型失败。您是否能够使用根捆绑自己加载资产？只是为了检查它是否可用。您是否将它们添加到pubspec.yaml？包括问题中的资产片段。是的，我已经将资产添加到pubspec.yaml中，并且我已经将这部分代码添加到我的原始帖子中。应该有一行缩进，上面写着

-assets/image\u classifier.tflite

和

-assets/image\u labels.txt

。缩进是否存在于

pubspec.yaml

中？因为在上面的代码片段中它不存在。我在pubspec.yaml中缩进了资产，但它仍然不起作用。它仍在打印。加载模型失败。您是否能够使用根捆绑自己加载资产？只是为了检查它是否可用。