preparation du modele yolo

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;
@@ -49,6 +53,7 @@ class AnalysisProvider extends ChangeNotifier {
   double _targetCenterX = 0.5;
   double _targetCenterY = 0.5;
   double _targetRadius = 0.4;
+  double _targetInnerRadius = 0.04;
   int _ringCount = 10;
   List<double>? _ringRadii; // Individual ring radii multipliers
   double _imageAspectRatio = 1.0; // width / height
@@ -79,6 +84,7 @@ class AnalysisProvider extends ChangeNotifier {
   double get targetCenterX => _targetCenterX;
   double get targetCenterY => _targetCenterY;
   double get targetRadius => _targetRadius;
+  double get targetInnerRadius => _targetInnerRadius;
   int get ringCount => _ringCount;
   List<double>? get ringRadii =>
       _ringRadii != null ? List.unmodifiable(_ringRadii!) : null;
@@ -134,6 +140,7 @@ class AnalysisProvider extends ChangeNotifier {
         _targetCenterX = 0.5;
         _targetCenterY = 0.5;
         _targetRadius = 0.4;
+        _targetInnerRadius = 0.04;
 
         // Initialize empty shots list
         _shots = [];
@@ -156,6 +163,7 @@ class AnalysisProvider extends ChangeNotifier {
       _targetCenterX = result.centerX;
       _targetCenterY = result.centerY;
       _targetRadius = result.radius;
+      _targetInnerRadius = result.radius * 0.1;
 
       // Create shots from detected impacts
       _shots = result.impacts.map((impact) {
@@ -484,12 +492,14 @@ class AnalysisProvider extends ChangeNotifier {
   void adjustTargetPosition(
     double centerX,
     double centerY,
+    double innerRadius,
     double radius, {
     int? ringCount,
     List<double>? ringRadii,
   }) {
     _targetCenterX = centerX;
     _targetCenterY = centerY;
+    _targetInnerRadius = innerRadius;
     _targetRadius = radius;
     if (ringCount != null) {
       _ringCount = ringCount;
@@ -508,6 +518,43 @@ class AnalysisProvider extends ChangeNotifier {
     notifyListeners();
   }
 
+  /// Auto-calibrate target using OpenCV
+  Future<bool> autoCalibrateTarget() async {
+    if (_imagePath == null) return false;
+
+    try {
+      // 1. Attempt to correct perspective/distortion first
+      final correctedPath = await _distortionService
+          .correctPerspectiveWithConcentricMesh(_imagePath!);
+
+      if (correctedPath != _imagePath) {
+        _imagePath = correctedPath;
+        _correctedImagePath = correctedPath;
+        _distortionCorrectionEnabled = true;
+        _imageAspectRatio =
+            1.0; // The corrected image is always square (side x side)
+        notifyListeners();
+      }
+
+      // 2. Detect the target on the straight/corrected image
+      final result = await _opencvTargetService.detectTarget(_imagePath!);
+
+      if (result.success) {
+        adjustTargetPosition(
+          result.centerX,
+          result.centerY,
+          result.radius * 0.1,
+          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(
@@ -665,6 +712,7 @@ class AnalysisProvider extends ChangeNotifier {
     _targetCenterX = 0.5;
     _targetCenterY = 0.5;
     _targetRadius = 0.4;
+    _targetInnerRadius = 0.04;
     _ringCount = 10;
     _ringRadii = null;
     _imageAspectRatio = 1.0;

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: [
@@ -298,6 +361,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                                 provider.adjustTargetPosition(
                                   provider.targetCenterX,
                                   provider.targetCenterY,
+                                  provider.targetInnerRadius,
                                   provider.targetRadius,
                                   ringCount: value.round(),
                                 );
@@ -348,6 +412,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                                 provider.adjustTargetPosition(
                                   provider.targetCenterX,
                                   provider.targetCenterY,
+                                  provider.targetInnerRadius,
                                   value,
                                   ringCount: provider.ringCount,
                                 );
@@ -375,7 +440,7 @@ 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 +505,19 @@ 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,
-                                  ),
+                                  ),*/
                                 ],
                               ),
                           ],
                         ],
-                      ),
+                      ),*/
                     ],
                   ),
                 ),
@@ -472,6 +537,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                             initialCenterX: provider.targetCenterX,
                             initialCenterY: provider.targetCenterY,
                             initialRadius: provider.targetRadius,
+                            initialInnerRadius: provider.targetInnerRadius,
                             initialRingCount: provider.ringCount,
                             initialRingRadii: provider.ringRadii,
                             targetType: provider.targetType!,
@@ -479,6 +545,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                                 (
                                   centerX,
                                   centerY,
+                                  innerRadius,
                                   radius,
                                   ringCount, {
                                   List<double>? ringRadii,
@@ -486,6 +553,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                                   provider.adjustTargetPosition(
                                     centerX,
                                     centerY,
+                                    innerRadius,
                                     radius,
                                     ringCount: ringCount,
                                     ringRadii: ringRadii,
@@ -647,7 +715,7 @@ 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 +1148,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
     );
   }
 
+  /*
   void _showAddShotHint(BuildContext context) {
     ScaffoldMessenger.of(context).showSnackBar(
       const SnackBar(
@@ -1088,6 +1157,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
       ),
     );
   }
+  */
 
   void _showClearConfirmation(BuildContext context, AnalysisProvider provider) {
     showDialog(
@@ -1117,6 +1187,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
     );
   }
 
+  /*
   void _showAutoDetectDialog(BuildContext context, AnalysisProvider provider) {
     // Detection settings
     bool clearExisting = true;
@@ -1315,6 +1386,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
       ),
     );
   }
+  */
 
   void _showCalibratedDetectionDialog(
     BuildContext context,

lib/features/analysis/widgets/target_calibration.dart

@@ -13,16 +13,26 @@ class TargetCalibration extends StatefulWidget {
   final double initialCenterX;
   final double initialCenterY;
   final double initialRadius;
+  final double initialInnerRadius;
   final int initialRingCount;
   final TargetType targetType;
   final List<double>? initialRingRadii;
-  final Function(double centerX, double centerY, double radius, int ringCount, {List<double>? ringRadii}) onCalibrationChanged;
+  final Function(
+    double centerX,
+    double centerY,
+    double innerRadius,
+    double radius,
+    int ringCount, {
+    List<double>? ringRadii,
+  })
+  onCalibrationChanged;
 
   const TargetCalibration({
     super.key,
     required this.initialCenterX,
     required this.initialCenterY,
     required this.initialRadius,
+    required this.initialInnerRadius,
     this.initialRingCount = 10,
     required this.targetType,
     this.initialRingRadii,
@@ -37,11 +47,13 @@ class _TargetCalibrationState extends State<TargetCalibration> {
   late double _centerX;
   late double _centerY;
   late double _radius;
+  late double _innerRadius;
   late int _ringCount;
   late List<double> _ringRadii;
 
   bool _isDraggingCenter = false;
   bool _isDraggingRadius = false;
+  bool _isDraggingInnerRadius = false;
 
