diff --git a/analyze_log.txt b/analyze_log.txt new file mode 100644 index 0000000..a95adb7 --- /dev/null +++ b/analyze_log.txt @@ -0,0 +1,31 @@ +Analyzing bully... + + info - Statements in an if should be enclosed in a block - lib\features\analysis\analysis_screen.dart:122:17 - curly_braces_in_flow_control_structures + info - 'withOpacity' is deprecated and shouldn't be used. Use .withValues() to avoid precision loss - lib\features\analysis\analysis_screen.dart:650:51 - deprecated_member_use +warning - The declaration '_showAddShotHint' isn't referenced - lib\features\analysis\analysis_screen.dart:1083:8 - unused_element +warning - The declaration '_showAutoDetectDialog' isn't referenced - lib\features\analysis\analysis_screen.dart:1120:8 - unused_element +warning - Unused import: 'widgets/target_type_selector.dart' - lib\features\capture\capture_screen.dart:16:8 - unused_import + info - The private field _selectedType could be 'final' - lib\features\capture\capture_screen.dart:28:14 - prefer_final_fields + info - 'scale' is deprecated and shouldn't be used. Use scaleByVector3, scaleByVector4, or scaleByDouble instead - lib\features\crop\crop_screen.dart:141:25 - deprecated_member_use + info - The import of 'package:flutter/foundation.dart' is unnecessary because all of the used elements are also provided by the import of 'package:flutter/material.dart' - lib\features\statistics\statistics_screen.dart:8:8 - unnecessary_import +warning - The declaration '_buildLegendItem' isn't referenced - lib\features\statistics\statistics_screen.dart:309:10 - unused_element + info - Unnecessary use of string interpolation - lib\features\statistics\statistics_screen.dart:408:15 - unnecessary_string_interpolations + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:192:7 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:239:7 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:246:9 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:278:9 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:289:11 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:292:11 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:297:9 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:332:7 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:336:7 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:683:7 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:725:7 - avoid_print + info - Don't invoke 'print' in production code - lib\services\image_processing_service.dart:736:7 - avoid_print +warning - The declaration '_detectDarkSpotsAdaptive' isn't referenced - lib\services\image_processing_service.dart:780:15 - unused_element + info - Don't invoke 'print' in production code - lib\services\opencv_impact_detection_service.dart:104:5 - avoid_print + info - Don't invoke 'print' in production code - lib\services\opencv_impact_detection_service.dart:116:5 - avoid_print + info - Don't invoke 'print' in production code - lib\services\target_detection_service.dart:297:7 - avoid_print + info - Don't invoke 'print' in production code - lib\services\target_detection_service.dart:342:7 - avoid_print + +27 issues found. (ran in 1.9s) diff --git a/analyze_opencv.txt b/analyze_opencv.txt new file mode 100644 index 0000000..3a964da Binary files /dev/null and b/analyze_opencv.txt differ diff --git a/android/app/src/main/AndroidManifest.xml b/android/app/src/main/AndroidManifest.xml index 86b2724..f7b80a6 100644 --- a/android/app/src/main/AndroidManifest.xml +++ b/android/app/src/main/AndroidManifest.xml @@ -1,4 +1,6 @@ + + A failure occurred while executing com.android.build.gradle.internal.res.LinkApplicationAndroidResourcesTask$TaskAction + > Android resource linking failed + ERROR: C:\Users\streaper2\Documents\00 - projet\bully\build\cunning_document_scanner\intermediates\merged_manifest\debug\processDebugManifest\AndroidManifest.xml:9:5-65: AAPT: error: unexpected element found in . + + +* Try: +> Run with --stacktrace option to get the stack trace. +> Run with --info or --debug option to get more log output. +> Run with --scan to get full insights. +> Get more help at https://help.gradle.org. + +BUILD FAILED in 5s +Running Gradle task 'assembleDebug'... 5,4s +Gradle task assembleDebug failed with exit code 1 diff --git a/ios/Runner/Info.plist b/ios/Runner/Info.plist index 0ae7f1a..bf8159c 100644 --- a/ios/Runner/Info.plist +++ b/ios/Runner/Info.plist @@ -2,6 +2,8 @@ + NSCameraUsageDescription + This app needs camera access to scan documents CADisableMinimumFrameDurationOnPhone CFBundleDevelopmentRegion diff --git a/lib/features/analysis/analysis_provider.dart b/lib/features/analysis/analysis_provider.dart index 3ab4cc1..10519b6 100644 --- a/lib/features/analysis/analysis_provider.dart +++ b/lib/features/analysis/analysis_provider.dart @@ -17,6 +17,7 @@ import '../../services/target_detection_service.dart'; import '../../services/score_calculator_service.dart'; import '../../services/grouping_analyzer_service.dart'; import '../../services/distortion_correction_service.dart'; +import '../../services/opencv_target_service.dart'; enum AnalysisState { initial, loading, success, error } @@ -26,6 +27,7 @@ class AnalysisProvider extends ChangeNotifier { final GroupingAnalyzerService _groupingAnalyzerService; final SessionRepository _sessionRepository; final DistortionCorrectionService _distortionService; + final OpenCVTargetService _opencvTargetService; final Uuid _uuid = const Uuid(); AnalysisProvider({ @@ -34,11 +36,13 @@ class AnalysisProvider extends ChangeNotifier { required GroupingAnalyzerService groupingAnalyzerService, required SessionRepository sessionRepository, DistortionCorrectionService? distortionService, + OpenCVTargetService? opencvTargetService, }) : _detectionService = detectionService, _scoreCalculatorService = scoreCalculatorService, _groupingAnalyzerService = groupingAnalyzerService, _sessionRepository = sessionRepository, - _distortionService = distortionService ?? DistortionCorrectionService(); + _distortionService = distortionService ?? DistortionCorrectionService(), + _opencvTargetService = opencvTargetService ?? OpenCVTargetService(); AnalysisState _state = AnalysisState.initial; String? _errorMessage; @@ -508,6 +512,24 @@ class AnalysisProvider extends ChangeNotifier { notifyListeners(); } + /// Auto-calibrate target using OpenCV + Future autoCalibrateTarget() async { + if (_imagePath == null) return false; + + try { + final result = await _opencvTargetService.detectTarget(_imagePath!); + + if (result.success) { + adjustTargetPosition(result.centerX, result.centerY, result.radius); + return true; + } + return false; + } catch (e) { + print('Auto-calibration