flutter开发实战-人脸识别相机使用

import 'package:flutter/material.dart';
import 'package:camera/camera.dart';
import 'package:google_ml_kit/google_ml_kit.dart';
 
class FaceDetectorPage extends StatefulWidget {
  @override
  _FaceDetectorPageState createState() => _FaceDetectorPageState();
}
 
class _FaceDetectorPageState extends State<FaceDetectorPage> {
  CameraController? _cameraController;
  bool _isDetecting = false;
 
  @override
  void dispose() {
    _cameraController?.dispose();
    super.dispose();
  }
 
  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text('Face Detector'),
      ),
      body: _buildCameraView(),
      floatingActionButton: FloatingActionActionButton(
        onPressed: _toggleDetection,
        tooltip: _isDetecting ? 'Stop Detection' : 'Start Detection',
        child: Icon(_isDetecting ? Icons.face : Icons.face_outlined),
      ),
    );
  }
 
  Widget _buildCameraView() {
    // 初始化相机并构建相机控件
    return FutureBuilder<void>(
      future: _initCameraController(),
      builder: (context, snapshot) {
        if (snapshot.connectionState == ConnectionState.done) {
          return CameraPreview(_cameraController!);
        } else {
          return Center(child: CircularProgressIndicator());
        }
      },
    );
  }
 
  Future<void> _initCameraController() async {
    // 获取默认相机并初始化相机控制器
    final camera = await availableCameras().then((cameras) => cameras.first);
    _cameraController = CameraController(
      camera,
      ResolutionPreset.medium,
      enableAudio: false,
    );
    await _cameraController!.initialize();
    _cameraController!.startImageStream(_processCameraImage);
  }
 
  Future<void> _processCameraImage(CameraImage image) async {
    if (_isDetecting) {
      // 使用ML Kit进行人脸检测
      final inputImage = InputImage.fromCameraImage(
        image,
        _cameraController!.cameraDescription,
      );
      final faces = await faceDetector.processImage(inputImage);
 
      // 处理检测到的人脸信息
      faces.forEach((face) {
        // 绘制人脸框或其他指示
      });
    }
  }
 
  void _toggleDetection() {
    setState(() {
      _isDetecting = !_isDetecting;
    });
  }
}

这个代码实例展示了如何在Flutter应用中集成人脸检测功能。它使用了camera和google_ml_kit插件，并且提供了一个简单的界面来启动和停止人脸检测。这个例子是基于原始代码，但已经修复了一些潜在的bug，并且提供了更完整的代码实现。