   @override
   void initState() {
@@ -49,28 +61,57 @@ class _TargetCalibrationState extends State<TargetCalibration> {
     _centerX = widget.initialCenterX;
     _centerY = widget.initialCenterY;
     _radius = widget.initialRadius;
+    _innerRadius = widget.initialInnerRadius;
     _ringCount = widget.initialRingCount;
     _initRingRadii();
   }
 
   void _initRingRadii() {
-    if (widget.initialRingRadii != null && widget.initialRingRadii!.length == _ringCount) {
+    if (widget.initialRingRadii != null &&
+        widget.initialRingRadii!.length == _ringCount) {
       _ringRadii = List.from(widget.initialRingRadii!);
     } else {
-      // Initialize with default proportional radii
+      // Initialize with default proportional radii interpolated between inner and outer
-      _ringRadii = List.generate(_ringCount, (i) => (i + 1) / _ringCount);
+      _ringRadii = List.generate(_ringCount, (i) {
+        if (_ringCount <= 1) return 1.0;
+        final ratio = _innerRadius / _radius;
+        return ratio + (1.0 - ratio) * i / (_ringCount - 1);
+      });
     }
   }
 
   @override
   void didUpdateWidget(TargetCalibration oldWidget) {
     super.didUpdateWidget(oldWidget);
+    bool shouldReinit = false;
+
+    if (widget.initialCenterX != oldWidget.initialCenterX &&
+        !_isDraggingCenter) {
+      _centerX = widget.initialCenterX;
+    }
+    if (widget.initialCenterY != oldWidget.initialCenterY &&
+        !_isDraggingCenter) {
+      _centerY = widget.initialCenterY;
+    }
     if (widget.initialRingCount != oldWidget.initialRingCount) {
       _ringCount = widget.initialRingCount;
-      _initRingRadii();
+      shouldReinit = true;
     }
     if (widget.initialRadius != oldWidget.initialRadius && !_isDraggingRadius) {
       _radius = widget.initialRadius;
+      shouldReinit = true;
+    }
+    if (widget.initialInnerRadius != oldWidget.initialInnerRadius &&
+        !_isDraggingInnerRadius) {
+      _innerRadius = widget.initialInnerRadius;
+      shouldReinit = true;
+    }
+    if (widget.initialRingRadii != oldWidget.initialRingRadii) {
+      shouldReinit = true;
+    }
+
+    if (shouldReinit) {
+      _initRingRadii();
     }
   }
 
@@ -90,11 +131,13 @@ class _TargetCalibrationState extends State<TargetCalibration> {
               centerX: _centerX,
               centerY: _centerY,
               radius: _radius,
+              innerRadius: _innerRadius,
               ringCount: _ringCount,
               ringRadii: _ringRadii,
               targetType: widget.targetType,
               isDraggingCenter: _isDraggingCenter,
               isDraggingRadius: _isDraggingRadius,
+              isDraggingInnerRadius: _isDraggingInnerRadius,
             ),
           ),
         );
@@ -109,21 +152,42 @@ class _TargetCalibrationState extends State<TargetCalibration> {
     // Check if tapping on center handle
     final distToCenter = _distance(tapX, tapY, _centerX, _centerY);
 
-    // Check if tapping on radius handle (on the right edge of the outermost circle)
+    // Check if tapping on outer radius handle
     final minDim = math.min(size.width, size.height);
-    final outerRadius = _radius * (_ringRadii.isNotEmpty ? _ringRadii.last : 1.0);
+    final outerRadius = _radius;
     final radiusHandleX = _centerX + outerRadius * minDim / size.width;
     final radiusHandleY = _centerY;
-    final distToRadiusHandle = _distance(tapX, tapY, radiusHandleX.clamp(0.0, 1.0), radiusHandleY.clamp(0.0, 1.0));
+    final distToOuterHandle = _distance(
+      tapX,
+      tapY,
+      radiusHandleX.clamp(0.0, 1.0),
+      radiusHandleY.clamp(0.0, 1.0),
+    );
 
+    // Check if tapping on inner radius handle (top edge of innermost circle)
+    final actualInnerRadius = _innerRadius;
+    final innerHandleX = _centerX;
+    final innerHandleY = _centerY - actualInnerRadius * minDim / size.height;
+    final distToInnerHandle = _distance(
+      tapX,
+      tapY,
+      innerHandleX.clamp(0.0, 1.0),
+      innerHandleY.clamp(0.0, 1.0),
+    );
+
+    // Increase touch target size slightly for handles
     if (distToCenter < 0.05) {
       setState(() {
         _isDraggingCenter = true;
       });
-    } else if (distToRadiusHandle < 0.05) {
+    } else if (distToOuterHandle < 0.05) {
       setState(() {
         _isDraggingRadius = true;
       });
+    } else if (distToInnerHandle < 0.05) {
+      setState(() {
+        _isDraggingInnerRadius = true;
+      });
     } else if (distToCenter < _radius + 0.02) {
       // Tapping inside the target - move center
       setState(() {
@@ -143,19 +207,36 @@ class _TargetCalibrationState extends State<TargetCalibration> {
         _centerX = _centerX + deltaX;
         _centerY = _centerY + deltaY;
       } else if (_isDraggingRadius) {
-        // Adjust outer radius (scales all rings proportionally)
+        // Adjust outer radius
         final newRadius = _radius + deltaX * (size.width / minDim);
-        _radius = newRadius.clamp(0.05, 3.0);
+        _radius = newRadius.clamp(math.max(0.05, _innerRadius + 0.01), 3.0);
+        _initRingRadii(); // Recalculate linear separation
+      } else if (_isDraggingInnerRadius) {
+        // Adjust inner radius (sliding up reduces Y, so deltaY is negative when growing. Thus we subtract deltaY)
+        final newInnerRadius = _innerRadius - deltaY * (size.height / minDim);
+        _innerRadius = newInnerRadius.clamp(
+          0.01,
+          math.max(0.01, _radius - 0.01),
+        );
+        _initRingRadii(); // Recalculate linear separation
       }
     });
 
-    widget.onCalibrationChanged(_centerX, _centerY, _radius, _ringCount, ringRadii: _ringRadii);
+    widget.onCalibrationChanged(
+      _centerX,
+      _centerY,
+      _innerRadius,
+      _radius,
+      _ringCount,
+      ringRadii: _ringRadii,
+    );
   }
 
   void _onPanEnd() {
     setState(() {
       _isDraggingCenter = false;
       _isDraggingRadius = false;
+      _isDraggingInnerRadius = false;
     });
   }
 
@@ -170,21 +251,25 @@ class _CalibrationPainter extends CustomPainter {
   final double centerX;
   final double centerY;
   final double radius;
+  final double innerRadius;
   final int ringCount;
   final List<double> ringRadii;
   final TargetType targetType;
   final bool isDraggingCenter;
   final bool isDraggingRadius;
+  final bool isDraggingInnerRadius;
 
   _CalibrationPainter({
     required this.centerX,
     required this.centerY,
     required this.radius,
+    required this.innerRadius,
     required this.ringCount,
     required this.ringRadii,
     required this.targetType,
     required this.isDraggingCenter,
     required this.isDraggingRadius,
+    required this.isDraggingInnerRadius,
   });
 
   @override
@@ -192,6 +277,7 @@ class _CalibrationPainter extends CustomPainter {
     final centerPx = Offset(centerX * size.width, centerY * size.height);
     final minDim = size.width < size.height ? size.width : size.height;
     final baseRadiusPx = radius * minDim;
+    final innerRadiusPx = innerRadius * minDim;
 
     if (targetType == TargetType.concentric) {
       _drawConcentricZones(canvas, size, centerPx, baseRadiusPx);
@@ -199,17 +285,42 @@ class _CalibrationPainter extends CustomPainter {
       _drawSilhouetteZones(canvas, size, centerPx, baseRadiusPx);
     }
 
