fix: on revire ml kit on essaie d ameliorer la detection des cercles
This commit is contained in:
@@ -2,7 +2,6 @@ import 'dart:io';
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import 'dart:math' as math;
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import 'dart:async';
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import 'package:flutter/material.dart';
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import 'package:flutter/services.dart';
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import 'package:image_picker/image_picker.dart';
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import 'package:permission_handler/permission_handler.dart';
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import 'package:device_info_plus/device_info_plus.dart';
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@@ -18,7 +17,6 @@ import 'widgets/image_source_button.dart';
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import '../../services/image_crop_service.dart';
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import '../../services/opencv_target_service.dart';
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import '../../services/parallelism_service.dart'; // NOUVEAU
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import '../../services/object_detection_service.dart'; // NOUVEAU : ML Kit
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import '../../services/target_rectify_service.dart'; // NOUVEAU : redressement
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import 'package:image/image.dart' as img;
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import 'package:path_provider/path_provider.dart';
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@@ -56,8 +54,9 @@ class _CaptureScreenState extends State<CaptureScreen>
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late AnimationController _scanAnimationController;
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late Animation<double> _scanAnimation;
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// Détection OpenCV (inchangée)
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// Détection OpenCV (cible circulaire) — on garde le résultat COMPLET
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bool? _alignmentStatus;
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TargetDetectionResult? _targetResult; // NOUVEAU : centre + rayon de la cible
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Timer? _detectionTimer;
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bool _isAnalyzingFrame = false;
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@@ -65,12 +64,7 @@ class _CaptureScreenState extends State<CaptureScreen>
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ParallelismData? _parallelismData;
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StreamSubscription<ParallelismData>? _parallelismSubscription;
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// NOUVEAU : Détection d'objet ML Kit
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final ObjectDetectionService _objectService = ObjectDetectionService();
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StreamSubscription<List<DetectedObject2D>>? _objectSubscription;
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List<DetectedObject2D> _detectedObjects = [];
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// NOUVEAU : Service de redressement de cible (warp perspective)
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// Service de redressement de cible (warp perspective)
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final TargetRectifyService _rectifyService = TargetRectifyService();
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@override
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@@ -93,8 +87,6 @@ class _CaptureScreenState extends State<CaptureScreen>
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_detectionTimer?.cancel();
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_parallelismSubscription?.cancel(); // NOUVEAU
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_parallelismService.dispose(); // NOUVEAU
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_objectSubscription?.cancel(); // NOUVEAU
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_objectService.dispose(); // NOUVEAU
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super.dispose();
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}
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@@ -122,52 +114,21 @@ class _CaptureScreenState extends State<CaptureScreen>
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}
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// ─────────────────────────────────────────────────────────────────────────
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// NOUVEAU : Démarre l'écoute de la détection d'objet ML Kit
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// ─────────────────────────────────────────────────────────────────────────
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void _startObjectDetection() {
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_objectSubscription?.cancel();
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_objectService.start();
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_objectSubscription = _objectService.stream.listen((objects) {
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if (mounted && _showLiveCamera) {
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setState(() {
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_detectedObjects = objects;
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});
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}
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});
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}
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void _stopObjectDetection() {
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_objectSubscription?.cancel();
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_objectSubscription = null;
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_objectService.stop();
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_detectedObjects = [];
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}
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// ─────────────────────────────────────────────────────────────────────────
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// NOUVEAU : Calcule la couleur et le message depuis les données IMU
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// Calcule la couleur et le message depuis l'IMU + la détection de cible
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// ─────────────────────────────────────────────────────────────────────────
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/// Y a-t-il un objet détecté suffisamment grand et globalement centré ?
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DetectedObject2D? get _primaryObject {
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if (_detectedObjects.isEmpty) return null;
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// On prend l'objet le plus grand (le sujet principal le plus probable).
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final sorted = [..._detectedObjects]
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..sort((a, b) => b.area.compareTo(a.area));
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final obj = sorted.first;
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// Filtre : doit occuper une part raisonnable de l'image et être centré.
