desactivation de tous les scripts et ia, supression du modele yolo

.vscode/settings.json

@@ -0,0 +1,4 @@
+{
+    "avdmanager.executable": "c:\\Users\\streaper2\\AppData\\Local\\Android\\Sdk\\cmdline-tools\\latest\\bin\\avdmanager.bat",
+    "avdmanager.sdkManager": "c:\\Users\\streaper2\\AppData\\Local\\Android\\Sdk\\cmdline-tools\\latest\\bin\\sdkmanager.bat"
+}

analyze_results_fixed.txt

@@ -0,0 +1,37 @@
+Analyzing bully...                                              
+
+   info - Don't invoke 'print' in production code - lib\features\analysis\analysis_provider.dart:553:7 - avoid_print
+   info - The private field _selectedType could be 'final' - lib\features\capture\capture_screen.dart:27:14 - prefer_final_fields
+   info - 'scale' is deprecated and shouldn't be used. Use scaleByVector3, scaleByVector4, or scaleByDouble instead - lib\features\crop\crop_screen.dart:142:25 - deprecated_member_use
+   info - Statements in an if should be enclosed in a block - lib\services\distortion_correction_service.dart:566:11 - curly_braces_in_flow_control_structures
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:639:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:764:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:825:9 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:953:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:1015:9 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:1063:7 - avoid_print
+   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\target_detection_service.dart:328:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\target_detection_service.dart:377:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\target_detection_service.dart:414:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\yolo_impact_detection_service.dart:23:9 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\yolo_impact_detection_service.dart:29:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\yolo_impact_detection_service.dart:31:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\yolo_impact_detection_service.dart:67:7 - avoid_print
+   info - Don't invoke 'print' in production code - tests\opencv_quad_test.dart:4:3 - avoid_print
+   info - Don't invoke 'print' in production code - tests\opencv_quad_test.dart:5:3 - avoid_print
+   info - Don't invoke 'print' in production code - tests\opencv_quad_test.dart:6:3 - avoid_print
+   info - Don't invoke 'print' in production code - tests\test_homography.dart:4:3 - avoid_print
+

analyze_utf8.txt

@@ -0,0 +1,38 @@
+Analyzing bully...                                              
+
+   info - Don't invoke 'print' in production code - lib\features\analysis\analysis_provider.dart:392:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\features\analysis\analysis_provider.dart:596:7 - avoid_print
+   info - The private field _selectedType could be 'final' - lib\features\capture\capture_screen.dart:27:14 - prefer_final_fields
+   info - 'scale' is deprecated and shouldn't be used. Use scaleByVector3, scaleByVector4, or scaleByDouble instead - lib\features\crop\crop_screen.dart:142:25 - deprecated_member_use
+   info - Statements in an if should be enclosed in a block - lib\services\distortion_correction_service.dart:566:11 - curly_braces_in_flow_control_structures
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:639:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:764:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:825:9 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:953:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:1015:9 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\distortion_correction_service.dart:1063:7 - avoid_print
+   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\target_detection_service.dart:328:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\target_detection_service.dart:377:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\target_detection_service.dart:414:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\yolo_impact_detection_service.dart:23:9 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\yolo_impact_detection_service.dart:29:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\yolo_impact_detection_service.dart:31:7 - avoid_print
+   info - Don't invoke 'print' in production code - lib\services\yolo_impact_detection_service.dart:67:7 - avoid_print
+   info - Don't invoke 'print' in production code - tests\opencv_quad_test.dart:4:3 - avoid_print
+   info - Don't invoke 'print' in production code - tests\opencv_quad_test.dart:5:3 - avoid_print
+   info - Don't invoke 'print' in production code - tests\opencv_quad_test.dart:6:3 - avoid_print
+   info - Don't invoke 'print' in production code - tests\test_homography.dart:4:3 - avoid_print
+