+    // Fullscreen crosshairs when dragging center
+    if (isDraggingCenter) {
+      final crosshairLinePaint = Paint()
+        ..color = AppTheme.successColor.withValues(alpha: 0.5)
+        ..strokeWidth = 1;
+      canvas.drawLine(
+        Offset(0, centerPx.dy),
+        Offset(size.width, centerPx.dy),
+        crosshairLinePaint,
+      );
+      canvas.drawLine(
+        Offset(centerPx.dx, 0),
+        Offset(centerPx.dx, size.height),
+        crosshairLinePaint,
+      );
+    }
+
     // Draw center handle
     _drawCenterHandle(canvas, centerPx);
 
     // Draw radius handle (for outer ring)
     _drawRadiusHandle(canvas, size, centerPx, baseRadiusPx);
 
+    // Draw inner radius handle
+    _drawInnerRadiusHandle(canvas, size, centerPx, innerRadiusPx);
+
     // Draw instructions
     _drawInstructions(canvas, size);
   }
 
-  void _drawConcentricZones(Canvas canvas, Size size, Offset center, double baseRadius) {
+  void _drawConcentricZones(
+    Canvas canvas,
+    Size size,
+    Offset center,
+    double baseRadius,
+  ) {
     // Generate colors for zones
     List<Color> zoneColors = [];
     for (int i = 0; i < ringCount; i++) {
@@ -235,7 +346,9 @@ class _CalibrationPainter extends CustomPainter {
 
     // Draw from outside to inside
     for (int i = ringCount - 1; i >= 0; i--) {
-      final ringRadius = ringRadii.length > i ? ringRadii[i] : (i + 1) / ringCount;
+      final ringRadius = ringRadii.length > i
+          ? ringRadii[i]
+          : (i + 1) / ringCount;
       final zoneRadius = baseRadius * ringRadius;
 
       zonePaint.color = zoneColors[i];
@@ -244,12 +357,12 @@ class _CalibrationPainter extends CustomPainter {
     }
 
     // Draw zone labels (only if within visible area)
-    final textPainter = TextPainter(
+    final textPainter = TextPainter(textDirection: TextDirection.ltr);
-      textDirection: TextDirection.ltr,
-    );
 
     for (int i = 0; i < ringCount; i++) {
-      final ringRadius = ringRadii.length > i ? ringRadii[i] : (i + 1) / ringCount;
+      final ringRadius = ringRadii.length > i
+          ? ringRadii[i]
+          : (i + 1) / ringCount;
       final prevRingRadius = i > 0
           ? (ringRadii.length > i - 1 ? ringRadii[i - 1] : i / ringCount)
           : 0.0;
@@ -268,9 +381,7 @@ class _CalibrationPainter extends CustomPainter {
           color: Colors.white.withValues(alpha: 0.9),
           fontSize: 12,
           fontWeight: FontWeight.bold,
-          shadows: const [
+          shadows: const [Shadow(color: Colors.black, blurRadius: 2)],
-            Shadow(color: Colors.black, blurRadius: 2),
-          ],
         ),
       );
       textPainter.layout();
@@ -278,14 +389,24 @@ class _CalibrationPainter extends CustomPainter {
       // Draw label on the right side of each zone
       final labelY = center.dy - textPainter.height / 2;
       if (labelY >= 0 && labelY <= size.height) {
-        textPainter.paint(canvas, Offset(labelX - textPainter.width / 2, labelY));
+        textPainter.paint(
+          canvas,
+          Offset(labelX - textPainter.width / 2, labelY),
+        );
       }
     }
   }
 
-  void _drawSilhouetteZones(Canvas canvas, Size size, Offset center, double radius) {
+  void _drawSilhouetteZones(
+    Canvas canvas,
+    Size size,
+    Offset center,
+    double radius,
+  ) {
     // Simplified silhouette zones
-    final paint = Paint()..style = PaintingStyle.stroke..strokeWidth = 2;
+    final paint = Paint()
+      ..style = PaintingStyle.stroke
+      ..strokeWidth = 2;
 
     // Draw silhouette outline (simplified as rectangle for now)
     final silhouetteWidth = radius * 0.8;
@@ -293,7 +414,11 @@ class _CalibrationPainter extends CustomPainter {
 
     paint.color = Colors.green.withValues(alpha: 0.5);
     canvas.drawRect(
-      Rect.fromCenter(center: center, width: silhouetteWidth, height: silhouetteHeight),
+      Rect.fromCenter(
+        center: center,
+        width: silhouetteWidth,
+        height: silhouetteHeight,
+      ),
       paint,
     );
   }
@@ -316,17 +441,36 @@ class _CalibrationPainter extends CustomPainter {
     final crossPaint = Paint()
       ..color = isDraggingCenter ? AppTheme.successColor : AppTheme.primaryColor
       ..strokeWidth = 2;
-    canvas.drawLine(Offset(center.dx - 20, center.dy), Offset(center.dx - 8, center.dy), crossPaint);
+    canvas.drawLine(
-    canvas.drawLine(Offset(center.dx + 8, center.dy), Offset(center.dx + 20, center.dy), crossPaint);
+      Offset(center.dx - 20, center.dy),
-    canvas.drawLine(Offset(center.dx, center.dy - 20), Offset(center.dx, center.dy - 8), crossPaint);
+      Offset(center.dx - 8, center.dy),
-    canvas.drawLine(Offset(center.dx, center.dy + 8), Offset(center.dx, center.dy + 20), crossPaint);
+      crossPaint,
+    );
+    canvas.drawLine(
+      Offset(center.dx + 8, center.dy),
+      Offset(center.dx + 20, center.dy),
+      crossPaint,
+    );
+    canvas.drawLine(
+      Offset(center.dx, center.dy - 20),
+      Offset(center.dx, center.dy - 8),
+      crossPaint,
+    );
+    canvas.drawLine(
+      Offset(center.dx, center.dy + 8),
+      Offset(center.dx, center.dy + 20),
+      crossPaint,
+    );
   }
 
-  void _drawRadiusHandle(Canvas canvas, Size size, Offset center, double baseRadius) {
+  void _drawRadiusHandle(
+    Canvas canvas,
+    Size size,
+    Offset center,
+    double baseRadius,
+  ) {
     // Radius handle on the right edge of the outermost ring
-    final outerRingRadius = ringRadii.isNotEmpty ? ringRadii.last : 1.0;
+    final actualHandleX = center.dx + baseRadius;
-    final actualRadius = baseRadius * outerRingRadius;
-    final actualHandleX = center.dx + actualRadius;
     final clampedHandleX = actualHandleX.clamp(20.0, size.width - 20);
     final clampedHandleY = center.dy.clamp(20.0, size.height - 20);
     final handlePos = Offset(clampedHandleX, clampedHandleY);
@@ -376,7 +520,7 @@ class _CalibrationPainter extends CustomPainter {
     // Label
     final textPainter = TextPainter(
       text: const TextSpan(
-        text: 'RAYON',
+        text: 'EXT.',
         style: TextStyle(
           color: Colors.white,
           fontSize: 8,
@@ -392,6 +536,78 @@ class _CalibrationPainter extends CustomPainter {
     );
   }
 