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final bool bigEnough = obj.area > 0.04; // ~20% × 20%
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final bool centered = obj.centerX > 0.2 &&
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obj.centerX < 0.8 &&
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obj.centerY > 0.2 &&
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obj.centerY < 0.8;
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return (bigEnough && centered) ? obj : null;
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/// La cible circulaire est-elle détectée et raisonnablement cadrée ?
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bool get _targetReady {
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final t = _targetResult;
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if (t == null || !t.success) return false;
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final bool centered =
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t.centerX > 0.15 && t.centerX < 0.85 && t.centerY > 0.15 && t.centerY < 0.85;
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final bool bigEnough = t.radius > 0.12;
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return centered && bigEnough;
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}
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bool get _objectReady => _primaryObject != null;
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/// Couleur du cadre : dépend UNIQUEMENT du parallélisme IMU.
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/// (La détection d'objet sert seulement à dessiner une boîte, elle ne
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/// (La détection de cible sert seulement à dessiner le cercle, elle ne
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/// bloque jamais le passage au vert.)
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Color get _frameColor {
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final bool imuAligned =
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@@ -182,10 +143,10 @@ class _CaptureScreenState extends State<CaptureScreen>
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return 'ALIGNEZ LA CIBLE DANS LE CADRE';
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}
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// Aligné → message de validation (avec bonus si un objet est cadré)
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// Aligné → message de validation (avec bonus si la cible est détectée)
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if (_parallelismData!.isAligned) {
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return _objectReady
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? 'PARFAIT — OBJET CADRÉ, PRÊT'
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return _targetReady
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? 'PARFAIT — CIBLE DÉTECTÉE, PRÊT'
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: 'PARALLÈLE OK — PRÊT À PHOTOGRAPHIER';
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}
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@@ -241,12 +202,12 @@ class _CaptureScreenState extends State<CaptureScreen>
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_isCameraInitialized = true;
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_showLiveCamera = true;
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_alignmentStatus = null;
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_targetResult = null; // reset détection cible
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_parallelismData = null; // NOUVEAU : reset IMU
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});
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_startAlignmentDetection();
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_startParallelismDetection(); // NOUVEAU
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_startObjectDetection(); // NOUVEAU
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}
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} catch (e) {
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debugPrint('Erreur caméra: $e');
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@@ -265,18 +226,11 @@ class _CaptureScreenState extends State<CaptureScreen>
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DateTime? _lastAnalysis;
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_cameraController!.startImageStream((CameraImage cameraImage) async {
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// NOUVEAU : on alimente ML Kit à chaque frame (le service gère son propre
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// throttle interne via _isBusy, donc pas de saturation).
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_objectService.processCameraImage(
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cameraImage,
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_cameras![0],
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DeviceOrientation.portraitUp,
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);
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if (_isAnalyzingFrame) return;
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final now = DateTime.now();
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// Cadence ~1 s : assez réactif pour suivre la cible sans saturer le CPU.
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if (_lastAnalysis != null &&
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now.difference(_lastAnalysis!).inSeconds < 3) return;
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now.difference(_lastAnalysis!).inMilliseconds < 1000) return;
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_lastAnalysis = now;
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_isAnalyzingFrame = true;
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@@ -300,6 +254,9 @@ class _CaptureScreenState extends State<CaptureScreen>
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if (mounted && _showLiveCamera) {
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setState(() {
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// On garde le résultat complet pour dessiner le cercle.