android/app/build.gradle.kts

@@ -35,6 +35,7 @@ android {
             // TODO: Add your own signing config for the release build.
             // Signing with the debug keys for now, so `flutter run --release` works.
             signingConfig = signingConfigs.getByName("debug")
+            proguardFiles(getDefaultProguardFile("proguard-android-optimize.txt"), "proguard-rules.pro")
         }
     }
 }

android/app/proguard-rules.pro

@@ -0,0 +1,7 @@
+# TensorFlow Lite
+-keep class org.tensorflow.lite.** { *; }
+-keep class com.google.android.gms.tflite.** { *; }
+-dontwarn org.tensorflow.lite.**
+
+# Specifically for the GPU delegate error
+-dontwarn org.tensorflow.lite.gpu.GpuDelegateFactory$Options

lib/features/analysis/analysis_provider.dart

@@ -223,6 +223,16 @@ class AnalysisProvider extends ChangeNotifier {
     notifyListeners();
   }
 
+  /// Update a shot's score manually
+  void updateShotScore(String shotId, int newScore) {
+    final index = _shots.indexWhere((shot) => shot.id == shotId);
+    if (index == -1) return;
+
+    _shots[index] = _shots[index].copyWith(score: newScore);
+    _recalculateScores();
+    notifyListeners();
+  }
+
   /// Auto-detect impacts using image processing
   Future<int> autoDetectImpacts({
     int darkThreshold = 80,
@@ -293,6 +303,8 @@ class AnalysisProvider extends ChangeNotifier {
     double param2 = 30,
     int minRadius = 5,
     int maxRadius = 50,
+    int minSize = 5,
+    int maxSize = 1000,
     int blurSize = 5,
     bool useContourDetection = true,
     double minCircularity = 0.6,
@@ -351,6 +363,47 @@ class AnalysisProvider extends ChangeNotifier {
     return detectedImpacts.length;
   }
 
+  /// Auto-detect impacts using YOLOv8 model
+  Future<int> autoDetectImpactsWithYOLO({bool clearExisting = false}) async {
+    if (_imagePath == null || _targetType == null) return 0;
+
+    try {
+      final detectedImpacts = await _detectionService.detectImpactsWithYOLO(
+        _imagePath!,
+        _targetType!,
+        _targetCenterX,
+        _targetCenterY,
+        _targetRadius,
+        _ringCount,
+      );
+
+      if (clearExisting) {
+        _shots.clear();
+      }
+
+      // Add detected impacts as shots
+      for (final impact in detectedImpacts) {
+        final shot = Shot(
+          id: _uuid.v4(),
+          x: impact.x,
+          y: impact.y,
+          score: impact.suggestedScore,
+          sessionId: '',
+        );
+        _shots.add(shot);
+      }
+
+      _recalculateScores();
+      _recalculateGrouping();
+      notifyListeners();
+
+      return detectedImpacts.length;
+    } catch (e) {
+      print('Error in YOLO auto-detection: $e');
+      return 0;
+    }
+  }
+
   /// Detect impacts with OpenCV using reference points
   Future<int> detectFromReferencesWithOpenCV({
     double tolerance = 2.0,