+  void _drawInnerRadiusHandle(
+    Canvas canvas,
+    Size size,
+    Offset center,
+    double innerRadiusPx,
+  ) {
+    // Inner radius handle on the top edge of the innermost ring
+    final actualHandleY = center.dy - innerRadiusPx;
+    final clampedHandleX = center.dx.clamp(20.0, size.width - 20);
+    final clampedHandleY = actualHandleY.clamp(20.0, size.height - 20);
+    final handlePos = Offset(clampedHandleX, clampedHandleY);
+
+    final isClamped = actualHandleY < 20.0;
+
+    final paint = Paint()
+      ..color = isDraggingInnerRadius
+          ? AppTheme.successColor
+          : (isClamped ? Colors.orange : Colors.purpleAccent)
+      ..style = PaintingStyle.fill;
+
+    // Draw handle
+    canvas.drawCircle(handlePos, 14, paint);
+
+    // Up/Down arrow indicators
+    final arrowPaint = Paint()
+      ..color = Colors.white
+      ..strokeWidth = 2
+      ..style = PaintingStyle.stroke;
+
+    // Up arrow
+    canvas.drawLine(
+      Offset(handlePos.dx, handlePos.dy - 4),
+      Offset(handlePos.dx - 4, handlePos.dy - 8),
+      arrowPaint,
+    );
+    canvas.drawLine(
+      Offset(handlePos.dx, handlePos.dy - 4),
+      Offset(handlePos.dx + 4, handlePos.dy - 8),
+      arrowPaint,
+    );
+
+    // Down arrow
+    canvas.drawLine(
+      Offset(handlePos.dx, handlePos.dy + 4),
+      Offset(handlePos.dx - 4, handlePos.dy + 8),
+      arrowPaint,
+    );
+    canvas.drawLine(
+      Offset(handlePos.dx, handlePos.dy + 4),
+      Offset(handlePos.dx + 4, handlePos.dy + 8),
+      arrowPaint,
+    );
+
+    // Label
+    final textPainter = TextPainter(
+      text: const TextSpan(
+        text: 'INT.',
+        style: TextStyle(
+          color: Colors.white,
+          fontSize: 8,
+          fontWeight: FontWeight.bold,
+        ),
+      ),
+      textDirection: TextDirection.ltr,
+    );
+    textPainter.layout();
+    textPainter.paint(
+      canvas,
+      Offset(handlePos.dx - textPainter.width / 2, handlePos.dy - 24),
+    );
+  }
+
   void _drawInstructions(Canvas canvas, Size size) {
     const instruction = 'Deplacez le centre ou ajustez le rayon';
 
@@ -418,9 +634,11 @@ class _CalibrationPainter extends CustomPainter {
     return centerX != oldDelegate.centerX ||
         centerY != oldDelegate.centerY ||
         radius != oldDelegate.radius ||
+        innerRadius != oldDelegate.innerRadius ||
         ringCount != oldDelegate.ringCount ||
         isDraggingCenter != oldDelegate.isDraggingCenter ||
         isDraggingRadius != oldDelegate.isDraggingRadius ||
+        isDraggingInnerRadius != oldDelegate.isDraggingInnerRadius ||
         ringRadii != oldDelegate.ringRadii;
   }
 }

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/main.dart

@@ -10,6 +10,7 @@ import 'services/target_detection_service.dart';
 import 'services/score_calculator_service.dart';
 import 'services/grouping_analyzer_service.dart';
 import 'services/image_processing_service.dart';
+import 'services/yolo_impact_detection_service.dart';
 
 void main() async {
   WidgetsFlutterBinding.ensureInitialized();
@@ -33,9 +34,13 @@ void main() async {
         Provider<ImageProcessingService>(
           create: (_) => ImageProcessingService(),
         ),
+        Provider<YOLOImpactDetectionService>(
+          create: (_) => YOLOImpactDetectionService(),
+        ),
         Provider<TargetDetectionService>(
           create: (context) => TargetDetectionService(
             imageProcessingService: context.read<ImageProcessingService>(),
+            yoloService: context.read<YOLOImpactDetectionService>(),
           ),
         ),
         Provider<ScoreCalculatorService>(
@@ -44,9 +49,7 @@ void main() async {
         Provider<GroupingAnalyzerService>(
           create: (_) => GroupingAnalyzerService(),
         ),
-        Provider<SessionRepository>(
+        Provider<SessionRepository>(create: (_) => SessionRepository()),
-          create: (_) => SessionRepository(),
-        ),
       ],
       child: const BullyApp(),
     ),