error: $e'); + return false; + } + } + /// Calcule les paramètres de distorsion basés sur la calibration actuelle void calculateDistortion() { _distortionParams = _distortionService.calculateDistortionFromCalibration( diff --git a/lib/features/analysis/analysis_screen.dart b/lib/features/analysis/analysis_screen.dart index e1d24dd..c5c4197 100644 --- a/lib/features/analysis/analysis_screen.dart +++ b/lib/features/analysis/analysis_screen.dart @@ -118,8 +118,9 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { actions: [ Consumer( builder: (context, provider, _) { - if (provider.state != AnalysisState.success) + if (provider.state != AnalysisState.success) { return const SizedBox.shrink(); + } return IconButton( icon: Icon(_isCalibrating ? Icons.check : Icons.tune), onPressed: () { @@ -273,6 +274,68 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { ), child: Column( children: [ + // Auto-calibrate button + /*SizedBox( + width: double.infinity, + child: ElevatedButton.icon( + onPressed: () async { + ScaffoldMessenger.of(context).showSnackBar( + const SnackBar( + content: Row( + children: [ + SizedBox( + width: 20, + height: 20, + child: CircularProgressIndicator( + strokeWidth: 2, + color: Colors.white, + ), + ), + SizedBox(width: 12), + Text('Auto-calibration en cours...'), + ], + ), + duration: Duration(seconds: 2), + ), + ); + + final success = await provider + .autoCalibrateTarget(); + + if (context.mounted) { + ScaffoldMessenger.of( + context, + ).hideCurrentSnackBar(); + if (success) { + ScaffoldMessenger.of(context).showSnackBar( + const SnackBar( + content: Text( + 'Cible calibrée automatiquement', + ), + backgroundColor: AppTheme.successColor, + ), + ); + } else { + ScaffoldMessenger.of(context).showSnackBar( + const SnackBar( + content: Text( + 'Échec de la calibration auto', + ), + backgroundColor: AppTheme.errorColor, + ), + ); + } + } + }, + icon: const Icon(Icons.auto_fix_high), + label: const Text('Auto-Calibrer la Cible'), + style: ElevatedButton.styleFrom( + backgroundColor: Colors.deepPurple, + foregroundColor: Colors.white, + ), + ), + ),*/ + const SizedBox(height: 16), // Ring count slider Row( children: [ @@ -375,7 +438,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { ), const Divider(color: Colors.white24, height: 16), // Distortion correction row - Row( + /*Row( children: [ const Icon( Icons.lens_blur, @@ -440,19 +503,19 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { ), ), const SizedBox(width: 8), - Switch( + /*Switch( value: provider.distortionCorrectionEnabled, onChanged: (value) => provider .setDistortionCorrectionEnabled(value), activeTrackColor: AppTheme.primaryColor .withValues(alpha: 0.5), activeThumbColor: AppTheme.primaryColor, - ), + ),*/ ], ), ], ], - ), + ),*/ ], ), ), @@ -647,7 +710,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { boxShadow: [ if (!_isAtBottom) BoxShadow( - color: Colors.black.withOpacity(0.2), + color: Colors.black.withValues(alpha: 0.2), blurRadius: 6, offset: const Offset(0, 3), ), @@ -1080,6 +1143,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { ); } + /* void _showAddShotHint(BuildContext context) { ScaffoldMessenger.of(context).showSnackBar( const SnackBar( @@ -1088,6 +1152,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { ), ); } + */ void _showClearConfirmation(BuildContext context, AnalysisProvider provider) { showDialog( @@ -1117,6 +1182,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { ); } + /* void _showAutoDetectDialog(BuildContext context, AnalysisProvider provider) { // Detection settings bool clearExisting = true; @@ -1315,6 +1381,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> { ), ); } + */ void _showCalibratedDetectionDialog( BuildContext context, diff --git a/lib/features/capture/capture_screen.dart b/lib/features/capture/capture_screen.dart index ee0cc45..0fc969f 100644 --- a/lib/features/capture/capture_screen.dart +++ b/lib/features/capture/capture_screen.dart @@ -6,13 +6,13 @@ library; import 'dart:io'; +import 'package:google_mlkit_document_scanner/google_mlkit_document_scanner.dart'; import 'package:flutter/material.dart'; import 'package:image_picker/image_picker.dart'; import '../../core/constants/app_constants.dart'; import '../../core/theme/app_theme.dart'; import '../../data/models/target_type.dart'; import '../crop/crop_screen.dart'; -import 'widgets/target_type_selector.dart'; import 'widgets/image_source_button.dart'; class CaptureScreen extends StatefulWidget { @@ -31,24 +31,12 @@ class _CaptureScreenState extends State { @override Widget build(BuildContext context) { return Scaffold( - appBar: AppBar( - title: const Text('Nouvelle Analyse'), - ), + appBar: AppBar(title: const Text('Nouvelle Analyse')), body: SingleChildScrollView( padding: const EdgeInsets.all(AppConstants.defaultPadding), child: Column( crossAxisAlignment: CrossAxisAlignment.stretch, children: [ - // TODO: une fois la cible de silhouette mise en place, rajouter le selecteur - // Target type selection - // _buildSectionTitle('Type de Cible'), - // const SizedBox(height: 12), - // TargetTypeSelector( - // selectedType: _selectedType, - // onTypeSelected: (type) { - // setState(() => _selectedType = type); - // }, - // ), const SizedBox(height: AppConstants.largePadding), // Image source selection @@ -59,8 +47,8 @@ class _CaptureScreenState extends State { Expanded( child: ImageSourceButton( icon: Icons.camera_alt, - label: 'Camera', - onPressed: _isLoading ? null : () => _captureImage(ImageSource.camera), + label: 'Scanner', + onPressed: _isLoading ? null : _scanDocument, ), ), const SizedBox(width: 12), @@ -68,7 +56,9 @@ class _CaptureScreenState extends State { child: ImageSourceButton( icon: Icons.photo_library, label: 'Galerie', - onPressed: _isLoading ? null : () => _captureImage(ImageSource.gallery), + onPressed: _isLoading + ? null + : () => _captureImage(ImageSource.gallery), ), ), ], @@ -87,16 +77,15 @@ class _CaptureScreenState extends State { _buildImagePreview(), // Guide text - if (_selectedImagePath == null && !_isLoading) - _buildGuide(), + if (_selectedImagePath == null && !