lib/features/analysis/analysis_screen.dart

@@ -274,68 +274,7 @@ 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: [
@@ -387,57 +326,6 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                           ),
                         ],
                       ),
-                      // Target size slider
-                      Row(
-                        children: [
-                          const Icon(
-                            Icons.zoom_out_map,
-                            color: Colors.white,
-                            size: 20,
-                          ),
-                          const SizedBox(width: 8),
-                          const Text(
-                            'Taille:',
-                            style: TextStyle(color: Colors.white),
-                          ),
-                          Expanded(
-                            child: Slider(
-                              value: provider.targetRadius.clamp(0.05, 3.0),
-                              min: 0.05,
-                              max: 3.0,
-                              label:
-                                  '${(provider.targetRadius * 100).toStringAsFixed(0)}%',
-                              activeColor: AppTheme.warningColor,
-                              onChanged: (value) {
-                                provider.adjustTargetPosition(
-                                  provider.targetCenterX,
-                                  provider.targetCenterY,
-                                  provider.targetInnerRadius,
-                                  value,
-                                  ringCount: provider.ringCount,
-                                );
-                              },
-                            ),
-                          ),
-                          Container(
-                            padding: const EdgeInsets.symmetric(
-                              horizontal: 12,
-                              vertical: 4,
-                            ),
-                            decoration: BoxDecoration(
-                              color: AppTheme.warningColor,
-                              borderRadius: BorderRadius.circular(12),
-                            ),
-                            child: Text(
-                              '${(provider.targetRadius * 100).toStringAsFixed(0)}%',
-                              style: const TextStyle(
-                                color: Colors.white,
-                                fontWeight: FontWeight.bold,
-                              ),
-                            ),
-                          ),
-                        ],
-                      ),
                       const Divider(color: Colors.white24, height: 16),
                       // Distortion correction row
                       /*Row(
@@ -793,6 +681,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                 ),
                 // Overlay qui se transforme avec l'image
                 TargetOverlay(
+                  showRings: true,
                   shots: provider.shots,
                   targetCenterX: provider.targetCenterX,
                   targetCenterY: provider.targetCenterY,
@@ -879,6 +768,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                   ),
                   // Overlay qui se transforme avec l'image
                   TargetOverlay(
+                    showRings: true,
                     shots: provider.shots,
                     targetCenterX: provider.targetCenterX,
                     targetCenterY: provider.targetCenterY,
@@ -991,107 +881,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
   }
 
   Widget _buildActionButtons(BuildContext context, AnalysisProvider provider) {
-    return Column(
+    return const SizedBox.shrink();
-      children: [
-        // Reference-based detection section
-        if (_isSelectingReferences) ...[
-          Card(
-            color: Colors.deepPurple.withValues(alpha: 0.1),
-            child: Padding(
-              padding: const EdgeInsets.all(12),
-              child: Column(
-                crossAxisAlignment: CrossAxisAlignment.start,
-                children: [
-                  Row(
-                    children: [
-                      const Icon(Icons.touch_app, color: Colors.deepPurple),
-                      const SizedBox(width: 8),
-                      Text(
-                        '${provider.referenceImpacts.length} reference(s) selectionnee(s)',
-                        style: const TextStyle(fontWeight: FontWeight.bold),
-                      ),
-                    ],
-                  ),
-                  const SizedBox(height: 8),
-                  const Text(
-                    'Touchez l\'image pour marquer 3-4 impacts de reference. '
-                    'L\'algorithme apprendra leurs caracteristiques pour detecter les autres.',
-                    style: TextStyle(fontSize: 12, color: Colors.grey),
-                  ),
-                  const SizedBox(height: 12),
-                  Row(
-                    children: [
-                      Expanded(
-                        child: OutlinedButton(
-                          onPressed: () {
-                            setState(() => _isSelectingReferences = false);
-                            provider.clearReferenceImpacts();
-                          },
-                          child: const Text('Annuler'),
-                        ),
-                      ),
-                      const SizedBox(width: 12),
-                      Expanded(
-                        child: ElevatedButton.icon(
-                          onPressed: provider.referenceImpacts.length >= 2
-                              ? () => _showCalibratedDetectionDialog(
-                                  context,
-                                  provider,
-                                )
-                              : null,
-                          icon: const Icon(Icons.auto_fix_high),
-                          label: const Text('Detecter'),
-                          style: ElevatedButton.styleFrom(
-                            backgroundColor: Colors.deepPurple,
-                            foregroundColor: Colors.white,
-                          ),
-                        ),
-                      ),
-                    ],
-                  ),
-                ],
-              ),
-            ),
-          ),
-          const SizedBox(height: 12),
-        ] else ...[
-          // désactiver le temps de l'amelioration du scripts d'auto-detection
-          // Auto-detect buttons row
-          // Row(
-          //   children: [
-          //     Expanded(
-          //       child: ElevatedButton.icon(
-          //         onPressed: () => _showAutoDetectDialog(context, provider),
-          //         icon: const Icon(Icons.auto_fix_high),
-          //         label: const Text('Auto-Detection'),
-          //         style: ElevatedButton.styleFrom(
-          //           backgroundColor: AppTheme.primaryColor,
-          //           foregroundColor: Colors.white,
-          //           padding: const EdgeInsets.symmetric(vertical: 12),
-          //         ),
-          //       ),
-          //     ),
-          //     const SizedBox(width: 12),
-          //     Expanded(
-          //       child: ElevatedButton.icon(
-          //         onPressed: () => setState(() => _isSelectingReferences = true),
-          //         icon: const Icon(Icons.touch_app),
-          //         label: const Text('Par Reference'),
-          //         style: ElevatedButton.styleFrom(
-          //           backgroundColor: Colors.deepPurple,
-          //           foregroundColor: Colors.white,
-          //           padding: const EdgeInsets.symmetric(vertical: 12),
-          //         ),
-          //       ),
-          //     ),
-          //   ],
-          // ),
-          const SizedBox(height: 12),
-        ],
-
-        // Manual actions
-      ],
-    );
   }
 