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);
@@ -408,8 +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<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.
     final List<double> b = List.generate(n, (i) => -matrix[i][8]);
@@ -428,7 +475,7 @@ class DistortionCorrectionService {
       final List<double> 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<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 +522,553 @@ 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;
+  }
+
+  /// Corrige la perspective en reformant le plus grand ovale (ellipse) en un cercle parfait,
+  /// sans recadrer agressivement l'image entière.
+  Future<String> correctPerspectiveUsingOvals(String imagePath) async {
+    try {
+      final src = cv.imread(imagePath, flags: cv.IMREAD_COLOR);
+      if (src.isEmpty) throw Exception("Impossible de charger l'image");
+
+      final gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY);
+      final blurred = cv.gaussianBlur(gray, (5, 5), 0);
+
+      final thresh = cv.threshold(
+        blurred,
+        0,
+        255,
+        cv.THRESH_BINARY | cv.THRESH_OTSU,
+      );
+      final edges = cv.canny(blurred, thresh.$1 * 0.5, thresh.$1);
+
+      final contoursResult = cv.findContours(
+        edges,
+        cv.RETR_EXTERNAL,
+        cv.CHAIN_APPROX_SIMPLE,
+      );
+      final contours = contoursResult.$1;
+
+      if (contours.isEmpty) return imagePath;
+
+      cv.RotatedRect? bestEllipse;
+      double maxArea = 0;
+
+      for (final contour in contours) {
+        if (contour.length < 5) continue;
+        final area = cv.contourArea(contour);
+        if (area < 1000) continue;
+
+        final ellipse = cv.fitEllipse(contour);
+        if (area > maxArea) {
+          maxArea = area;
+          bestEllipse = ellipse;
+        }
+      }
+
+      if (bestEllipse == null) return imagePath;
+
+      // The goal here is to morph the bestEllipse into a perfect circle, while
+      // keeping the image the same size and the center of the ellipse in the same place.
+      // We'll use the average of the width and height (or max) to define the target circle
+      final targetRadius =
+          math.max(bestEllipse.size.width, bestEllipse.size.height) / 2.0;
+
+      // Extract the 4 bounding box points of the ellipse
+      final boxPoints = cv.boxPoints(bestEllipse);
+      final List<cv.Point> srcPoints = [];
+      for (int i = 0; i < boxPoints.length; i++) {
+        srcPoints.add(cv.Point(boxPoints[i].x.toInt(), boxPoints[i].y.toInt()));
+      }
+      _sortPoints(srcPoints);
+
+      // Calculate the size of the perfectly squared output image
+      final int side = (targetRadius * 2).toInt();
+
+      final List<cv.Point> dstPoints = [
+        cv.Point(0, 0), // Top-Left
+        cv.Point(side, 0), // Top-Right
+        cv.Point(side, side), // Bottom-Right
+        cv.Point(0, side), // Bottom-Left
+      ];
+
+      // Morph the target region into a perfect square, cropping the rest of the image
+      final M = cv.getPerspectiveTransform(
+        cv.VecPoint.fromList(srcPoints),
+        cv.VecPoint.fromList(dstPoints),
+      );
+
+      final corrected = cv.warpPerspective(src, M, (side, side));
+
+      final tempDir = await getTemporaryDirectory();
+      final timestamp = DateTime.now().millisecondsSinceEpoch;
+      final outputPath = '${tempDir.path}/corrected_oval_$timestamp.jpg';
+
+      cv.imwrite(outputPath, corrected);
+
+      return outputPath;
+    } catch (e) {
+      print('Erreur correction perspective ovales: $e');
+      return imagePath;
+    }
+  }
+
+  /// Corrige la distorsion et la profondeur (perspective) en créant un maillage
+  /// basé sur la concentricité des différents cercles de la cible pour trouver le meilleur plan.
+  Future<String> correctPerspectiveWithConcentricMesh(String imagePath) async {
+    try {
+      final src = cv.imread(imagePath, flags: cv.IMREAD_COLOR);
+      if (src.isEmpty) throw Exception("Impossible de charger l'image");
+
+      final gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY);
+      final blurred = cv.gaussianBlur(gray, (5, 5), 0);
+      final thresh = cv.threshold(
+        blurred,
+        0,
+        255,
+        cv.THRESH_BINARY | cv.THRESH_OTSU,
+      );
+      final edges = cv.canny(blurred, thresh.$1 * 0.5, thresh.$1);
+
+      final contoursResult = cv.findContours(
+        edges,
+        cv.RETR_LIST,
+        cv.CHAIN_APPROX_SIMPLE,
+      );
+      final contours = contoursResult.$1;
+      if (contours.isEmpty) return imagePath;
+
+      List<cv.RotatedRect> ellipses = [];
+      for (final contour in contours) {
+        if (contour.length < 5) continue;
+        if (cv.contourArea(contour) < 500) continue;
+        ellipses.add(cv.fitEllipse(contour));
+      }
+
+      if (ellipses.isEmpty) return imagePath;
+
+      // Find the largest ellipse to serve as our central reference
+      ellipses.sort(
+        (a, b) => (b.size.width * b.size.height).compareTo(
+          a.size.width * a.size.height,
+        ),
+      );
+      final largestEllipse = ellipses.first;
+      final maxDist =
+          math.max(largestEllipse.size.width, largestEllipse.size.height) *
+          0.15;
+
+      // Group all ellipses that are roughly concentric with the largest one
+      List<cv.RotatedRect> concentricGroup = [];
+      for (final e in ellipses) {
+        final dx = e.center.x - largestEllipse.center.x;
+        final dy = e.center.y - largestEllipse.center.y;
+        if (math.sqrt(dx * dx + dy * dy) < maxDist) {
+          concentricGroup.add(e);
+        }
+      }
+
+      if (concentricGroup.length < 2) {
+        print(
+          "Pas assez de cercles concentriques pour le maillage, utilisation de la méthode simple.",
+        );
+        return await correctPerspectiveUsingOvals(imagePath);
+      }
+
+      final targetRadius =
+          math.max(largestEllipse.size.width, largestEllipse.size.height) / 2.0;
+      final int side = (targetRadius * 2.4).toInt(); // Add padding
+      final double cx = side / 2.0;
+      final double cy = side / 2.0;
+
+      List<cv.Point2f> srcPointsList = [];
+      List<cv.Point2f> dstPointsList = [];
+
+      for (final ellipse in concentricGroup) {
+        final box = cv.boxPoints(ellipse);
+        final m0 = cv.Point2f(
+          (box[0].x + box[1].x) / 2,
+          (box[0].y + box[1].y) / 2,
+        );
+        final m1 = cv.Point2f(
+          (box[1].x + box[2].x) / 2,
+          (box[1].y + box[2].y) / 2,
+        );
+        final m2 = cv.Point2f(
+          (box[2].x + box[3].x) / 2,
+          (box[2].y + box[3].y) / 2,
+        );
+        final m3 = cv.Point2f(
+          (box[3].x + box[0].x) / 2,
+          (box[3].y + box[0].y) / 2,
+        );
+
+        final d02 = math.sqrt(
+          math.pow(m0.x - m2.x, 2) + math.pow(m0.y - m2.y, 2),
+        );
+        final d13 = math.sqrt(
+          math.pow(m1.x - m3.x, 2) + math.pow(m1.y - m3.y, 2),
+        );
+
+        cv.Point2f maj1, maj2, min1, min2;
+        double r;
+
+        if (d02 > d13) {
+          maj1 = m0;
+          maj2 = m2;
+          min1 = m1;
+          min2 = m3;
+          r = d02 / 2.0;
+        } else {
+          maj1 = m1;
+          maj2 = m3;
+          min1 = m0;
+          min2 = m2;
+          r = d13 / 2.0;
+        }
+
+        // Sort maj1 and maj2 so maj1 is left/top
+        if ((maj1.x - maj2.x).abs() > (maj1.y - maj2.y).abs()) {
+          if (maj1.x > maj2.x) {
+            final t = maj1;
+            maj1 = maj2;
+            maj2 = t;
+          }
+        } else {
+          if (maj1.y > maj2.y) {
+            final t = maj1;
+            maj1 = maj2;
+            maj2 = t;
+          }
+        }
+
+        // Sort min1 and min2 so min1 is top/left
+        if ((min1.y - min2.y).abs() > (min1.x - min2.x).abs()) {
+          if (min1.y > min2.y) {
+            final t = min1;
+            min1 = min2;
+            min2 = t;
+          }
+        } else {
+          if (min1.x > min2.x) {
+            final t = min1;
+            min1 = min2;
+            min2 = t;
+          }
+        }
+
+        srcPointsList.addAll([maj1, maj2, min1, min2]);
+        dstPointsList.addAll([
+          cv.Point2f(cx - r, cy),
+          cv.Point2f(cx + r, cy),
+          cv.Point2f(cx, cy - r),
+          cv.Point2f(cx, cy + r),
+        ]);
+
+        // Add ellipse centers mapping perfectly to the origin to force concentric depth alignment
+        srcPointsList.add(cv.Point2f(ellipse.center.x, ellipse.center.y));
+        dstPointsList.add(cv.Point2f(cx, cy));
+      }
+
+      // We explicitly convert points to VecPoint to use findHomography standard binding
+      final srcVec = cv.VecPoint.fromList(
+        srcPointsList.map((p) => cv.Point(p.x.toInt(), p.y.toInt())).toList(),
+      );
+      final dstVec = cv.VecPoint.fromList(
+        dstPointsList.map((p) => cv.Point(p.x.toInt(), p.y.toInt())).toList(),
+      );
+
+      final M = cv.findHomography(
+        cv.Mat.fromVec(srcVec),
+        cv.Mat.fromVec(dstVec),
+        method: cv.RANSAC,
+      );
+
+      if (M.isEmpty) {
+        return await correctPerspectiveUsingOvals(imagePath);
+      }
+
+      final corrected = cv.warpPerspective(src, M, (side, side));
+
+      final tempDir = await getTemporaryDirectory();
+      final timestamp = DateTime.now().millisecondsSinceEpoch;
+      final outputPath = '${tempDir.path}/corrected_mesh_$timestamp.jpg';
+      cv.imwrite(outputPath, corrected);
+
+      return outputPath;
+    } catch (e) {
+      print('Erreur correction perspective maillage concentrique: $e');
+      return imagePath;
+    }
+  }
+
+  /// Corrige la perspective en détectant les 4 coins de la feuille (quadrilatère)
+  ///
+  /// Cette méthode cherche le plus grand polygone à 4 côtés (le bord du papier)
+  /// et le déforme pour en faire un carré parfait.
+  Future<String> correctPerspectiveUsingQuadrilateral(String imagePath) async {
+    try {
+      final src = cv.imread(imagePath, flags: cv.IMREAD_COLOR);
+      if (src.isEmpty) throw Exception("Impossible de charger l'image");
+
+      final gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY);
+      // Flou plus important pour ignorer les détails internes (cercles, trous)
+      final blurred = cv.gaussianBlur(gray, (9, 9), 0);
+
+      // Canny edge detector
+      final thresh = cv.threshold(
+        blurred,
+        0,
+        255,
+        cv.THRESH_BINARY | cv.THRESH_OTSU,
+      );
+      final edges = cv.canny(blurred, thresh.$1 * 0.5, thresh.$1);
+
+      // Pour la détection de la feuille (les bords peuvent être discontinus à cause de l'éclairage)
+      final kernel = cv.getStructuringElement(cv.MORPH_RECT, (5, 5));
+      final closedEdges = cv.morphologyEx(edges, cv.MORPH_CLOSE, kernel);
+
+      // Find contours
+      final contoursResult = cv.findContours(
+        closedEdges,
+        cv.RETR_EXTERNAL,
+        cv.CHAIN_APPROX_SIMPLE,
+      );
+      final contours = contoursResult.$1;
+
+      cv.VecPoint? bestQuad;
+      double maxArea = 0;
+
+      final minArea = src.rows * src.cols * 0.1; // Au moins 10% de l'image
+
+      for (final contour in contours) {
+        final area = cv.contourArea(contour);
+        if (area < minArea) continue;
+
+        final peri = cv.arcLength(contour, true);
+        // Approximation polygonale (tolérance = 2% à 5% du périmètre)
+        final approx = cv.approxPolyDP(contour, 0.04 * peri, true);
+
+        if (approx.length == 4) {
+          if (area > maxArea) {
+            maxArea = area;
+            bestQuad = approx;
+          }
+        }
+      }
+
+      // Fallback
+      if (bestQuad == null) {
+        print(
+          "Aucun papier quadrilatère détecté, on utilise les cercles à la place.",
+        );
+        return await correctPerspectiveUsingCircles(imagePath);
+      }
+
+      // Convert to List<cv.Point>
+      final List<cv.Point> srcPoints = [];
+      for (int i = 0; i < bestQuad.length; i++) {
+        srcPoints.add(bestQuad[i]);
+      }
+
+      _sortPoints(srcPoints);
+
+      // Calculate max width and height
+      double widthA = _distanceCV(srcPoints[2], srcPoints[3]);
+      double widthB = _distanceCV(srcPoints[1], srcPoints[0]);
+      int dstWidth = math.max(widthA, widthB).toInt();
+
+      double heightA = _distanceCV(srcPoints[1], srcPoints[2]);
+      double heightB = _distanceCV(srcPoints[0], srcPoints[3]);
+      int dstHeight = math.max(heightA, heightB).toInt();
+
+      // Since standard target paper forms a square, we force the resulting warp to be a perfect square.
+      int side = math.max(dstWidth, dstHeight);
+
+      final List<cv.Point> dstPoints = [
+        cv.Point(0, 0),
+        cv.Point(side, 0),
+        cv.Point(side, side),
+        cv.Point(0, side),
+      ];
+
+      final M = cv.getPerspectiveTransform(
+        cv.VecPoint.fromList(srcPoints),
+        cv.VecPoint.fromList(dstPoints),
+      );
+
+      final corrected = cv.warpPerspective(src, M, (side, side));
+
+      final tempDir = await getTemporaryDirectory();
+      final timestamp = DateTime.now().millisecondsSinceEpoch;
+      final outputPath = '${tempDir.path}/corrected_quad_$timestamp.jpg';
+
+      cv.imwrite(outputPath, corrected);
+
+      return outputPath;
+    } catch (e) {
+      print('Erreur correction perspective quadrilatère: $e');
+      // Fallback
+      return await correctPerspectiveUsingCircles(imagePath);
+    }
+  }
+
+  double _distanceCV(cv.Point p1, cv.Point p2) {
+    final dx = p2.x - p1.x;
+    final dy = p2.y - p1.y;
+    return math.sqrt(dx * dx + dy * dy);
+  }
 }