_isLoading) _buildGuide(), ], ), ), floatingActionButton: _selectedImagePath != null ? FloatingActionButton.extended( onPressed: _analyzeImage, - icon: const Icon(Icons.analytics), - label: const Text('Analyser'), + icon: const Icon(Icons.arrow_forward), + label: const Text('Suivant'), ) : null, ); @@ -105,9 +94,9 @@ class _CaptureScreenState extends State { Widget _buildSectionTitle(String title) { return Text( title, - style: Theme.of(context).textTheme.titleMedium?.copyWith( - fontWeight: FontWeight.bold, - ), + style: Theme.of( + context, + ).textTheme.titleMedium?.copyWith(fontWeight: FontWeight.bold), ); } @@ -160,7 +149,9 @@ class _CaptureScreenState extends State { Expanded( child: Text( 'Assurez-vous que la cible est bien centree et visible.', - style: TextStyle(color: AppTheme.warningColor.withValues(alpha: 0.8)), + style: TextStyle( + color: AppTheme.warningColor.withValues(alpha: 0.8), + ), ), ), ], @@ -175,20 +166,19 @@ class _CaptureScreenState extends State { padding: const EdgeInsets.all(AppConstants.defaultPadding), child: Column( children: [ - Icon( - Icons.help_outline, - size: 48, - color: Colors.grey[400], - ), + Icon(Icons.help_outline, size: 48, color: Colors.grey[400]), const SizedBox(height: 12), Text( 'Conseils pour une bonne analyse', - style: Theme.of(context).textTheme.titleSmall?.copyWith( - fontWeight: FontWeight.bold, - ), + style: Theme.of( + context, + ).textTheme.titleSmall?.copyWith(fontWeight: FontWeight.bold), ), const SizedBox(height: 12), - _buildGuideItem(Icons.crop_free, 'Cadrez la cible entiere dans l\'image'), + _buildGuideItem( + Icons.crop_free, + 'Cadrez la cible entiere dans l\'image', + ), _buildGuideItem(Icons.wb_sunny, 'Utilisez un bon eclairage'), _buildGuideItem(Icons.straighten, 'Prenez la photo de face'), _buildGuideItem(Icons.blur_off, 'Evitez les images floues'), @@ -211,6 +201,39 @@ class _CaptureScreenState extends State { ); } + Future _scanDocument() async { + setState(() => _isLoading = true); + + try { + final options = DocumentScannerOptions( + documentFormat: DocumentFormat.jpeg, + mode: ScannerMode.base, + pageLimit: 1, + isGalleryImport: false, + ); + + final scanner = DocumentScanner(options: options); + final documents = await scanner.scanDocument(); + + if (documents.images.isNotEmpty) { + setState(() => _selectedImagePath = documents.images.first); + } + } catch (e) { + if (mounted) { + ScaffoldMessenger.of(context).showSnackBar( + SnackBar( + content: Text('Erreur lors du scan: $e'), + backgroundColor: AppTheme.errorColor, + ), + ); + } + } finally { + if (mounted) { + setState(() => _isLoading = false); + } + } + } + Future _captureImage(ImageSource source) async { setState(() => _isLoading = true); diff --git a/lib/features/crop/crop_screen.dart b/lib/features/crop/crop_screen.dart index b25995b..484a83d 100644 --- a/lib/features/crop/crop_screen.dart +++ b/lib/features/crop/crop_screen.dart @@ -119,7 +119,8 @@ class _CropScreenState extends State { _viewportSize = Size(constraints.maxWidth, constraints.maxHeight); // Taille du carré de crop (90% de la plus petite dimension) - _cropSize = math.min(constraints.maxWidth, constraints.maxHeight) * 0.85; + _cropSize = + math.min(constraints.maxWidth, constraints.maxHeight) * 0.85; // Calculer l'échelle initiale si pas encore fait if (_scale == 1.0 && _offset == Offset.zero) { @@ -138,7 +139,7 @@ class _CropScreenState extends State { child: Transform( transform: Matrix4.identity() ..setTranslationRaw(_offset.dx, _offset.dy, 0) - ..scale(_scale, _scale, 1.0), + ..scale(_scale, _scale), alignment: Alignment.center, child: Image.file( File(widget.imagePath), @@ -153,10 +154,7 @@ class _CropScreenState extends State { // Overlay de recadrage Positioned.fill( child: IgnorePointer( - child: CropOverlay( - cropSize: _cropSize, - showGrid: true, - ), + child: CropOverlay(cropSize: _cropSize, showGrid: true), ), ), diff --git a/lib/features/crop/widgets/crop_overlay.dart b/lib/features/crop/widgets/crop_overlay.dart index 075e2e4..2794d09 100644 --- a/lib/features/crop/widgets/crop_overlay.dart +++ b/lib/features/crop/widgets/crop_overlay.dart @@ -13,20 +13,13 @@ class CropOverlay extends StatelessWidget { /// Afficher la grille des tiers final bool showGrid; - const CropOverlay({ - super.key, - required this.cropSize, - this.showGrid = true, - }); + const CropOverlay({super.key, required this.cropSize, this.showGrid = true}); @override Widget build(BuildContext context) { return CustomPaint( size: Size.infinite, - painter: _CropOverlayPainter( - cropSize: cropSize, - showGrid: showGrid, - ), + painter: _CropOverlayPainter(cropSize: cropSize, showGrid: showGrid), ); } } @@ -35,10 +28,7 @@ class _CropOverlayPainter extends CustomPainter { final double cropSize; final bool showGrid; - _CropOverlayPainter({ - required this.cropSize, - required this.showGrid, - }); + _CropOverlayPainter({required this.cropSize, required this.showGrid}); @override void paint(Canvas canvas, Size size) { @@ -77,6 +67,9 @@ class _CropOverlayPainter extends CustomPainter { if (showGrid) { _drawGrid(canvas, cropRect); } + + // Dessiner le point central (croix) + _drawCenterPoint(canvas, cropRect); } void _drawCorners(Canvas canvas, Rect rect) { @@ -171,6 +164,38 @@ class _CropOverlayPainter extends CustomPainter { ); } + void _drawCenterPoint(Canvas canvas, Rect rect) { + final centerPaint = Paint() + ..color = Colors.white.withValues(alpha: 0.8) + ..style = PaintingStyle.stroke + ..strokeWidth = 2; + + const size = 10.0; + final centerX = rect.center.dx; + final centerY = rect.center.dy; + + // Ligne horizontale + canvas.drawLine( + Offset(centerX - size, centerY), + Offset(centerX + size, centerY), + centerPaint, + ); + + // Ligne verticale + canvas.drawLine( + Offset(centerX, centerY - size), + Offset(centerX, centerY + size), + centerPaint, + ); + + // Petit cercle central pour précision (optionnel, mais aide à viser) + canvas.drawCircle( + rect.center, + 2, + Paint()..color = Colors.red.withValues(alpha: 0.6), + ); + } + @override bool shouldRepaint(covariant _CropOverlayPainter oldDelegate) { return cropSize != oldDelegate.cropSize || showGrid != oldDelegate.showGrid; diff --git a/lib/features/statistics/statistics_screen.dart b/lib/features/statistics/statistics_screen.dart index f020461..f77edc1 100644 --- a/lib/features/statistics/statistics_screen.dart +++ b/lib/features/statistics/statistics_screen.dart @@ -5,7 +5,6 @@ /// écart-type et distribution régionale des tirs. library; -import 'package:flutter/foundation.dart'; import 'package:flutter/material.dart'; import 'package:provider/provider.dart'; import '../../core/constants/app_constants.dart'; @@ -69,28 +68,38 @@ class _StatisticsScreenState extends State { } void _calculateStats() { - debugPrint('Calculating stats for ${_allSessions.length} sessions, period: $_selectedPeriod'); + debugPrint( + 'Calculating stats for ${_allSessions.length} sessions, period: $_selectedPeriod', + ); for (final session in _allSessions) { - debugPrint(' Session: ${session.id}, shots: ${session.shots.length}, date: ${session.createdAt}'); + debugPrint( + ' Session: ${session.id}, shots: ${session.shots.length}, date: ${session.createdAt}', + ); } _statistics = _statisticsService.calculateStatistics( _allSessions, period: _selectedPeriod, ); - debugPrint('Statistics result: totalShots=${_statistics?.totalShots}, totalScore=${_statistics?.totalScore}'); + debugPrint( + 'Statistics result: totalShots=${_statistics?.totalShots}, totalScore=${_statistics?.totalScore}', + ); } @override Widget build(BuildContext context) { return Scaffold( appBar: AppBar( - title: Text(widget.singleSession != null ? 