   void _showHelpDialog(BuildContext context) {
@@ -1129,21 +919,68 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
     AnalysisProvider provider,
     String shotId,
   ) {
+    final shot = provider.shots.firstWhere((s) => s.id == shotId);
+    
     showModalBottomSheet(
       context: context,
+      shape: const RoundedRectangleBorder(
+        borderRadius: BorderRadius.vertical(top: Radius.circular(20)),
+      ),
       builder: (context) => SafeArea(
-        child: Wrap(
+        child: Padding(
+          padding: const EdgeInsets.all(20.0),
+          child: Column(
+            mainAxisSize: MainAxisSize.min,
             children: [
-            ListTile(
+              Text(
-              leading: const Icon(Icons.delete, color: AppTheme.errorColor),
+                'Modifier l\'impact',
-              title: const Text('Supprimer cet impact'),
+                style: Theme.of(context).textTheme.titleLarge,
-              onTap: () {
+              ),
-                provider.removeShot(shotId);
+              const SizedBox(height: 20),
+              // Dropdown for score
+              Row(
+                mainAxisAlignment: MainAxisAlignment.center,
+                children: [
+                  const Text('Valeur de l\'impact : ', style: TextStyle(fontSize: 16)),
+                  const SizedBox(width: 10),
+                  DropdownButton<int>(
+                    value: shot.score.clamp(0, 10),
+                    items: List.generate(11, (i) => i).map((i) {
+                      return DropdownMenuItem<int>(
+                        value: i,
+                        child: Text(i == 10 && provider.targetType == TargetType.concentric ? '10 (X)' : '$i'),
+                      );
+                    }).toList(),
+                    onChanged: (newScore) {
+                      if (newScore != null) {
+                        provider.updateShotScore(shotId, newScore);
                         Navigator.pop(context);
+                      }
                     },
                   ),
                 ],
               ),
+              const SizedBox(height: 20),
+              // Delete button at the bottom
+              SizedBox(
+                width: double.infinity,
+                child: ElevatedButton.icon(
+                  onPressed: () {
+                    provider.removeShot(shotId);
+                    Navigator.pop(context);
+                  },
+                  icon: const Icon(Icons.delete),
+                  label: const Text('SUPPRIMER L\'IMPACT'),
+                  style: ElevatedButton.styleFrom(
+                    backgroundColor: AppTheme.errorColor,
+                    foregroundColor: Colors.white,
+                    padding: const EdgeInsets.symmetric(vertical: 12),
+                  ),
+                ),
+              ),
+            ],
+          ),
+        ),
       ),
     );
   }
@@ -1187,7 +1024,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
     );
   }
 
