ai_image_classifier 1.0.0

A simple and powerful Flutter package for on-device image classification using TensorFlow Lite models. Supports custom models, image resizing, and normalization.

example/lib/main.dart

import 'dart:io';
import 'package:flutter/material.dart';
import 'package:image_picker/image_picker.dart';
import 'package:ai_image_classifier/ai_image_classifier.dart';

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

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

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      title: 'AI Image Classifier',
      theme: ThemeData(
        colorScheme: ColorScheme.fromSeed(seedColor: Colors.deepPurple, brightness: Brightness.dark),
        useMaterial3: true,
      ),
      home: const HomePage(),
    );
  }
}

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

  @override
  State<HomePage> createState() => _HomePageState();
}

class _HomePageState extends State<HomePage> {
  final AiImageClassifier _classifier = AiImageClassifier();
  File? _image;
  List<Classification>? _results;
  bool _isLoading = false;
  final ImagePicker _picker = ImagePicker();

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

  Future<void> _loadModel() async {
    try {
      await _classifier.loadModel(
        modelPath: 'assets/models/mobilenet_v1.tflite',
        labelsPath: 'assets/models/labels.txt',
      );
    } catch (e) {
      debugPrint("Error loading model: $e");
    }
  }

  Future<void> _pickImage(ImageSource source) async {
    final XFile? pickedFile = await _picker.pickImage(source: source);

    if (pickedFile != null) {
      setState(() {
        _image = File(pickedFile.path);
        _isLoading = true;
        _results = null;
      });

      try {
        final results = await _classifier.classifyImagePath(pickedFile.path);
        setState(() {
          _results = results;
          _isLoading = false;
        });
      } catch (e) {
        debugPrint("Error classifying image: $e");
        setState(() {
          _isLoading = false;
        });
      }
    }
  }

  @override
  void dispose() {
    _classifier.dispose();
    super.dispose();
  }

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: const Text('AI Image Classifier'),
        centerTitle: true,
        elevation: 2,
      ),
      body: SingleChildScrollView(
        child: Column(
          children: [
            const SizedBox(height: 20),
            _buildImageDisplay(),
            const SizedBox(height: 20),
            _buildActionButtons(),
            const SizedBox(height: 30),
            if (_isLoading)
              const CircularProgressIndicator()
            else if (_results != null)
              _buildResultsList(),
          ],
        ),
      ),
    );
  }

  Widget _buildImageDisplay() {
    return Center(
      child: Container(
        width: 300,
        height: 300,
        decoration: BoxDecoration(
          color: Colors.grey[900],
          borderRadius: BorderRadius.circular(20),
          boxShadow: [
            BoxShadow(
              color: Colors.black.withOpacity(0.5),
              blurRadius: 10,
              offset: const Offset(0, 5),
            ),
          ],
        ),
        child: ClipRRect(
          borderRadius: BorderRadius.circular(20),
          child: _image != null
              ? Image.file(_image!, fit: BoxFit.cover)
              : const Column(
                  mainAxisAlignment: MainAxisAlignment.center,
                  children: [
                    Icon(Icons.image, size: 100, color: Colors.grey),
                    SizedBox(height: 10),
                    Text("No image selected", style: TextStyle(color: Colors.grey)),
                  ],
                ),
        ),
      ),
    );
  }

  Widget _buildActionButtons() {
    return Row(
      mainAxisAlignment: MainAxisAlignment.spaceEvenly,
      children: [
        ElevatedButton.icon(
          onPressed: () => _pickImage(ImageSource.gallery),
          icon: const Icon(Icons.photo_library),
          label: const Text("Gallery"),
          style: ElevatedButton.styleFrom(
            padding: const EdgeInsets.symmetric(horizontal: 20, vertical: 12),
          ),
        ),
        ElevatedButton.icon(
          onPressed: () => _pickImage(ImageSource.camera),
          icon: const Icon(Icons.camera_alt),
          label: const Text("Camera"),
          style: ElevatedButton.styleFrom(
            padding: const EdgeInsets.symmetric(horizontal: 20, vertical: 12),
            backgroundColor: Theme.of(context).colorScheme.primary,
            foregroundColor: Theme.of(context).colorScheme.onPrimary,
          ),
        ),
      ],
    );
  }

  Widget _buildResultsList() {
    return Padding(
      padding: const EdgeInsets.symmetric(horizontal: 20),
      child: Column(
        crossAxisAlignment: CrossAxisAlignment.start,
        children: [
          const Text(
            "Classification Results:",
            style: TextStyle(fontSize: 18, fontWeight: FontWeight.bold),
          ),
          const SizedBox(height: 10),
          ListView.builder(
            shrinkWrap: true,
            physics: const NeverScrollableScrollPhysics(),
            itemCount: _results!.length,
            itemBuilder: (context, index) {
              final res = _results![index];
              return Card(
                margin: const EdgeInsets.only(bottom: 10),
                child: ListTile(
                  title: Text(res.label, style: const TextStyle(fontWeight: FontWeight.w600)),
                  trailing: Text(
                    "${(res.confidence * 100).toStringAsFixed(1)}%",
                    style: TextStyle(
                      color: Theme.of(context).colorScheme.primary,
                      fontWeight: FontWeight.bold,
                      fontSize: 16,
                    ),
                  ),
                  subtitle: LinearProgressIndicator(
                    value: res.confidence,
                    backgroundColor: Colors.grey[800],
                    borderRadius: BorderRadius.circular(10),
                  ),
                ),
              );
            },
          ),
        ],
      ),
    );
  }
}