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_targetResult = result.success ? result : null;
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if (!result.success) {
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_alignmentStatus = null;
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} else {
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@@ -329,6 +286,7 @@ class _CaptureScreenState extends State<CaptureScreen>
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}
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} catch (_) {}
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_alignmentStatus = null;
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_targetResult = null;
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}
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img.Image? _convertCameraImage(CameraImage cameraImage) {
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@@ -510,16 +468,16 @@ class _CaptureScreenState extends State<CaptureScreen>
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),
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),
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// NOUVEAU : 1.bis Cadre dessiné autour de CHAQUE objet détecté
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if (_detectedObjects.isNotEmpty)
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// 1.bis Cercle dessiné autour de la cible circulaire détectée
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if (_targetResult != null && _targetResult!.success)
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Center(
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child: AspectRatio(
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aspectRatio: 3 / 4,
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child: CustomPaint(
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painter: _ObjectBoxPainter(
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objects: _detectedObjects,
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primary: _primaryObject,
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color: frameColor,
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painter: _TargetCirclePainter(
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target: _targetResult!,
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color: _targetReady ? frameColor : Colors.white,
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highlighted: _targetReady,
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),
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),
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),
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@@ -584,7 +542,6 @@ class _CaptureScreenState extends State<CaptureScreen>
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onPressed: () {
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_stopAlignmentDetection();
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_stopParallelismDetection(); // NOUVEAU
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_stopObjectDetection(); // NOUVEAU
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setState(() {
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_showLiveCamera = false;
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});
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@@ -793,7 +750,6 @@ class _CaptureScreenState extends State<CaptureScreen>
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_stopAlignmentDetection();
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_stopParallelismDetection(); // NOUVEAU
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_stopObjectDetection(); // NOUVEAU
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final XFile photo = await _cameraController!.takePicture();
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@@ -818,7 +774,7 @@ class _CaptureScreenState extends State<CaptureScreen>
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duration: const Duration(seconds: 2),
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content: Text(
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'Cible redressée automatiquement '
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'(inclinaison ${result.estimatedTiltDegrees.toStringAsFixed(1)}° corrigée)',
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'(inclinaison ${result.estimatedTiltDegrees.toStringAsFixed(1)}° corrigée)',
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),
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),
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);
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@@ -938,66 +894,66 @@ class _CaptureScreenState extends State<CaptureScreen>
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}
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// ─────────────────────────────────────────────────────────────────────────
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// Painter qui dessine la boîte englobante de CHAQUE objet détecté.
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// L'objet principal (le plus grand et centré) est mis en évidence avec
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// la couleur d'état (vert/orange) ; les autres en blanc translucide.
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// Painter qui dessine un cercle autour de la cible circulaire détectée.
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// Le centre et le rayon viennent d'OpenCV (coordonnées normalisées 0..1).
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// Blanc tant que la cible n'est pas bien cadrée, couleur d'état sinon.
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// ─────────────────────────────────────────────────────────────────────────
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class _ObjectBoxPainter extends CustomPainter {
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final List<DetectedObject2D> objects;
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final DetectedObject2D? primary;
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class _TargetCirclePainter extends CustomPainter {
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final TargetDetectionResult target;
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final Color color;
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final bool highlighted;
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_ObjectBoxPainter({
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required this.objects,
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required this.primary,
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_TargetCirclePainter({
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required this.target,
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required this.color,
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required this.highlighted,
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});
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@override
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void paint(Canvas canvas, Size size) {
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for (final obj in objects) {
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final bool isPrimary = identical(obj, primary);
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final Color boxColor =
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isPrimary ? color : Colors.white.withValues(alpha: 0.6);
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// Centre en pixels dans la zone de dessin
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final double cx = target.centerX * size.width;
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final double cy = target.centerY * size.height;
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// radius est normalisé par min(largeur, hauteur) côté OpenCV
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final double r = target.radius * math.min(size.width, size.height);
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final Paint stroke = Paint()
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..style = PaintingStyle.stroke
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..strokeWidth = isPrimary ? 3.0 : 1.5
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..color = boxColor;
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final Paint stroke = Paint()
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..style = PaintingStyle.stroke
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..strokeWidth = highlighted ? 3.5 : 2.0
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..color = color;
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final Rect rect = Rect.fromLTRB(
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obj.left * size.width,
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obj.top * size.height,
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obj.right * size.width,
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obj.bottom * size.height,
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);
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final RRect rrect =
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RRect.fromRectAndRadius(rect, const Radius.circular(8));
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canvas.drawRRect(rrect, stroke);
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// Cercle principal autour de la cible
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canvas.drawCircle(Offset(cx, cy), r, stroke);