'Statistiques Session' : 'Statistiques'), + title: Text( + widget.singleSession != null + ? 'Statistiques Session' + : 'Statistiques', + ), ), body: _isLoading ? const Center(child: CircularProgressIndicator()) : _statistics == null || _statistics!.totalShots == 0 - ? _buildEmptyState() - : _buildStatistics(), + ? _buildEmptyState() + : _buildStatistics(), ); } @@ -101,7 +110,11 @@ class _StatisticsScreenState extends State { child: Column( mainAxisAlignment: MainAxisAlignment.center, children: [ - Icon(Icons.analytics_outlined, size: 64, color: Colors.grey.shade400), + Icon( + Icons.analytics_outlined, + size: 64, + color: Colors.grey.shade400, + ), const SizedBox(height: 16), Text( 'Aucune donnee disponible', @@ -292,11 +305,17 @@ class _StatisticsScreenState extends State { children: [ Padding( padding: const EdgeInsets.only(left: 16), - child: Text('Peu', style: TextStyle(fontSize: 12, color: Colors.grey.shade600)), + child: Text( + 'Peu', + style: TextStyle(fontSize: 12, color: Colors.grey.shade600), + ), ), Padding( padding: const EdgeInsets.only(right: 16), - child: Text('Beaucoup', style: TextStyle(fontSize: 12, color: Colors.grey.shade600)), + child: Text( + 'Beaucoup', + style: TextStyle(fontSize: 12, color: Colors.grey.shade600), + ), ), ], ), @@ -306,28 +325,6 @@ class _StatisticsScreenState extends State { ); } - Widget _buildLegendItem(Color color, String label) { - return Padding( - padding: const EdgeInsets.symmetric(horizontal: 4), - child: Row( - mainAxisSize: MainAxisSize.min, - children: [ - Container( - width: 16, - height: 16, - decoration: BoxDecoration( - color: color, - borderRadius: BorderRadius.circular(2), - border: Border.all(color: Colors.grey.shade400), - ), - ), - const SizedBox(width: 4), - Text(label, style: const TextStyle(fontSize: 10)), - ], - ), - ); - } - Widget _buildPrecisionSection() { final precision = _statistics!.precision; @@ -339,7 +336,10 @@ class _StatisticsScreenState extends State { children: [ Row( children: [ - const Icon(Icons.center_focus_strong, color: AppTheme.successColor), + const Icon( + Icons.center_focus_strong, + color: AppTheme.successColor, + ), const SizedBox(width: 8), const Text( 'Precision', @@ -368,12 +368,18 @@ class _StatisticsScreenState extends State { ], ), const Divider(height: 32), - _buildStatRow('Distance moyenne du centre', - '${(precision.avgDistanceFromCenter * 100).toStringAsFixed(1)}%'), - _buildStatRow('Diametre de groupement', - '${(precision.groupingDiameter * 100).toStringAsFixed(1)}%'), - _buildStatRow('Score moyen', - _statistics!.avgScore.toStringAsFixed(2)), + _buildStatRow( + 'Distance moyenne du centre', + '${(precision.avgDistanceFromCenter * 100).toStringAsFixed(1)}%', + ), + _buildStatRow( + 'Diametre de groupement', + '${(precision.groupingDiameter * 100).toStringAsFixed(1)}%', + ), + _buildStatRow( + 'Score moyen', + _statistics!.avgScore.toStringAsFixed(2), + ), _buildStatRow('Meilleur score', '${_statistics!.maxScore}'), _buildStatRow('Plus bas score', '${_statistics!.minScore}'), ], @@ -386,8 +392,8 @@ class _StatisticsScreenState extends State { final color = value > 70 ? AppTheme.successColor : value > 40 - ? AppTheme.warningColor - : AppTheme.errorColor; + ? AppTheme.warningColor + : AppTheme.errorColor; return Column( children: [ @@ -405,7 +411,7 @@ class _StatisticsScreenState extends State { ), ), Text( - '${value.toStringAsFixed(0)}', + value.toStringAsFixed(0), style: TextStyle( fontSize: 20, fontWeight: FontWeight.bold, @@ -415,10 +421,7 @@ class _StatisticsScreenState extends State { ], ), const SizedBox(height: 8), - Text( - title, - style: const TextStyle(fontWeight: FontWeight.bold), - ), + Text(title, style: const TextStyle(fontWeight: FontWeight.bold)), Text( subtitle, style: TextStyle(fontSize: 10, color: Colors.grey.shade600), @@ -439,7 +442,10 @@ class _StatisticsScreenState extends State { children: [ Row( children: [ - const Icon(Icons.stacked_line_chart, color: AppTheme.warningColor), + const Icon( + Icons.stacked_line_chart, + color: AppTheme.warningColor, + ), const SizedBox(width: 8), const Text( 'Ecart Type', @@ -453,21 +459,32 @@ class _StatisticsScreenState extends State { style: TextStyle(color: Colors.grey.shade600, fontSize: 12), ), const SizedBox(height: 16), - _buildStatRow('Ecart type X (horizontal)', - '${(stdDev.stdDevX * 100).toStringAsFixed(2)}%'), - _buildStatRow('Ecart type Y (vertical)', - '${(stdDev.stdDevY * 100).toStringAsFixed(2)}%'), - _buildStatRow('Ecart type radial', - '${(stdDev.stdDevRadial * 100).toStringAsFixed(2)}%'), - _buildStatRow('Ecart type score', - stdDev.stdDevScore.toStringAsFixed(2)), + _buildStatRow( + 'Ecart type X (horizontal)', + '${(stdDev.stdDevX * 100).toStringAsFixed(2)}%', + ), + _buildStatRow( + 'Ecart type Y (vertical)', + '${(stdDev.stdDevY * 100).toStringAsFixed(2)}%', + ), + _buildStatRow( + 'Ecart type radial', + '${(stdDev.stdDevRadial * 100).toStringAsFixed(2)}%', + ), + _buildStatRow( + 'Ecart type score', + stdDev.stdDevScore.toStringAsFixed(2), + ), const Divider(height: 24), - _buildStatRow('Position moyenne X', - '${(stdDev.meanX * 100).toStringAsFixed(1)}%'), - _buildStatRow('Position moyenne Y', - '${(stdDev.meanY * 100).toStringAsFixed(1)}%'), - _buildStatRow('Score moyen', - stdDev.meanScore.toStringAsFixed(2)), + _buildStatRow( + 'Position moyenne X', + '${(stdDev.meanX * 100).toStringAsFixed(1)}%', + ), + _buildStatRow( + 'Position moyenne Y', + '${(stdDev.meanY * 100).toStringAsFixed(1)}%', + ), + _buildStatRow('Score moyen', stdDev.meanScore.toStringAsFixed(2)), ], ), ), @@ -504,7 +521,10 @@ class _StatisticsScreenState extends State { ), child: Row( children: [ - const Icon(Icons.compass_calibration, color: AppTheme.primaryColor), + const Icon( + Icons.compass_calibration, + color: AppTheme.primaryColor, + ), const SizedBox(width: 12), Expanded( child: Column( @@ -536,7 +556,10 @@ class _StatisticsScreenState extends State { ), child: Row( children: [ - const Icon(Icons.warning_amber, color: AppTheme.warningColor), + const Icon( + Icons.warning_amber, + color: AppTheme.warningColor, + ), const SizedBox(width: 12), Expanded( child: Column( @@ -556,7 +579,10 @@ class _StatisticsScreenState extends State { const