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 $2
+
+        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 +1,240 @@
+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
+        (img.rows / 16)
+            .toDouble(), // minDist decreased to allow more rings in same general area
+        param1: 100, // Canny edge detection
+        param2:
+            60, // Accumulator threshold (higher = fewer false circles, more accurate)
+        minRadius: img.cols ~/ 20,
+        maxRadius: img.cols ~/ 2,
+      );
+
+      // 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: 100,
+          param2: 40,
+          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) {
+        // Calculate the actual center of the cluster based on the smallest circle (the likely bullseye)
+        double clusterCenterX = cluster.first.x;
+        double clusterCenterY = cluster.first.y;
+        double minRadiusInCluster = cluster.first.r;
+
+        for (final c in cluster) {
+          if (c.r < minRadiusInCluster) {
+            minRadiusInCluster = c.r;
+            clusterCenterX = c.x;
+            clusterCenterY = c.y;
+          }
+        }
+
+        final dist = math.sqrt(
+          math.pow(circle.x - clusterCenterX, 2) +
+              math.pow(circle.y - clusterCenterY, 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 squared (heavily favor concentric rings)
+      double score = math.pow(cluster.length, 2).toDouble() * 10.0;
+
+      // Small penalty for distance from center (only as tie-breaker)
+      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 * 2.0; // Very minor penalty so we don't snap to screen 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,
+    );
+  }
+}

lib/services/target_detection_service.dart

@@ -2,9 +2,12 @@ import 'dart:math' as math;
 import '../data/models/target_type.dart';
 import 'image_processing_service.dart';
 import 'opencv_impact_detection_service.dart';
+import 'yolo_impact_detection_service.dart';
 
-export 'image_processing_service.dart' show ImpactDetectionSettings, ReferenceImpact, ImpactCharacteristics;
+export 'image_processing_service.dart'
-export 'opencv_impact_detection_service.dart' show OpenCVDetectionSettings, OpenCVDetectedImpact;
+    show ImpactDetectionSettings, ReferenceImpact, ImpactCharacteristics;
+export 'opencv_impact_detection_service.dart'
+    show OpenCVDetectionSettings, OpenCVDetectedImpact;
 
 class TargetDetectionResult {
   final double centerX; // Relative (0-1)
@@ -52,18 +55,19 @@ class DetectedImpactResult {
 class TargetDetectionService {
   final ImageProcessingService _imageProcessingService;
   final OpenCVImpactDetectionService _opencvService;
+  final YOLOImpactDetectionService _yoloService;
 