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if (obj.label.isNotEmpty) {
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final textPainter = TextPainter(
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text: TextSpan(
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text: ' ${obj.label} '
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'${(obj.confidence * 100).toStringAsFixed(0)}% ',
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style: TextStyle(
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color: Colors.black,
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fontSize: 12,
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fontWeight: FontWeight.bold,
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backgroundColor: boxColor,
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),
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// Petite croix au centre détecté
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final Paint cross = Paint()
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..strokeWidth = 2.0
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..color = color;
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const double k = 10;
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canvas.drawLine(Offset(cx - k, cy), Offset(cx + k, cy), cross);
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canvas.drawLine(Offset(cx, cy - k), Offset(cx, cy + k), cross);
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// Étiquette "CIBLE" quand elle est bien cadrée
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if (highlighted) {
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final tp = TextPainter(
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text: TextSpan(
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text: ' CIBLE ',
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style: TextStyle(
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color: Colors.black,
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fontSize: 12,
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fontWeight: FontWeight.bold,
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backgroundColor: color,
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),
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textDirection: TextDirection.ltr,
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)..layout();
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textPainter.paint(
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canvas,
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Offset(rect.left, (rect.top - 18).clamp(0.0, size.height)),
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);
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}
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),
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textDirection: TextDirection.ltr,
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)..layout();
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tp.paint(canvas, Offset(cx - tp.width / 2, (cy - r - 20).clamp(0.0, size.height)));
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}
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}
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@override
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bool shouldRepaint(_ObjectBoxPainter old) =>
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old.objects != objects || old.color != color || old.primary != primary;
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}
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bool shouldRepaint(_TargetCirclePainter old) =>
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old.target != target ||
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old.color != color ||
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old.highlighted != highlighted;
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}
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@@ -1,186 +0,0 @@
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import 'dart:async';
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import 'package:flutter/foundation.dart';
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import 'package:flutter/services.dart';
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import 'package:camera/camera.dart';
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import 'package:google_mlkit_object_detection/google_mlkit_object_detection.dart';
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/// Un objet détecté, exprimé en coordonnées NORMALISÉES (0..1) par rapport
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/// à l'image source. Indépendant de la résolution réelle de la caméra.
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class DetectedObject2D {
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/// Boîte englobante normalisée (left, top, right, bottom dans [0..1]).
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final double left;
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final double top;
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final double right;
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final double bottom;
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/// Label le plus probable (ex: "Fruit", "Plant"...) — peut être vide.
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final String label;
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/// Confiance du label [0..1].
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final double confidence;
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const DetectedObject2D({
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required this.left,
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required this.top,
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required this.right,
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required this.bottom,
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required this.label,
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required this.confidence,
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});
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double get centerX => (left + right) / 2;
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double get centerY => (top + bottom) / 2;
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double get width => right - left;
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double get height => bottom - top;
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double get area => width * height;
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}
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/// Service de détection d'objets en temps réel basé sur Google ML Kit.
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///
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/// Traite directement les frames `CameraImage` du flux caméra (pas de
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/// passage par un fichier JPEG, donc beaucoup plus rapide qu'OpenCV ici).
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///
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/// Usage :
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/// final svc = ObjectDetectionService();
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/// svc.start();
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/// cameraController.startImageStream((frame) =>
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/// svc.processCameraImage(frame, cameraDescription, rotation));
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/// svc.stream.listen((objects) { ... });
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class ObjectDetectionService {
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ObjectDetector? _detector;
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final StreamController<List<DetectedObject2D>> _controller =
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StreamController<List<DetectedObject2D>>.broadcast();
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bool _isBusy = false;
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bool _started = false;
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Stream<List<DetectedObject2D>> get stream => _controller.stream;
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void start() {
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if (_started) return;
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_started = true;
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// Mode STREAM : optimisé pour le flux vidéo temps réel.
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// classifyObjects: true => label grossier + confiance par objet.
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// multipleObjects: true => on détecte et encadre TOUS les objets visibles.
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final options = ObjectDetectorOptions(
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mode: DetectionMode.stream,
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classifyObjects: true,
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multipleObjects: true,
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);
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_detector = ObjectDetector(options: options);
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}
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/// À appeler depuis `startImageStream`.