SizedBox(height: 16), // Sector distribution - const Text('Repartition par secteur:', style: TextStyle(fontWeight: FontWeight.bold)), + const Text( + 'Repartition par secteur:', + style: TextStyle(fontWeight: FontWeight.bold), + ), const SizedBox(height: 8), Wrap( spacing: 8, @@ -572,7 +598,10 @@ class _StatisticsScreenState extends State { const SizedBox(height: 16), // Quadrant distribution - const Text('Repartition par quadrant:', style: TextStyle(fontWeight: FontWeight.bold)), + const Text( + 'Repartition par quadrant:', + style: TextStyle(fontWeight: FontWeight.bold), + ), const SizedBox(height: 8), _buildQuadrantGrid(regional.quadrantDistribution), ], @@ -598,7 +627,9 @@ class _StatisticsScreenState extends State { return Container( padding: const EdgeInsets.symmetric(horizontal: 12, vertical: 6), decoration: BoxDecoration( - color: count > 0 ? AppTheme.primaryColor.withValues(alpha: 0.1) : Colors.grey.shade100, + color: count > 0 + ? AppTheme.primaryColor.withValues(alpha: 0.1) + : Colors.grey.shade100, borderRadius: BorderRadius.circular(16), border: Border.all( color: count > 0 ? AppTheme.primaryColor : Colors.grey.shade300, @@ -649,10 +680,7 @@ class _StatisticsScreenState extends State { children: [ Text( '$count', - style: const TextStyle( - fontWeight: FontWeight.bold, - fontSize: 24, - ), + style: const TextStyle(fontWeight: FontWeight.bold, fontSize: 24), ), Text( '${percentage.toStringAsFixed(0)}%', @@ -712,10 +740,7 @@ class _StatCard extends StatelessWidget { color: color, ), ), - Text( - title, - style: TextStyle(color: Colors.grey.shade600), - ), + Text(title, style: TextStyle(color: Colors.grey.shade600)), ], ), ), diff --git a/lib/services/distortion_correction_service.dart b/lib/services/distortion_correction_service.dart index 223360e..6acc10a 100644 --- a/lib/services/distortion_correction_service.dart +++ b/lib/services/distortion_correction_service.dart @@ -8,6 +8,7 @@ library; import 'dart:io'; import 'dart:math' as math; import 'package:image/image.dart' as img; +import 'package:opencv_dart/opencv_dart.dart' as cv; import 'package:path_provider/path_provider.dart'; /// Paramètres de distorsion calculés à partir de la calibration @@ -281,16 +282,56 @@ class DistortionCorrectionService { final p11 = image.getPixel(x1, y1); // Interpoler chaque canal - final r = _lerp2D(p00.r.toDouble(), p10.r.toDouble(), p01.r.toDouble(), p11.r.toDouble(), wx, wy); - final g = _lerp2D(p00.g.toDouble(), p10.g.toDouble(), p01.g.toDouble(), p11.g.toDouble(), wx, wy); - final b = _lerp2D(p00.b.toDouble(), p10.b.toDouble(), p01.b.toDouble(), p11.b.toDouble(), wx, wy); - final a = _lerp2D(p00.a.toDouble(), p10.a.toDouble(), p01.a.toDouble(), p11.a.toDouble(), wx, wy); + final r = _lerp2D( + p00.r.toDouble(), + p10.r.toDouble(), + p01.r.toDouble(), + p11.r.toDouble(), + wx, + wy, + ); + final g = _lerp2D( + p00.g.toDouble(), + p10.g.toDouble(), + p01.g.toDouble(), + p11.g.toDouble(), + wx, + wy, + ); + final b = _lerp2D( + p00.b.toDouble(), + p10.b.toDouble(), + p01.b.toDouble(), + p11.b.toDouble(), + wx, + wy, + ); + final a = _lerp2D( + p00.a.toDouble(), + p10.a.toDouble(), + p01.a.toDouble(), + p11.a.toDouble(), + wx, + wy, + ); - return img.ColorRgba8(r.round().clamp(0, 255), g.round().clamp(0, 255), b.round().clamp(0, 255), a.round().clamp(0, 255)); + return img.ColorRgba8( + r.round().clamp(0, 255), + g.round().clamp(0, 255), + b.round().clamp(0, 255), + a.round().clamp(0, 255), + ); } /// Interpolation linéaire 2D - double _lerp2D(double v00, double v10, double v01, double v11, double wx, double wy) { + double _lerp2D( + double v00, + double v10, + double v01, + double v11, + double wx, + double wy, + ) { final top = v00 * (1 - wx) + v10 * wx; final bottom = v01 * (1 - wx) + v11 * wx; return top * (1 - wy) + bottom * wy; @@ -320,7 +361,9 @@ class DistortionCorrectionService { final height = image.height; // Convertir les coordonnées normalisées en pixels - final srcCorners = corners.map((c) => (x: c.x * width, y: c.y * height)).toList(); + final srcCorners = corners + .map((c) => (x: c.x * width, y: c.y * height)) + .toList(); // Calculer la taille du rectangle destination // On prend la moyenne des largeurs et hauteurs @@ -336,20 +379,21 @@ class DistortionCorrectionService { final result = img.Image(width: dstWidth, height: dstHeight); // Calculer la matrice de transformation perspective - final matrix = _computePerspectiveMatrix( - srcCorners, - [ - (x: 0.0, y: 0.0), - (x: dstWidth.toDouble(), y: 0.0), - (x: dstWidth.toDouble(), y: dstHeight.toDouble()), - (x: 0.0, y: dstHeight.toDouble()), - ], - ); + final matrix = _computePerspectiveMatrix(srcCorners, [ + (x: 0.0, y: 0.0), + (x: dstWidth.toDouble(), y: 0.0), + (x: dstWidth.toDouble(), y: dstHeight.toDouble()), + (x: 0.0, y: dstHeight.toDouble()), + ]); // Appliquer la transformation for (int y = 0; y < dstHeight; y++) { for (int x = 0; x < dstWidth; x++) { - final src = _applyPerspectiveTransform(matrix, x.toDouble(), y.toDouble()); + final src = _applyPerspectiveTransform( + matrix, + x.toDouble(), + y.toDouble(), + ); if (src.x >= 0 && src.x < width && src.y >= 0 && src.y < height) { final pixel = _bilinearInterpolate(image, src.x, src.y); @@ -408,8 +452,11 @@ class DistortionCorrectionService { // Le système 'a' est de taille 8x9 (8 équations, 9 inconnues). // On fixe h8 = 1.0 pour résoudre le système, ce qui nous donne un système 8x8. final int n = 8; - final List> matrix = List.generate(n, (i) => List.from(a[i])); - + final List> matrix = List.generate( + n, + (i) => List.from(a[i]), + ); + // Vecteur B (les constantes de l'autre côté de l'égalité) // Dans DLT, -h8 * dx (ou dy) devient le terme constant. final List b = List.generate(n, (i) => -matrix[i][8]); @@ -428,7 +475,7 @@ class DistortionCorrectionService { final List tempRow = matrix[i]; matrix[i] = matrix[pivot]; matrix[pivot] = tempRow; - + final double tempB = b[i]; b[i] = b[pivot]; b[pivot] = tempB; @@ -462,7 +509,11 @@ class DistortionCorrectionService { return h; } - ({double x, double y}) _applyPerspectiveTransform(List h, double x, double y) { + ({double x, double y}) _applyPerspectiveTransform( + List h, + double x, + double y, + ) { final w = h[6] * x + h[7] * y + h[8]; if (w.abs() < 1e-10) { return (x: x, y: y); @@ -471,4 +522,158 @@ class DistortionCorrectionService { final ny = (h[3] * x + h[4] * y + h[5]) / w; return (x: nx, y: ny); } + + /// Corrige la perspective en se basant sur la détection de cercles (ellipses) + /// dans l'image. + /// + /// Cette méthode tente de détecter l'ellipse la plus proéminente (la cible) + /// et calcule une transformation pour la rendre parfaitement circulaire. + Future correctPerspectiveUsingCircles(String imagePath) async { + try { + // 1. Charger l'image avec OpenCV + final src = cv.imread(imagePath, flags: cv.IMREAD_COLOR); + if (src.isEmpty) throw Exception("Impossible de charger l'image"); + + // 2. Prétraitement + final gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY); + final blurred = cv.gaussianBlur(gray, (5, 5), 0); + + // Canny edge detector avec seuil adaptatif (Otsu) + final thresh = cv.threshold( + blurred, + 0, + 255, + cv.THRESH_BINARY | cv.THRESH_OTSU, + ); + final edges = cv.canny(blurred, thresh.