PalmOilRipenessDetection-Python/palm_oil_mobile/lib/services/yolo_service.dart

import 'dart:typed_data';
import 'dart:io';
import 'package:image_picker/image_picker.dart';
import 'package:ultralytics_yolo/ultralytics_yolo.dart';

class YoloService {
  late YOLO _yolo;
  final ImagePicker _picker = ImagePicker();
  bool _isInitialized = false;

  Future<void> initModel() async {
    try {
      _yolo = YOLO(
        modelPath: 'best.tflite',
        task: YOLOTask.detect,
        useGpu: false, // Disabling GPU for better stability on budget devices
      );
      final success = await _yolo.loadModel();
      if (!success) {
        throw Exception("Model failed to load.");
      }
      _isInitialized = true;
    } catch (e) {
      print("YOLO Init Error: $e");
      rethrow;
    }
  }

  Future<XFile?> pickImage() async {
    return await _picker.pickImage(
      source: ImageSource.gallery,
      maxWidth: 640,
      maxHeight: 640,
    );
  }

  Future<List<dynamic>?> runInference(String imagePath) async {
    if (!_isInitialized) {
      await initModel();
    }
    
    try {
      final File imageFile = File(imagePath);
      final Uint8List bytes = await imageFile.readAsBytes();
      final results = await _yolo.predict(bytes);
      return results['detections'] as List<dynamic>?;
    } catch (e) {
      print("YOLO Inference Error: $e");
      rethrow;
    }
  }

  void dispose() {
    // No explicit close on YOLO class
  }
}