   TargetDetectionService({
     ImageProcessingService? imageProcessingService,
     OpenCVImpactDetectionService? opencvService,
-  })  : _imageProcessingService = imageProcessingService ?? ImageProcessingService(),
+    YOLOImpactDetectionService? yoloService,
-        _opencvService = opencvService ?? OpenCVImpactDetectionService();
+  }) : _imageProcessingService =
+           imageProcessingService ?? ImageProcessingService(),
+       _opencvService = opencvService ?? OpenCVImpactDetectionService(),
+       _yoloService = yoloService ?? YOLOImpactDetectionService();
 
   /// Detect target and impacts from an image file
-  TargetDetectionResult detectTarget(
+  TargetDetectionResult detectTarget(String imagePath, TargetType targetType) {
-    String imagePath,
-    TargetType targetType,
-  ) {
     try {
       // Detect main target
       final mainTarget = _imageProcessingService.detectMainTarget(imagePath);
@@ -84,7 +88,13 @@ class TargetDetectionService {
       // Convert impacts to relative coordinates and calculate scores
       final detectedImpacts = impacts.map((impact) {
         final score = targetType == TargetType.concentric
-            ? _calculateConcentricScore(impact.x, impact.y, centerX, centerY, radius)
+            ? _calculateConcentricScore(
+                impact.x,
+                impact.y,
+                centerX,
+                centerY,
+                radius,
+              )
             : _calculateSilhouetteScore(impact.x, impact.y, centerX, centerY);
 
         return DetectedImpactResult(
@@ -149,9 +159,9 @@ class TargetDetectionService {
 
     // Vertical zones
     if (dy < -0.25) return 5; // Head zone (top)
-    if (dy < 0.0) return 5;   // Center mass (upper body)
+    if (dy < 0.0) return 5; // Center mass (upper body)
-    if (dy < 0.15) return 4;  // Body
+    if (dy < 0.15) return 4; // Body
-    if (dy < 0.35) return 3;  // Lower body
+    if (dy < 0.35) return 3; // Lower body
 
     return 0; // Outside target
   }
@@ -177,7 +187,13 @@ class TargetDetectionService {
       return impacts.map((impact) {
         final score = targetType == TargetType.concentric
             ? _calculateConcentricScoreWithRings(
-                impact.x, impact.y, centerX, centerY, radius, ringCount)
+                impact.x,
+                impact.y,
+                centerX,
+                centerY,
+                radius,
+                ringCount,
+              )
             : _calculateSilhouetteScore(impact.x, impact.y, centerX, centerY);
 
         return DetectedImpactResult(
@@ -221,7 +237,10 @@ class TargetDetectionService {
     String imagePath,
     List<ReferenceImpact> references,
   ) {
-    return _imageProcessingService.analyzeReferenceImpacts(imagePath, references);
+    return _imageProcessingService.analyzeReferenceImpacts(
+      imagePath,
+      references,
+    );
   }
 
   /// Detect impacts based on reference characteristics (calibrated detection)
@@ -245,7 +264,13 @@ class TargetDetectionService {
       return impacts.map((impact) {
         final score = targetType == TargetType.concentric
             ? _calculateConcentricScoreWithRings(
-                impact.x, impact.y, centerX, centerY, radius, ringCount)
+                impact.x,
+                impact.y,
+                centerX,
+                centerY,
+                radius,
+                ringCount,
+              )
             : _calculateSilhouetteScore(impact.x, impact.y, centerX, centerY);
 
         return DetectedImpactResult(
@@ -283,7 +308,13 @@ class TargetDetectionService {
       return impacts.map((impact) {
         final score = targetType == TargetType.concentric
             ? _calculateConcentricScoreWithRings(
-                impact.x, impact.y, centerX, centerY, radius, ringCount)
+                impact.x,
+                impact.y,
+                centerX,
+                centerY,
+                radius,
+                ringCount,
+              )
             : _calculateSilhouetteScore(impact.x, impact.y, centerX, centerY);
 
         return DetectedImpactResult(
@@ -315,9 +346,7 @@ class TargetDetectionService {
   }) {
     try {
       // Convertir les références au format OpenCV
-      final refPoints = references
+      final refPoints = references.map((r) => (x: r.x, y: r.y)).toList();
-          .map((r) => (x: r.x, y: r.y))
-          .toList();
 
       final impacts = _opencvService.detectFromReferences(
         imagePath,
@@ -328,7 +357,13 @@ class TargetDetectionService {
       return impacts.map((impact) {
         final score = targetType == TargetType.concentric
             ? _calculateConcentricScoreWithRings(
-                impact.x, impact.y, centerX, centerY, radius, ringCount)
+                impact.x,
+                impact.y,
+                centerX,
+                centerY,
+                radius,
+                ringCount,
+              )
             : _calculateSilhouetteScore(impact.x, impact.y, centerX, centerY);
 
         return DetectedImpactResult(
@@ -343,4 +378,41 @@ class TargetDetectionService {
       return [];
     }
   }
+
+  /// Détecte les impacts en utilisant YOLOv8
+  Future<List<DetectedImpactResult>> detectImpactsWithYOLO(
+    String imagePath,
+    TargetType targetType,
+    double centerX,
+    double centerY,
+    double radius,
+    int ringCount,
+  ) async {
+    try {
+      final impacts = await _yoloService.detectImpacts(imagePath);
+
+      return impacts.map((impact) {
+        final score = targetType == TargetType.concentric
+            ? _calculateConcentricScoreWithRings(
+                impact.x,
+                impact.y,
+                centerX,
+                centerY,
+                radius,
+                ringCount,
+              )
+            : _calculateSilhouetteScore(impact.x, impact.y, centerX, centerY);
+
+        return DetectedImpactResult(
+          x: impact.x,
+          y: impact.y,
+          radius: impact.radius,
+          suggestedScore: score,
+        );
+      }).toList();
+    } catch (e) {
+      print('Erreur détection YOLOv8: $e');
+      return [];
+    }
+  }
 }