-  /*
+
   void _showAutoDetectDialog(BuildContext context, AnalysisProvider provider) {
     // Detection settings
     bool clearExisting = true;
@@ -1197,9 +1034,6 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
     int maxImpactSize = 500;
     double minFillRatio = 0.5;
 
-    // NOTE: OpenCV désactivé - problèmes de build Windows
-    // Utilisation de la détection classique uniquement
-
     showDialog(
       context: context,
       builder: (context) => StatefulBuilder(
@@ -1216,11 +1050,78 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
               mainAxisSize: MainAxisSize.min,
               crossAxisAlignment: CrossAxisAlignment.start,
               children: [
+                // YOLO option button
+                Card(
+                  color: AppTheme.primaryColor.withAlpha(25),
+                  child: ListTile(
+                    leading: const Icon(Icons.psychology, color: AppTheme.primaryColor),
+                    title: const Text('IA Detection (YOLOv8)', style: TextStyle(fontWeight: FontWeight.bold)),
+                    subtitle: const Text('Détection intelligente via modèle entraîné'),
+                    onTap: () async {
+                      Navigator.pop(context);
+                      
+                      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('Détection IA en cours...'),
+                            ],
+                          ),
+                          duration: Duration(seconds: 10),
+                        ),
+                      );
+
+                      final count = await provider.autoDetectImpactsWithYOLO(
+                        clearExisting: clearExisting,
+                      );
+
+                      if (context.mounted) {
+                        ScaffoldMessenger.of(context).hideCurrentSnackBar();
+                        ScaffoldMessenger.of(context).showSnackBar(
+                          SnackBar(
+                            content: Text(
+                              count > 0
+                                  ? '$count impact(s) détecté(s) par l\'IA'
+                                  : 'Aucun impact détecté par l\'IA.',
+                            ),
+                            backgroundColor: count > 0
+                                ? AppTheme.successColor
+                                : AppTheme.warningColor,
+                          ),
+                        );
+                      }
+                    },
+                  ),
+                ),
+                
+                const Padding(
+                  padding: EdgeInsets.symmetric(vertical: 12),
+                  child: Row(
+                    children: [
+                      Expanded(child: Divider()),
+                      Padding(
+                        padding: EdgeInsets.symmetric(horizontal: 8),
+                        child: Text('OU', style: TextStyle(color: Colors.grey, fontSize: 12)),
+                      ),
+                      Expanded(child: Divider()),
+                    ],
+                  ),
+                ),
+
                 const Text(
-                  'Ajustez les parametres de detection:',
+                  'Détection Classique (Paramétrable):',
                   style: TextStyle(fontWeight: FontWeight.bold),
                 ),
-                const SizedBox(height: 16),
+                const SizedBox(height: 8),
 
                 // Dark threshold slider
                 Text('Seuil de detection (zones sombres): $darkThreshold'),
@@ -1379,14 +1280,13 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
                 }
               },
               icon: const Icon(Icons.search),
-              label: const Text('Detecter'),
+              label: const Text('Détecter (Classique)'),
             ),
           ],
         ),
       ),
     );
   }
-  */
 
   void _showCalibratedDetectionDialog(
     BuildContext context,

lib/features/analysis/widgets/target_overlay.dart

@@ -25,6 +25,7 @@ class TargetOverlay extends StatelessWidget {
   final double? groupingDiameter;
   final List<Shot>? referenceImpacts;
   final double zoomScale;
+  final bool showRings;
 
   const TargetOverlay({
     super.key,
@@ -42,6 +43,7 @@ class TargetOverlay extends StatelessWidget {
     this.groupingDiameter,
     this.referenceImpacts,
     this.zoomScale = 1.0,
+    this.showRings = false,
   });
 
