flutter create image_classifier
cd image_classifier

dependencies:
  flutter:
    sdk: flutter
  tflite_flutter: ^0.10.0 # 最新版本可能不同
  image_picker: ^1.0.4 # 最新版本可能不同

flutter:
  uses-material-design: true
  assets:
    - assets/ml/mobilenet_v2_1.0_224.tflite
    - assets/ml/labels.txt

import 'package:flutter/material.dart';
import 'package:image_picker/image_picker.dart';
import 'dart:io';
import 'package:tflite_flutter/tflite_flutter.dart';
import 'package:tflite_flutter/tflite_flutter_helper.dart'; // 用于图像预处理

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

class MyApp extends StatelessWidget {
  const MyApp({super.key});

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      title: '图像分类器',
      theme: ThemeData(
        primarySwatch: Colors.teal,
      ),
      home: const ImageClassifierScreen(),
    );
  }
}

class ImageClassifierScreen extends StatefulWidget {
  const ImageClassifierScreen({super.key});

  @override
  State<ImageClassifierScreen> createState() => _ImageClassifierScreenState();
}

class _ImageClassifierScreenState extends State<ImageClassifierScreen> {
  Interpreter? _interpreter;
  List<String>? _labels;
  File? _image;
  String _result = '请选择一张图片进行分类';
  bool _isLoading = false;

  final ImagePicker _picker = ImagePicker();

  @override
  void initState() {
    super.initState();
    _loadModel();
  }

  @override
  void dispose() {
    _interpreter?.close();
    super.dispose();
  }

  Future<void> _loadModel() async {
    setState(() {
      _isLoading = true;
    });
    try {
      _interpreter = await Interpreter.fromAsset(
        'assets/ml/mobilenet_v2_1.0_224.tflite',
        options: InterpreterOptions()..threads = 4, // 可以配置线程数
      );
      _labels = await FileUtil.loadLabels('assets/ml/labels.txt');
      _result = '模型加载成功，请选择图片。';
    } catch (e) {
      _result = '模型加载失败: $e';
      print('Failed to load model: $e');
    } finally {
      setState(() {
        _isLoading = false;
      });
    }
  }

  Future<void> _pickImage() async {
    final XFile? pickedFile = await _picker.pickImage(source: ImageSource.gallery);
    if (pickedFile != null) {
      setState(() {
        _image = File(pickedFile.path);
        _result = '正在分类...';
        _isLoading = true;
      });
      await _classifyImage(_image!);
    }
  }

  Future<void> _classifyImage(File image) async {
    if (_interpreter == null || _labels == null) {
      setState(() {
        _result = '模型未加载或标签缺失。';
        _isLoading = false;
      });
      return;
    }

    try {
      // 图像预处理
      // 根据你的模型输入要求调整参数
      // MobileNetV2 通常需要 224x224 像素的 RGB 图像，像素值归一化到 [-1, 1] 或 [0, 1]
      ImageProcessor imageProcessor = ImageProcessorBuilder()
          .add(ResizeOp(224, 224, ResizeMethod.BILINEAR))
          .add(NormalizeOp(127.5, 127.5)) // 归一化到 [-1, 1]
          .build();

      TensorImage tensorImage = TensorImage.fromFile(image);
      tensorImage = imageProcessor.process(tensorImage);

      // 获取输入输出张量信息
      Tensor inputTensor = _interpreter!.getInputTensor(0);
      Tensor outputTensor = _interpreter!.getOutputTensor(0);

      // 运行模型
      _interpreter!.run(tensorImage.buffer, outputTensor.buffer);

      // 解析输出结果
      // 假设输出是 Float32List，表示每个类别的概率
      List<double> probabilities = outputTensor.buffer.asFloat32List();

      // 找到概率最高的类别
      int maxProbIndex = 0;
      for (int i = 0; i < probabilities.length; i++) {
        if (probabilities[i] > probabilities[maxProbIndex]) {
          maxProbIndex = i;
        }
      }

      String predictedLabel = _labels![maxProbIndex];
      double confidence = probabilities[maxProbIndex] * 100;

      setState(() {
        _result = '分类结果: $predictedLabel (${confidence.toStringAsFixed(2)}%)';
      });
    } catch (e) {
      setState(() {
        _result = '分类失败: $e';
        print('Failed to classify image: $e');
      });
    } finally {
      setState(() {
        _isLoading = false;
      });
    }
  }

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: const Text('图像分类器'),
      ),
      body: Center(
        child: Column(
          mainAxisAlignment: MainAxisAlignment.center,
          children: <Widget>[
            _image == null
                ? const Text('没有选择图片')
                : Image.file(
                    _image!,
                    height: 250,
                    width: 250,
                    fit: BoxFit.contain,
                  ),
            const SizedBox(height: 20),
            Text(
              _result,
              textAlign: TextAlign.center,
              style: const TextStyle(fontSize: 18, fontWeight: FontWeight.bold),
            ),
            const SizedBox(height: 20),
            _isLoading
                ? const CircularProgressIndicator()
                : ElevatedButton(
                    onPressed: _pickImage,
                    child: const Text('从相册选择图片'),
                  ),
          ],
        ),
      ),
    );
  }
}