lib/services/yolo_impact_detection_service.dart

@@ -0,0 +1,174 @@
+import 'dart:io';
+import 'dart:math' as math;
+import 'dart:typed_data';
+import 'package:tflite_flutter/tflite_flutter.dart';
+import 'package:image/image.dart' as img;
+import 'target_detection_service.dart';
+
+class YOLOImpactDetectionService {
+  Interpreter? _interpreter;
+
+  static const String modelPath = 'assets/models/yolov11n_impact.tflite';
+  static const String labelsPath = 'assets/models/labels.txt';
+
+  Future<void> init() async {
+    if (_interpreter != null) return;
+
+    try {
+      // Try loading the specific YOLOv11 model first, fallback to v8 if not found
+      try {
+        _interpreter = await Interpreter.fromAsset(modelPath);
+      } catch (e) {
+        print('YOLOv11 model not found at $modelPath, trying YOLOv8 fallback');
+        _interpreter = await Interpreter.fromAsset(
+          'assets/models/yolov8n_impact.tflite',
+        );
+      }
+
+      print('YOLO Interpreter loaded successfully');
+    } catch (e) {
+      print('Error loading YOLO model: $e');
+    }
+  }
+
+  Future<List<DetectedImpactResult>> detectImpacts(String imagePath) async {
+    if (_interpreter == null) await init();
+    if (_interpreter == null) return [];
+
+    try {
+      final bytes = File(imagePath).readAsBytesSync();
+      final originalImage = img.decodeImage(bytes);
+      if (originalImage == null) return [];
+
+      // YOLOv8/v11 usually takes 640x640
+      const int inputSize = 640;
+      final resizedImage = img.copyResize(
+        originalImage,
+        width: inputSize,
+        height: inputSize,
+      );
+
+      // Prepare input tensor
+      var input = _imageToByteListFloat32(resizedImage, inputSize);
+
+      // Raw YOLO output shape usually [1, 4 + num_classes, 8400]
+      // For single class "impact", it's [1, 5, 8400]
+      var output = List<double>.filled(1 * 5 * 8400, 0).reshape([1, 5, 8400]);
+
+      _interpreter!.run(input, output);
+
+      return _processOutput(
+        output[0],
+        originalImage.width,
+        originalImage.height,
+      );
+    } catch (e) {
+      print('Error during YOLO inference: $e');
+      return [];
+    }
+  }
+
+  List<DetectedImpactResult> _processOutput(
+    List<List<double>> output,
+    int imgWidth,
+    int imgHeight,
+  ) {
+    final List<_Detection> candidates = [];
+    const double threshold = 0.25;
+
+    // output is [5, 8400] -> [x, y, w, h, conf]
+    for (int i = 0; i < 8400; i++) {
+      final double confidence = output[4][i];
+      if (confidence > threshold) {
+        candidates.add(
+          _Detection(
+            x: output[0][i],
+            y: output[1][i],
+            w: output[2][i],
+            h: output[3][i],
+            confidence: confidence,
+          ),
+        );
+      }
+    }
+
+    // Apply Non-Max Suppression (NMS)
+    final List<_Detection> suppressed = _nms(candidates);
+
+    return suppressed
+        .map(
+          (det) => DetectedImpactResult(
+            x: det.x / 640.0,
+            y: det.y / 640.0,
+            radius: 5.0,
+            suggestedScore: 0,
+          ),
+        )
+        .toList();
+  }
+
+  List<_Detection> _nms(List<_Detection> detections) {
+    if (detections.isEmpty) return [];
+
+    // Sort by confidence descending
+    detections.sort((a, b) => b.confidence.compareTo(a.confidence));
+
+    final List<_Detection> selected = [];
+    final List<bool> active = List.filled(detections.length, true);
+
+    for (int i = 0; i < detections.length; i++) {
+      if (!active[i]) continue;
+
+      selected.add(detections[i]);
+
+      for (int j = i + 1; j < detections.length; j++) {
+        if (!active[j]) continue;
+
+        if (_iou(detections[i], detections[j]) > 0.45) {
+          active[j] = false;
+        }
+      }
+    }
+
+    return selected;
+  }
+
+  double _iou(_Detection a, _Detection b) {
+    final double areaA = a.w * a.h;
+    final double areaB = b.w * b.h;
+
+    final double x1 = math.max(a.x - a.w / 2, b.x - b.w / 2);
+    final double y1 = math.max(a.y - a.h / 2, b.y - b.h / 2);
+    final double x2 = math.min(a.x + a.w / 2, b.x + b.w / 2);
+    final double y2 = math.min(a.y + a.h / 2, b.y + b.h / 2);
+
+    final double intersection = math.max(0.0, x2 - x1) * math.max(0.0, y2 - y1);
+    return intersection / (areaA + areaB - intersection);
+  }
+
+  Uint8List _imageToByteListFloat32(img.Image image, int inputSize) {
+    var convertedBytes = Float32List(1 * inputSize * inputSize * 3);
+    var buffer = Float32List.view(convertedBytes.buffer);
+    int pixelIndex = 0;
+    for (int i = 0; i < inputSize; i++) {
+      for (int j = 0; j < inputSize; j++) {
+        var pixel = image.getPixel(j, i);
+        buffer[pixelIndex++] = (pixel.r / 255.0);
+        buffer[pixelIndex++] = (pixel.g / 255.0);
+        buffer[pixelIndex++] = (pixel.b / 255.0);
+      }
+    }
+    return convertedBytes.buffer.asUint8List();
+  }
+}
+
+class _Detection {
+  final double x, y, w, h, confidence;
+  _Detection({
+    required this.x,
+    required this.y,
+    required this.w,
+    required this.h,
+    required this.confidence,
+  });
+}

linux/flutter/generated_plugins.cmake

@@ -7,6 +7,7 @@ list(APPEND FLUTTER_PLUGIN_LIST
 )
 
 list(APPEND FLUTTER_FFI_PLUGIN_LIST
+  tflite_flutter
 )
 
 set(PLUGIN_BUNDLED_LIBRARIES)

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:
@@ -496,6 +536,14 @@ packages:
       url: "https://pub.dev"
     source: hosted
     version: "2.2.0"
+  quiver:
+    dependency: transitive
+    description:
+      name: quiver
+      sha256: ea0b925899e64ecdfbf9c7becb60d5b50e706ade44a85b2363be2a22d88117d2
+      url: "https://pub.dev"
+    source: hosted
+    version: "3.2.2"
   sky_engine:
     dependency: transitive
     description: flutter
@@ -613,6 +661,14 @@ packages:
       url: "https://pub.dev"
     source: hosted
     version: "0.7.9"
+  tflite_flutter:
+    dependency: "direct main"
+    description:
+      name: tflite_flutter
+      sha256: ffb8651fdb116ab0131d6dc47ff73883e0f634ad1ab12bb2852eef1bbeab4a6a
+      url: "https://pub.dev"
+    source: hosted
+    version: "0.10.4"
   typed_data:
     dependency: transitive
     description:
@@ -679,4 +735,4 @@ 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
@@ -64,6 +64,9 @@ dependencies:
   # Image processing for impact detection
   image: ^4.1.7
 
+  # Machine Learning for YOLOv8
+  tflite_flutter: ^0.10.4
+
 dev_dependencies:
   flutter_test:
     sdk: flutter

tests/find_homography_test.dart

@@ -0,0 +1,12 @@
+import 'package:opencv_dart/opencv_dart.dart' as cv;
+
+void main() {
+  var p1 = cv.VecPoint.fromList([cv.Point(0, 0), cv.Point(1, 1)]);
+  var p2 = cv.VecPoint2f.fromList([cv.Point2f(0, 0), cv.Point2f(1, 1)]);
+
+  // Is it p1.mat ?
+  // Or is it cv.findHomography(p1, p1) but actually needs specific types ?
+  cv.Mat mat1 = cv.Mat.fromVec(p1);
+  cv.Mat mat2 = cv.Mat.fromVec(p2);
+  cv.findHomography(mat1, mat2);
+}

tests/opencv_quad_test.dart

@@ -0,0 +1,7 @@
+import 'package:opencv_dart/opencv_dart.dart' as cv;
+
+void main() {
+  print(cv.approxPolyDP);
+  print(cv.arcLength);
+  print(cv.contourArea);
+}

tests/test_homography.dart

@@ -0,0 +1,5 @@
+import 'package:opencv_dart/opencv_dart.dart' as cv;
+
+void main() {
+  print(cv.findHomography);
+}

windows/flutter/generated_plugins.cmake

@@ -7,6 +7,7 @@ list(APPEND FLUTTER_PLUGIN_LIST
 )
 
 list(APPEND FLUTTER_FFI_PLUGIN_LIST
+  tflite_flutter
 )
 
 set(PLUGIN_BUNDLED_LIBRARIES)