$1 * 0.5, thresh.$1); + + // 3. Trouver les contours + final contoursResult = cv.findContours( + edges, + cv.RETR_EXTERNAL, + cv.CHAIN_APPROX_SIMPLE, + ); + final contours = contoursResult.$1; + + if (contours.isEmpty) return imagePath; // Pas de contours trouvés + + // 4. Trouver le meilleur candidat ellipse + cv.RotatedRect? bestEllipse; + double maxArea = 0; + + for (final contour in contours) { + if (contour.length < 5) + continue; // fitEllipse nécessite au moins 5 points + + final area = cv.contourArea(contour); + if (area < 1000) continue; // Ignorer les trop petits bruits + + final ellipse = cv.fitEllipse(contour); + + // Critère de sélection: on cherche la plus grande ellipse qui est proche d'un cercle + // Mais comme on veut corriger la distorsion, elle PEUT être aplatie. + // Donc on prend juste la plus grande ellipse raisonnablement centrée. + if (area > maxArea) { + maxArea = area; + bestEllipse = ellipse; + } + } + + if (bestEllipse == null) return imagePath; + + // 5. Calculer la transformation perspective + // L'idée est de mapper les 4 sommets de l'ellipse détectée vers un cercle parfait. + // Ou plus simplement, mapper le rectangle englobant de l'ellipse vers un carré. + + // Points source: les 4 coins du rotated rect de l'ellipse + // Note: opencv_dart RotatedRect points() non dispo directement? + // On peut utiliser boxPoints(ellipse) + final boxPoints = cv.boxPoints(bestEllipse); + // boxPoints returns Mat (4x2 float32) + + // Extraire les 4 points + final List srcPoints = []; + + for (int i = 0; i < boxPoints.length; i++) { + // On accède directement au point à l'index i + final point2f = boxPoints[i]; + + // On convertit les coordonnées float en int pour cv.Point + srcPoints.add(cv.Point(point2f.x.toInt(), point2f.y.toInt())); + } + + // Trier les points pour avoir: TL, TR, BR, BL + _sortPoints(srcPoints); + + // Dimensions cibles + final side = math + .max(bestEllipse.size.width, bestEllipse.size.height) + .toInt(); + + final List dstPoints = [ + cv.Point(0, 0), + cv.Point(side, 0), + cv.Point(side, side), + cv.Point(0, side), + ]; + + // Matrice de perspective + final M = cv.getPerspectiveTransform( + cv.VecPoint.fromList(srcPoints), + cv.VecPoint.fromList(dstPoints), + ); + + // 6. Warper l'image + final corrected = cv.warpPerspective(src, M, (side, side)); + + // 7. Sauvegarder + final tempDir = await getTemporaryDirectory(); + final timestamp = DateTime.now().millisecondsSinceEpoch; + final outputPath = '${tempDir.path}/corrected_circle_$timestamp.jpg'; + + cv.imwrite(outputPath, corrected); + + return outputPath; + } catch (e) { + // En cas d'erreur, retourner l'image originale + print('Erreur correction perspective cercles: $e'); + return imagePath; + } + } + + /// Trie les points dans l'ordre: Top-Left, Top-Right, Bottom-Right, Bottom-Left + void _sortPoints(List points) { + // Calculer le centre de gravité + double cx = 0; + double cy = 0; + for (final p in points) { + cx += p.x; + cy += p.y; + } + cx /= points.length; + cy /= points.length; + + points.sort((a, b) { + // Trier par angle autour du centre + final angleA = math.atan2(a.y - cy, a.x - cx); + final angleB = math.atan2(b.y - cy, b.x - cx); + return angleA.compareTo(angleB); + }); + + // Re-trier pour être sûr: + points.sort((a, b) => (a.y + a.x).compareTo(b.y + b.x)); + final tl = points[0]; + final br = points[3]; + + // Reste tr et bl + final remaining = [points[1], points[2]]; + remaining.sort((a, b) => a.x.compareTo(b.x)); + final bl = remaining[0]; + final tr = remaining[1]; + + points[0] = tl; + points[1] = tr; + points[2] = br; + points[3] = bl; + } } diff --git a/lib/services/opencv_impact_detection_service.dart b/lib/services/opencv_impact_detection_service.dart index 89f4b12..cfa32c6 100644 --- a/lib/services/opencv_impact_detection_service.dart +++ b/lib/services/opencv_impact_detection_service.dart @@ -1,13 +1,8 @@ /// Service de détection d'impacts utilisant OpenCV. -/// -/// NOTE: OpenCV est actuellement désactivé sur Windows en raison de problèmes -/// de compilation. Ce fichier contient des stubs qui permettent au code de -/// compiler sans OpenCV. Réactiver opencv_dart dans pubspec.yaml et -/// décommenter le code ci-dessous quand le support sera corrigé. library; -// import 'dart:math' as math; -// import 'package:opencv_dart/opencv_dart.dart' as cv; +import 'dart:math' as math; +import 'package:opencv_dart/opencv_dart.dart' as cv; /// Paramètres de détection d'impacts OpenCV class OpenCVDetectionSettings { @@ -90,30 +85,144 @@ class OpenCVDetectedImpact { } /// Service de détection d'impacts utilisant OpenCV -/// -/// NOTE: Actuellement désactivé - retourne des listes vides. -/// OpenCV n'est pas disponible sur Windows pour le moment. class OpenCVImpactDetectionService { /// Détecte les impacts dans une image en utilisant OpenCV - /// - /// STUB: Retourne une liste vide car OpenCV est désactivé. List detectImpacts( String imagePath, { OpenCVDetectionSettings settings = const OpenCVDetectionSettings(), }) { - print('OpenCV est désactivé - utilisation de la détection classique recommandée'); - return []; + try { + final img = cv.imread(imagePath, flags: cv.IMREAD_COLOR); + if (img.isEmpty) return []; + + final gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY); + + // Apply blur to reduce noise + final blurKSize = (settings.blurSize, settings.blurSize); + final blurred = cv.gaussianBlur(gray, blurKSize, 2, sigmaY: 2); + + final List detectedImpacts = []; + + final circles = cv.HoughCircles( + blurred, + cv.HOUGH_GRADIENT, + 1, + settings.minDist, + param1: settings.param1, + param2: settings.param2, + minRadius: settings.minRadius, + maxRadius: settings.maxRadius, + ); + + if (circles.rows > 0 && circles.cols > 0) { + // Mat shape: (1, N, 3) usually for HoughCircles (CV_32FC3) + // We use at directly. + + for (int i = 0; i < circles.cols; i++) { + final vec = circles.at(0, i); + final x = vec.val1; + final y = vec.val2; + final r = vec.val3; + + detectedImpacts.add( + OpenCVDetectedImpact( + x: x / img.cols, + y: y / img.rows, + radius: r, + confidence: 0.8, + method: 'hough', + ), + ); + } + } + + // 2. Contour Detection (if enabled) + if (settings.useContourDetection) { + // Canny edge detection + final edges = cv.canny( + blurred, + settings.cannyThreshold1, + settings.cannyThreshold2, + ); + + // Find contours + final contoursResult = cv.findContours( + edges, + cv.RETR_EXTERNAL, + cv.CHAIN_APPROX_SIMPLE, + ); + + final contours = contoursResult.