Merge branch 'temp-fix'

detached branch a merge pour récupérer le travail

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)

android/app/src/main/AndroidManifest.xml

@@ -1,4 +1,6 @@
 <manifest xmlns:android="http://schemas.android.com/apk/res/android">
+    <uses-permission android:name="android.permission.CAMERA" />
+
     <application
         android:label="bully"
         android:name="${applicationName}"

build_log.txt

@@ -0,0 +1,20 @@
+Running Gradle task 'assembleDebug'...                          
+
+FAILURE: Build failed with an exception.
+
+* What went wrong:
+Execution failed for task ':app:processDebugResources'.
+> 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 <uses-permission> found in <manifest><application>.
+
+
+* 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

ios/Runner/Info.plist

@@ -2,6 +2,8 @@
 <!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
 <plist version="1.0">
 <dict>
+	<key>NSCameraUsageDescription</key>
+	<string>This app needs camera access to scan documents</string>
 	<key>CADisableMinimumFrameDurationOnPhone</key>
 	<true/>
 	<key>CFBundleDevelopmentRegion</key>

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<bool> 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(

lib/features/analysis/analysis_screen.dart

@@ -118,8 +118,9 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
         actions: [
           Consumer<AnalysisProvider>(
             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,

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<CaptureScreen> {
   @override
   Widget build(BuildContext context) {
     return Scaffold(
-      appBar: AppBar(
+      appBar: AppBar(title: const Text('Nouvelle Analyse')),
-        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<CaptureScreen> {
                 Expanded(
                   child: ImageSourceButton(
                     icon: Icons.camera_alt,
-                    label: 'Camera',
+                    label: 'Scanner',
-                    onPressed: _isLoading ? null : () => _captureImage(ImageSource.camera),
+                    onPressed: _isLoading ? null : _scanDocument,
                   ),
                 ),
                 const SizedBox(width: 12),
@@ -68,7 +56,9 @@ class _CaptureScreenState extends State<CaptureScreen> {
                   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<CaptureScreen> {
               _buildImagePreview(),
 
             // Guide text
-            if (_selectedImagePath == null && !_isLoading)
+            if (_selectedImagePath == null && !_isLoading) _buildGuide(),
-              _buildGuide(),
           ],
         ),
       ),
       floatingActionButton: _selectedImagePath != null
           ? FloatingActionButton.extended(
               onPressed: _analyzeImage,
-              icon: const Icon(Icons.analytics),
+              icon: const Icon(Icons.arrow_forward),
-              label: const Text('Analyser'),
+              label: const Text('Suivant'),
             )
           : null,
     );
@@ -105,9 +94,9 @@ class _CaptureScreenState extends State<CaptureScreen> {
   Widget _buildSectionTitle(String title) {
     return Text(
       title,
-      style: Theme.of(context).textTheme.titleMedium?.copyWith(
+      style: Theme.of(
-        fontWeight: FontWeight.bold,
+        context,
-      ),
+      ).textTheme.titleMedium?.copyWith(fontWeight: FontWeight.bold),
     );
   }
 
@@ -160,7 +149,9 @@ class _CaptureScreenState extends State<CaptureScreen> {
             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<CaptureScreen> {
         padding: const EdgeInsets.all(AppConstants.defaultPadding),
         child: Column(
           children: [
-            Icon(
+            Icon(Icons.help_outline, size: 48, color: Colors.grey[400]),
-              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(
+              style: Theme.of(
-                fontWeight: FontWeight.bold,
+                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<CaptureScreen> {
     );
   }
 
+  Future<void> _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<void> _captureImage(ImageSource source) async {
     setState(() => _isLoading = true);
 

lib/features/crop/crop_screen.dart

@@ -119,7 +119,8 @@ class _CropScreenState extends State<CropScreen> {
         _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<CropScreen> {
                   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<CropScreen> {
               // Overlay de recadrage
               Positioned.fill(
                 child: IgnorePointer(
-                  child: CropOverlay(
+                  child: CropOverlay(cropSize: _cropSize, showGrid: true),
-                    cropSize: _cropSize,
-                    showGrid: true,
-                  ),
                 ),
               ),
 

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({
+  const CropOverlay({super.key, required this.cropSize, this.showGrid = true});
-    super.key,
-    required this.cropSize,
-    this.showGrid = true,
-  });
 
   @override
   Widget build(BuildContext context) {
     return CustomPaint(
       size: Size.infinite,
-      painter: _CropOverlayPainter(
+      painter: _CropOverlayPainter(cropSize: cropSize, showGrid: showGrid),
-        cropSize: cropSize,
-        showGrid: showGrid,
-      ),
     );
   }
 }
@@ -35,10 +28,7 @@ class _CropOverlayPainter extends CustomPainter {
   final double cropSize;
   final bool showGrid;
 
