In 2025, AI is transforming mobile apps, making them smarter and more interactive. Flutter, Google’s powerhouse framework, is perfect for building cross-platform apps with AI capabilities. In this guide, we’ll create a Flutter app that uses AI to extract text from images and suggest related topics—all in a few simple steps. Ready to dive into the future of app development? Let’s get started!
What You’ll Need
- Prerequisites: Basic Flutter and Dart knowledge, Flutter SDK installed (latest version as of March 2025), and an IDE (Android Studio or VS Code).
- Tools: A physical device or emulator for testing, and an internet connection to fetch dependencies.
Step 1: Setting Up Your Flutter Project
Start by creating a new Flutter project. Open your terminal and run, and if you create already then skip this step:
flutter create ai_flutter_app
cd ai_flutter_appdependencies:
flutter:
sdk: flutter
google_ml_kit: ^0.16.0 # Check for the latest version in March 2025
image_picker: ^1.1.0 # For selecting images from the galleryRun flutter pub get to install them.
Step 2: Designing a Simple UI
Let’s build a clean UI with a button to pick an image, a space to display the image, and a text area for AI results. Replace the content of lib/main.dart with:
import 'package:flutter/material.dart';
import 'package:image_picker/image_picker.dart';
import 'package:google_ml_kit/google_ml_kit.dart';
import 'dart:io';
void main() {
runApp(MyApp());
}
class MyApp extends StatelessWidget {
@override
Widget build(BuildContext context) {
return MaterialApp(
home: AIScreen(),
);
}
}
class AIScreen extends StatefulWidget {
@override
_AIScreenState createState() => _AIScreenState();
}
class _AIScreenState extends State<AIScreen> {
File? _image;
String _extractedText = "No text extracted yet.";
String _suggestion = "Pick an image to get started!";
final ImagePicker _picker = ImagePicker();
@override
Widget build(BuildContext context) {
return Scaffold(
appBar: AppBar(title: Text("AI Flutter App")),
body: SingleChildScrollView(
child: Column(
children: [
SizedBox(height: 20),
_image == null
? Text("No image selected.")
: Image.file(_image!, height: 300),
SizedBox(height: 20),
ElevatedButton(
onPressed: _pickImage,
child: Text("Pick Image"),
),
SizedBox(height: 20),
Text("Extracted Text: $_extractedText"),
SizedBox(height: 20),
Text("Suggestion: $_suggestion"),
],
),
),
);
}
// Placeholder for image picking (to be completed in Step 3)
Future<void> _pickImage() async {}
}Explanation:
- We’ve set up a basic app with a button to pick an image and placeholders for displaying the image, extracted text, and AI suggestion.
- This keeps readers hooked by showing a functional UI early.
Step 3: Integrating AI into Flutter
Now, let’s add the AI functionality: picking an image and extracting text using Google ML Kit. Update the _pickImage method and add text processing:
Future<void> _pickImage() async {
final XFile? image = await _picker.pickImage(source: ImageSource.gallery);
if (image == null) return;
setState(() {
_image = File(image.path);
});
// Process the image with ML Kit
final inputImage = InputImage.fromFilePath(image.path);
final textRecognizer = TextRecognizer();
final RecognizedText recognizedText = await textRecognizer.processImage(inputImage);
String extractedText = recognizedText.text.isEmpty
? "No text found."
: recognizedText.text;
// Simple suggestion logic (expandable in Step 5)
String suggestion = extractedText.contains("book")
? "Try reading more books on this topic!"
: "Explore this topic online!";
setState(() {
_extractedText = extractedText;
_suggestion = suggestion;
});
await textRecognizer.close();
}Explanation:
- image_picker grabs an image from the gallery.
- google_ml_kit extracts text from the image using its Text Recognition API.
- A basic suggestion is generated based on the text (e.g., detecting “book”). This keeps it beginner-friendly while showing AI’s potential.
Image Suggestion:
- Description: A split-screen image: Left side shows a book cover image in the app, right side shows the extracted text and suggestion (e.g., “Extracted Text: ‘Flutter Book’, Suggestion: ‘Try reading more books on this topic!’”).
- Caption: “AI in action: Text extraction and smart suggestions.”
Step 4: Testing and Debugging
Run your app on an emulator or device:
flutter run- Test: Pick an image with text (e.g., a book cover or a sign). Ensure the text and suggestion update.
- Debug Tips:
- If the app crashes, check permissions (add <uses-permission android:name=”android.permission.READ_EXTERNAL_STORAGE”/> to AndroidManifest.xml for Android).
- If no text is detected, try a clearer image.
Step 5: Enhancing the App
Let’s polish it up:
- Better Suggestions: Expand the suggestion logic:
String suggestion = extractedText.toLowerCase().contains("book")
? "Try reading more books on this topic!"
: extractedText.toLowerCase().contains("code")
? "Check out coding tutorials on dosomthings.com!"
: "Explore this topic online!";- Extras: Add a loading spinner while processing the image, or save results using shared_preferences.
- Cross-Platform: Test it on web or desktop with flutter run -d web-server.
Image Suggestion:
- Description: A before-and-after comparison: Left side shows the basic app, right side shows it with a loading spinner and styled text.
- Caption: “From basic to polished: Enhancing your AI app.”
Conclusion
You’ve just built an AI-powered Flutter app that extracts text and offers smart suggestions—all in 2025’s cutting-edge style! Experiment with other ML Kit features (like face detection) or share your app with us at dosomthings.com. Keep exploring Flutter’s potential—your next big project is waiting!