$1; + // hierarchy is item2 + + for (int i = 0; i < contours.length; i++) { + final contour = contours[i]; + + // Filter by area + final area = cv.contourArea(contour); + if (area < settings.minContourArea || + area > settings.maxContourArea) { + continue; + } + + // Filter by circularity + final perimeter = cv.arcLength(contour, true); + if (perimeter == 0) continue; + final circularity = 4 * math.pi * area / (perimeter * perimeter); + + if (circularity < settings.minCircularity) continue; + + // Get bounding circle + final enclosingCircle = cv.minEnclosingCircle(contour); + final center = enclosingCircle.$1; + final radius = enclosingCircle.$2; + + // Avoid duplicates (simple distance check against Hough results) + bool isDuplicate = false; + for (final existing in detectedImpacts) { + final dx = existing.x * img.cols - center.x; + final dy = existing.y * img.rows - center.y; + final dist = math.sqrt(dx * dx + dy * dy); + if (dist < radius) { + isDuplicate = true; + break; + } + } + + if (!isDuplicate) { + detectedImpacts.add( + OpenCVDetectedImpact( + x: center.x / img.cols, + y: center.y / img.rows, + radius: radius, + confidence: circularity, // Use circularity as confidence + method: 'contour', + ), + ); + } + } + } + + return detectedImpacts; + } catch (e) { + // print('OpenCV Error: $e'); + return []; + } } /// Détecte les impacts en utilisant une image de référence - /// - /// STUB: Retourne une liste vide car OpenCV est désactivé. List detectFromReferences( String imagePath, List<({double x, double y})> referencePoints, { double tolerance = 2.0, }) { - print('OpenCV est désactivé - utilisation de la détection par références classique recommandée'); - return []; + // Basic implementation: use average color/brightness of reference points + // This is a placeholder for a more complex template matching or feature matching + + // For now, we can just run the standard detection but filter results + // based on properties of the reference points (e.g. size/radius if we had it). + + // Returning standard detection for now to enable the feature. + return detectImpacts(imagePath); } } diff --git a/lib/services/opencv_target_service.dart b/lib/services/opencv_target_service.dart new file mode 100644 index 0000000..6b2f9c0 --- /dev/null +++ b/lib/services/opencv_target_service.dart @@ -0,0 +1,235 @@ +import 'dart:math' as math; +import 'package:opencv_dart/opencv_dart.dart' as cv; + +class TargetDetectionResult { + final double centerX; + final double centerY; + final double radius; + final bool success; + + TargetDetectionResult({ + required this.centerX, + required this.centerY, + required this.radius, + this.success = true, + }); + + factory TargetDetectionResult.failure() { + return TargetDetectionResult( + centerX: 0.5, + centerY: 0.5, + radius: 0.4, + success: false, + ); + } +} + +class OpenCVTargetService { + /// Detect the main target (center and radius) from an image file + Future detectTarget(String imagePath) async { + try { + // Read image + final img = cv.imread(imagePath, flags: cv.IMREAD_COLOR); + if (img.isEmpty) { + return TargetDetectionResult.failure(); + } + + // Convert to grayscale + final gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY); + + // Apply Gaussian blur to reduce noise + final blurred = cv.gaussianBlur(gray, (9, 9), 2, sigmaY: 2); + + // Detect circles using Hough Transform + // Parameters need to be tuned for the specific target type + final circles = cv.HoughCircles( + blurred, + cv.HOUGH_GRADIENT, + 1, // dp: Inverse ratio of the accumulator resolution to the image resolution + (img.rows / 8) + .toDouble(), // minDist: Minimum distance between the centers of the detected circles + param1: 100, // param1: Gradient value for Canny edge detection + param2: + 30, // param2: Accumulator threshold for the circle centers at the detection stage + minRadius: img.cols ~/ 20, // minRadius + maxRadius: img.cols ~/ 2, // maxRadius + ); + + // HoughCircles returns a Mat of shape (1, N, 3) where N is number of circles. + // In opencv_dart, we cannot iterate easily. + // However, we can access data via pointer if needed, or check if Vec3f is supported. + // Given the user report, `at` likely failed compilation or runtime. + // Let's use a safer approach: assume standard memory layout (x, y, r, x, y, r...). + // Or use `at` carefully. + + // Better yet: try to use `circles.data` if available, but it returns a Pointer. + // Let's stick to `at` but use `double` and manual offset if Vec3f fails. + // actually, let's try to trust `at` for flattened access OR `at`. + // NOTE: `at` was reported as "method at not defined for VecPoint2f" earlier, NOT for Mat. + // The user error was for `VecPoint2f`. `Mat` definitely has `at`. + // BUT `VecPoint2f` is a List-like structure in Dart wrapper. + // usage of `at` on `VecPoint2f` was the error. + // Here `circles` IS A MAT. So `at` IS defined. + // However, to be safe and robust, and to implement clustering... + + if (circles.isEmpty) { + // Try with different parameters if first attempt fails (more lenient) + final looseCircles = cv.HoughCircles( + blurred, + cv.HOUGH_GRADIENT, + 1, + (img.rows / 8).toDouble(), + param1: 50, + param2: 20, + minRadius: img.cols ~/ 20, + maxRadius: img.cols ~/ 2, + ); + + if (looseCircles.isEmpty) { + return TargetDetectionResult.failure(); + } + return _findBestConcentricCircles(looseCircles, img.cols, img.rows); + } + + return _findBestConcentricCircles(circles, img.cols, img.rows); + } catch (e) { + // print('Error detecting target with OpenCV: $e'); + return TargetDetectionResult.failure(); + } + } + + TargetDetectionResult _findBestConcentricCircles( + cv.Mat circles, + int width, + int height, + ) { + if (circles.rows == 0 || circles.cols == 0) { + return TargetDetectionResult.failure(); + } + + final int numCircles = circles.cols; + final List<({double x, double y, double r})> detected = []; + + // Extract circles safely + // We'll use `at` assuming the Mat is (1, N, 3) float32 (CV_32FC3 usually) + // Actually HoughCircles usually returns CV_32FC3. + // So we can access `at(0, i)`. + // If that fails, we can fall back. But since `Mat` has `at`, it should work unless generic is bad. + // Let's assume it works for Mat but checking boundaries. + + // NOTE: If this throws "at not defined" (unlikely for Mat), we'd need another way. + // But since the previous error was on `VecPoint2f` (which is NOT a Mat), this should be fine. + + for (int i = 0; i < numCircles; i++) { + // Access using Vec3f if possible, or try to interpret memory + // Using `at` is the standard way. + final vec = circles.at(0, i); + detected.add((x: vec.val1, y: vec.val2, r: vec.val3)); + } + + if (detected.isEmpty) return TargetDetectionResult.failure(); + + // Cluster circles by center position + // We consider circles "concentric" if their centers are within 5% of image min dimension + final double tolerance = math.min(width, height) * 0.05; + final List> clusters = []; + + for (final circle in detected) { + bool added = false; + for (final cluster in clusters) { + // Check distance to cluster center (average of existing) + double clusterX = 0; + double clusterY = 0; + for (final c in cluster) { + clusterX += c.x; + clusterY += c.y; + } + clusterX /= cluster.length; + clusterY /= cluster.length; + + final dist = math.sqrt( + math.pow(circle.x - clusterX, 2) + math.pow(circle.y - clusterY, 2), + ); + + if (dist < tolerance) { + cluster.add(circle); + added = true; + break; + } + } + if (!added) { + clusters.add([circle]); + } + } + + // Find the best cluster + // 1. Prefer clusters with more circles (concentric rings) + // 2. Tie-break: closest to image center + + List<({double x, double y, double r})> bestCluster = clusters.first; + double bestScore = -1.0; + + for (final cluster in clusters) { + // Score calculation + // Base score = number of circles * 10 + double score = cluster.length * 10.0; + + // Penalize distance from center + double cx = 0, cy = 0; + for (final c in cluster) { + cx += c.x; + cy += c.y; + } + cx /= cluster.length; + cy /= cluster.length; + + final distFromCenter = math.sqrt( + math.pow(cx - width / 2, 2) + math.pow(cy - height / 2, 2), + ); + final relDist = distFromCenter / math.min(width, height); + + score -= relDist * 5.0; // Moderate penalty for off-center + + // Penalize very small clusters if they are just noise + // (Optional: check if radii are somewhat distributed?) + + if (score > bestScore) { + bestScore = score; + bestCluster = cluster; + } + } + + // Compute final result from best cluster + // Center: Use the smallest circle (bullseye) for best precision + // Radius: Use the largest circle (outer edge) for full coverage + + double centerX = 0; + double centerY = 0; + double maxR = 0; + double minR = double.infinity; + + for (final c in bestCluster) { + if (c.r > maxR) { + maxR = c.r; + } + if (c.r < minR) { + minR = c.r; + centerX = c.x; + centerY = c.y; + } + } + + // Fallback if something went wrong (shouldn't happen with non-empty cluster) + if (minR == double.infinity) { + centerX = bestCluster.first.x; + centerY = bestCluster.first.y; + } + + return TargetDetectionResult( + centerX: centerX / width, + centerY: centerY / height, + radius: maxR / math.min(width, height), + success: true, + ); + } +} diff --git a/pubspec.lock b/pubspec.lock index 62ca582..a76930f 100644 --- a/pubspec.lock +++ b/pubspec.lock @@ -25,6 +25,14 @@ packages: url: "https://pub.dev" source: hosted version: "2.1.2" + change_case: + dependency: transitive + description: + name: change_case + sha256: e41ef3df58521194ef8d7649928954805aeb08061917cf658322305e61568003 + url: "https://pub.dev" + source: hosted + version: "2.2.0" characters: dependency: transitive description: @@ -61,10 +69,10 @@ packages: dependency: transitive description: name: cross_file - sha256: "701dcfc06da0882883a2657c445103380e53e647060ad8d9dfb710c100996608" + sha256: "28bb3ae56f117b5aec029d702a90f57d285cd975c3c5c281eaca38dbc47c5937" url: "https://pub.dev" source: hosted - version: "0.3.5+1" + version: "0.3.5+2" crypto: dependency: transitive description: @@ -81,6 +89,14 @@ packages: url: "https://pub.dev" source: hosted version: "1.0.8" + dartcv4: + dependency: transitive + description: + name: dartcv4 + sha256: "43dba49162662f3b6e3daf5a95d071429365e2f1ada67d412b851fc9be442e58" + url: "https://pub.dev" + source: hosted + version: "2.2.1+1" equatable: dependency: transitive description: @@ -200,6 +216,14 @@ packages: url: "https://pub.dev" source: hosted version: "2.1.3" + google_mlkit_document_scanner: + dependency: "direct main" + description: + name: google_mlkit_document_scanner + sha256: "67428ddb853880c8185049a5834cd328e6420921a74786f6aadee0b76f8536bd" + url: "https://pub.dev" + source: hosted + version: "0.2.1" hooks: dependency: transitive description: @@ -244,10 +268,10 @@ packages: dependency: transitive description: name: image_picker_android - sha256: "5e9bf126c37c117cf8094215373c6d561117a3cfb50ebc5add1a61dc6e224677" + sha256: "518a16108529fc18657a3e6dde4a043dc465d16596d20ab2abd49a4cac2e703d" url: "https://pub.dev" source: hosted - version: "0.8.13+10" + version: "0.8.13+13" image_picker_for_web: dependency: transitive description: @@ -260,10 +284,10 @@ packages: dependency: transitive description: name: image_picker_ios - sha256: "956c16a42c0c708f914021666ffcd8265dde36e673c9fa68c81f7d085d9774ad" + sha256: b9c4a438a9ff4f60808c9cf0039b93a42bb6c2211ef6ebb647394b2b3fa84588 url: "https://pub.dev" source: hosted - version: "0.8.13+3" + version: "0.8.13+6" image_picker_linux: dependency: transitive description: @@ -384,6 +408,14 @@ packages: url: "https://pub.dev" source: hosted version: "0.17.4" + native_toolchain_cmake: + dependency: transitive + description: + name: native_toolchain_cmake + sha256: fe40e8483183ced98e851e08a9cd2a547fd412cccab98277aa23f2377e43d66f + url: "https://pub.dev" + source: hosted + version: "0.2.4" nested: dependency: transitive description: @@ -392,6 +424,14 @@ packages: url: "https://pub.dev" source: hosted version: "1.0.0" + opencv_dart: + dependency: "direct main" + description: + name: opencv_dart + sha256: c2b7cc614cad69c2857e9b684e3066af662a03fe7100f4dc9a630e81ad42103a + url: "https://pub.dev" + source: hosted + version: "2.2.1+1" path: dependency: "direct main" description: @@ -679,4 +719,4 @@ packages: version: "3.1.3" sdks: dart: ">=3.12.0-35.0.dev <4.0.0" - flutter: ">=3.35.0" + flutter: ">=3.38.1" diff --git a/pubspec.yaml b/pubspec.yaml index 7150431..e6bafe6 100644 --- a/pubspec.yaml +++ b/pubspec.yaml @@ -35,11 +35,11 @@ dependencies: # Use with the CupertinoIcons class for iOS style icons. cupertino_icons: ^1.0.8 - # Image processing with OpenCV (désactivé temporairement - problèmes de build Windows) - # opencv_dart: ^2.1.0 + opencv_dart: ^2.1.0 # Image capture from camera/gallery - image_picker: ^1.0.7 + image_picker: ^1.2.1 + google_mlkit_document_scanner: ^0.2.0 # Local database for history sqflite: ^2.3.2