-  _CropOverlayPainter({
+  _CropOverlayPainter({required this.cropSize, required this.showGrid});
-    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;

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<StatisticsScreen> {
   }
 
   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()
+          ? _buildEmptyState()
-              : _buildStatistics(),
+          : _buildStatistics(),
     );
   }
 
@@ -101,7 +110,11 @@ class _StatisticsScreenState extends State<StatisticsScreen> {
         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<StatisticsScreen> {
               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<StatisticsScreen> {
     );
   }
 
-  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<StatisticsScreen> {
           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<StatisticsScreen> {
               ],
             ),
             const Divider(height: 32),
-            _buildStatRow('Distance moyenne du centre',
+            _buildStatRow(
-              '${(precision.avgDistanceFromCenter * 100).toStringAsFixed(1)}%'),
+              'Distance moyenne du centre',
-            _buildStatRow('Diametre de groupement',
+              '${(precision.avgDistanceFromCenter * 100).toStringAsFixed(1)}%',
-              '${(precision.groupingDiameter * 100).toStringAsFixed(1)}%'),
+            ),
-            _buildStatRow('Score moyen',
+            _buildStatRow(
-              _statistics!.avgScore.toStringAsFixed(2)),
+              'Diametre de groupement',
+              '${(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<StatisticsScreen> {
     final color = value > 70
         ? AppTheme.successColor
         : value > 40
-            ? AppTheme.warningColor
+        ? AppTheme.warningColor
-            : AppTheme.errorColor;
+        : AppTheme.errorColor;
 
     return Column(
       children: [
@@ -405,7 +411,7 @@ class _StatisticsScreenState extends State<StatisticsScreen> {
               ),
             ),
             Text(
-              '${value.toStringAsFixed(0)}',
+              value.toStringAsFixed(0),
               style: TextStyle(
                 fontSize: 20,
                 fontWeight: FontWeight.bold,
@@ -415,10 +421,7 @@ class _StatisticsScreenState extends State<StatisticsScreen> {
           ],
         ),
         const SizedBox(height: 8),
-        Text(
+        Text(title, style: const TextStyle(fontWeight: FontWeight.bold)),
-          title,
-          style: const TextStyle(fontWeight: FontWeight.bold),
-        ),
         Text(
           subtitle,
           style: TextStyle(fontSize: 10, color: Colors.grey.shade600),
@@ -439,7 +442,10 @@ class _StatisticsScreenState extends State<StatisticsScreen> {
           children: [
             Row(
               children: [
-                const Icon(Icons.stacked_line_chart, color: AppTheme.warningColor),
+                const Icon(
+                  Icons.stacked_line_chart,
+                  color: AppTheme.warningColor,
+                ),
                 const SizedBox(width: 8),
                 const Text(
                   'Ecart Type',
@@ -453,21 +459,32 @@ class _StatisticsScreenState extends State<StatisticsScreen> {
               style: TextStyle(color: Colors.grey.shade600, fontSize: 12),
             ),
             const SizedBox(height: 16),
-            _buildStatRow('Ecart type X (horizontal)',
+            _buildStatRow(
-              '${(stdDev.stdDevX * 100).toStringAsFixed(2)}%'),
+              'Ecart type X (horizontal)',
-            _buildStatRow('Ecart type Y (vertical)',
+              '${(stdDev.stdDevX * 100).toStringAsFixed(2)}%',
-              '${(stdDev.stdDevY * 100).toStringAsFixed(2)}%'),
+            ),
-            _buildStatRow('Ecart type radial',
+            _buildStatRow(
-              '${(stdDev.stdDevRadial * 100).toStringAsFixed(2)}%'),
+              'Ecart type Y (vertical)',
-            _buildStatRow('Ecart type score',
+              '${(stdDev.stdDevY * 100).toStringAsFixed(2)}%',
-              stdDev.stdDevScore.toStringAsFixed(2)),
+            ),
+            _buildStatRow(
+              'Ecart type radial',
+              '${(stdDev.stdDevRadial * 100).toStringAsFixed(2)}%',
+            ),
+            _buildStatRow(
+              'Ecart type score',
+              stdDev.stdDevScore.toStringAsFixed(2),
+            ),
             const Divider(height: 24),
-            _buildStatRow('Position moyenne X',
+            _buildStatRow(
-              '${(stdDev.meanX * 100).toStringAsFixed(1)}%'),
+              'Position moyenne X',
-            _buildStatRow('Position moyenne Y',
+              '${(stdDev.meanX * 100).toStringAsFixed(1)}%',
-              '${(stdDev.meanY * 100).toStringAsFixed(1)}%'),
+            ),
-            _buildStatRow('Score moyen',
+            _buildStatRow(
-              stdDev.meanScore.toStringAsFixed(2)),
+              'Position moyenne Y',
+              '${(stdDev.meanY * 100).toStringAsFixed(1)}%',
+            ),
+            _buildStatRow('Score moyen', stdDev.meanScore.toStringAsFixed(2)),
           ],
         ),
       ),
@@ -504,7 +521,10 @@ class _StatisticsScreenState extends State<StatisticsScreen> {
               ),
               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<StatisticsScreen> {
                 ),
                 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<StatisticsScreen> {
             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<StatisticsScreen> {
             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<StatisticsScreen> {
     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<StatisticsScreen> {
         children: [
           Text(
             '$count',
-            style: const TextStyle(
+            style: const TextStyle(fontWeight: FontWeight.bold, fontSize: 24),
-              fontWeight: FontWeight.bold,
-              fontSize: 24,
-            ),
           ),
           Text(
             '${percentage.toStringAsFixed(0)}%',
@@ -712,10 +740,7 @@ class _StatCard extends StatelessWidget {
                 color: color,
               ),
             ),
-            Text(
+            Text(title, style: TextStyle(color: Colors.grey.shade600)),
-              title,
-              style: TextStyle(color: Colors.grey.shade600),
-            ),
           ],
         ),
       ),