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Future<void> processCameraImage(
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CameraImage image,
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CameraDescription camera,
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DeviceOrientation deviceOrientation,
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) async {
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if (!_started || _detector == null) return;
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if (_isBusy) return; // On saute la frame si la précédente n'est pas finie
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_isBusy = true;
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try {
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final inputImage = _toInputImage(image, camera, deviceOrientation);
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if (inputImage == null) {
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_isBusy = false;
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return;
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}
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final objects = await _detector!.processImage(inputImage);
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final int imgW = image.width;
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final int imgH = image.height;
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final List<DetectedObject2D> results = objects.map((o) {
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final rect = o.boundingBox;
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String label = '';
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double conf = 0;
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if (o.labels.isNotEmpty) {
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final best = o.labels.reduce(
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(a, b) => a.confidence >= b.confidence ? a : b,
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);
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label = best.text;
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conf = best.confidence;
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}
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return DetectedObject2D(
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left: (rect.left / imgW).clamp(0.0, 1.0),
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top: (rect.top / imgH).clamp(0.0, 1.0),
|
||||
right: (rect.right / imgW).clamp(0.0, 1.0),
|
||||
bottom: (rect.bottom / imgH).clamp(0.0, 1.0),
|
||||
label: label,
|
||||
confidence: conf,
|
||||
);
|
||||
}).toList();
|
||||
|
||||
if (!_controller.isClosed) _controller.add(results);
|
||||
} catch (e) {
|
||||
debugPrint('ObjectDetection erreur: $e');
|
||||
} finally {
|
||||
_isBusy = false;
|
||||
}
|
||||
}
|
||||
|
||||
/// Convertit une CameraImage en InputImage ML Kit.
|
||||
InputImage? _toInputImage(
|
||||
CameraImage image,
|
||||
CameraDescription camera,
|
||||
DeviceOrientation deviceOrientation,
|
||||
) {
|
||||
// Rotation : combine l'orientation du capteur et celle de l'appareil.
|
||||
final sensorOrientation = camera.sensorOrientation;
|
||||
InputImageRotation? rotation;
|
||||
|
||||
if (defaultTargetPlatform == TargetPlatform.iOS) {
|
||||
rotation = InputImageRotationValue.fromRawValue(sensorOrientation);
|
||||
} else {
|
||||
// Android : table d'orientation
|
||||
var rotationCompensation = _orientations[deviceOrientation] ?? 0;
|
||||
if (camera.lensDirection == CameraLensDirection.front) {
|
||||
rotationCompensation =
|
||||
(sensorOrientation + rotationCompensation) % 360;
|
||||
} else {
|
||||
rotationCompensation =
|
||||
(sensorOrientation - rotationCompensation + 360) % 360;
|
||||
}
|
||||
rotation = InputImageRotationValue.fromRawValue(rotationCompensation);
|
||||
}
|
||||
if (rotation == null) return null;
|
||||
|
||||
final format = InputImageFormatValue.fromRawValue(image.format.raw);
|
||||
if (format == null) return null;
|
||||
|
||||
// ML Kit attend un seul plan contigu (NV21 sur Android, BGRA sur iOS).
|
||||
if (image.planes.isEmpty) return null;
|
||||
final plane = image.planes.first;
|
||||
|
||||
return InputImage.fromBytes(
|
||||
bytes: plane.bytes,
|
||||
metadata: InputImageMetadata(
|
||||
size: Size(image.width.toDouble(), image.height.toDouble()),
|
||||
rotation: rotation,
|
||||
format: format,
|
||||
bytesPerRow: plane.bytesPerRow,
|
||||
),
|
||||
);
|
||||
}
|
||||
|
||||
static const Map<DeviceOrientation, int> _orientations = {
|
||||
DeviceOrientation.portraitUp: 0,
|
||||
DeviceOrientation.landscapeLeft: 90,
|
||||
DeviceOrientation.portraitDown: 180,
|
||||
DeviceOrientation.landscapeRight: 270,
|
||||
};
|
||||
|
||||
void stop() {
|
||||
_started = false;
|
||||
}
|
||||
|
||||
void dispose() {
|
||||
stop();
|
||||
_detector?.close();
|
||||
_detector = null;
|
||||
_controller.close();
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user