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 r = _lerp2D(
-    final g = _lerp2D(p00.g.toDouble(), p10.g.toDouble(), p01.g.toDouble(), p11.g.toDouble(), wx, wy);
+      p00.r.toDouble(),
-    final b = _lerp2D(p00.b.toDouble(), p10.b.toDouble(), p01.b.toDouble(), p11.b.toDouble(), wx, wy);
+      p10.r.toDouble(),
-    final a = _lerp2D(p00.a.toDouble(), p10.a.toDouble(), p01.a.toDouble(), p11.a.toDouble(), wx, wy);
+      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(
+    final matrix = _computePerspectiveMatrix(srcCorners, [
-      srcCorners,
+      (x: 0.0, y: 0.0),
-      [
+      (x: dstWidth.toDouble(), y: 0.0),
-        (x: 0.0, y: 0.0),
+      (x: dstWidth.toDouble(), y: dstHeight.toDouble()),
-        (x: dstWidth.toDouble(), y: 0.0),
+      (x: 0.0, y: dstHeight.toDouble()),
-        (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);
@@ -408,7 +452,10 @@ 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<List<double>> matrix = List.generate(n, (i) => List<double>.from(a[i]));
+    final List<List<double>> matrix = List.generate(
+      n,
+      (i) => List<double>.from(a[i]),
+    );
 
     // Vecteur B (les constantes de l'autre côté de l'égalité)
     // Dans DLT, -h8 * dx (ou dy) devient le terme constant.
@@ -462,7 +509,11 @@ class DistortionCorrectionService {
     return h;
   }
 
-  ({double x, double y}) _applyPerspectiveTransform(List<double> h, double x, double y) {
+  ({double x, double y}) _applyPerspectiveTransform(
+    List<double> 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<String> 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<cv.Point> 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<cv.Point> 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<cv.Point> 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;
+  }
 }

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 'dart:math' as math;
-// import 'package:opencv_dart/opencv_dart.dart' as cv;
+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<OpenCVDetectedImpact> detectImpacts(
     String imagePath, {
     OpenCVDetectionSettings settings = const OpenCVDetectionSettings(),
   }) {
-    print('OpenCV est désactivé - utilisation de la détection classique recommandée');
+    try {
-    return [];
+      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<OpenCVDetectedImpact> 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<Vec3f> directly.
+
+        for (int i = 0; i < circles.cols; i++) {
+          final vec = circles.at<cv.Vec3f>(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<OpenCVDetectedImpact> 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');
+    // Basic implementation: use average color/brightness of reference points
-    return [];
+    // 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);
   }
 }

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<TargetDetectionResult> 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<Vec3f>` likely failed compilation or runtime.
+      // Let's use a safer approach: assume standard memory layout (x, y, r, x, y, r...).
+      // Or use `at<double>` 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<double>` for flattened access OR `at<Vec3f>`.
+      // NOTE: `at<Vec3f>` 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<double>` assuming the Mat is (1, N, 3) float32 (CV_32FC3 usually)
+    // Actually HoughCircles usually returns CV_32FC3.
+    // So we can access `at<cv.Vec3f>(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<cv.Vec3f>` is the standard way.
+      final vec = circles.at<cv.Vec3f>(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<List<({double x, double y, double r})>> 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,
+    );
+  }
+}

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"

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