   @override
@@ -72,6 +74,7 @@ class TargetOverlay extends StatelessWidget {
               groupingDiameter: groupingDiameter,
               referenceImpacts: referenceImpacts,
               zoomScale: zoomScale,
+              showRings: showRings,
             ),
             child: Stack(
               children: shots.map((shot) {
@@ -132,6 +135,7 @@ class _TargetOverlayPainter extends CustomPainter {
   final double? groupingDiameter;
   final List<Shot>? referenceImpacts;
   final double zoomScale;
+  final bool showRings;
 
   _TargetOverlayPainter({
     required this.shots,
@@ -146,12 +150,15 @@ class _TargetOverlayPainter extends CustomPainter {
     this.groupingDiameter,
     this.referenceImpacts,
     this.zoomScale = 1.0,
+    this.showRings = false,
   });
 
   @override
   void paint(Canvas canvas, Size size) {
     // Draw target center indicator
+    if (showRings) {
       _drawTargetCenter(canvas, size);
+    }
 
     // Draw grouping circle
     if (groupingCenterX != null && groupingCenterY != null && groupingDiameter != null && shots.length > 1) {
@@ -371,6 +378,7 @@ class _TargetOverlayPainter extends CustomPainter {
         groupingCenterY != oldDelegate.groupingCenterY ||
         groupingDiameter != oldDelegate.groupingDiameter ||
         referenceImpacts != oldDelegate.referenceImpacts ||
-        zoomScale != oldDelegate.zoomScale;
+        zoomScale != oldDelegate.zoomScale ||
+        showRings != oldDelegate.showRings;
   }
 }

lib/services/target_detection_service.dart

@@ -392,7 +392,11 @@ class TargetDetectionService {
       final impacts = await _yoloService.detectImpacts(imagePath);
 
       return impacts.map((impact) {
-        final score = targetType == TargetType.concentric
+        // Use YOLO-detected score (valeur) if available, otherwise calculate it
+        int score = impact.suggestedScore;
+        
+        if (score <= 0) {
+          score = targetType == TargetType.concentric
               ? _calculateConcentricScoreWithRings(
                   impact.x,
                   impact.y,
@@ -402,6 +406,7 @@ class TargetDetectionService {
                   ringCount,
                 )
               : _calculateSilhouetteScore(impact.x, impact.y, centerX, centerY);
+        }
 
         return DetectedImpactResult(
           x: impact.x,

lib/services/yolo_impact_detection_service.dart

@@ -7,25 +7,41 @@ import 'target_detection_service.dart';
 
 class YOLOImpactDetectionService {
   Interpreter? _interpreter;
+  int _inputSize = 640;
+  List<int> _outputShape = [1, 17, 8400];
+  int _numClasses = 13;
 
-  static const String modelPath = 'assets/models/yolov11n_impact.tflite';
+  static const String modelPath = 'assets/models/yolov8n_32.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');
+      // Get model metadata
-        _interpreter = await Interpreter.fromAsset(
+      final inputTensors = _interpreter!.getInputTensors();
-          'assets/models/yolov8n_impact.tflite',
+      if (inputTensors.isNotEmpty) {
-        );
+        // [1, 640, 640, 3] or [1, 3, 640, 640]
+        final shape = inputTensors[0].shape;
+        if (shape.length == 4) {
+          _inputSize = shape[1] == 3 ? shape[2] : shape[1];
+        }
+      }
+
+      final outputTensors = _interpreter!.getOutputTensors();
+      if (outputTensors.isNotEmpty) {
+        _outputShape = outputTensors[0].shape;
+        // Output is usually [1, 4 + num_classes, num_boxes]
+        if (_outputShape.length == 3) {
+          _numClasses = _outputShape[1] - 4;
+        }
       }
 
       print('YOLO Interpreter loaded successfully');
+      print('Model Input Size: $_inputSize');
+      print('Model Output Shape: $_outputShape (Classes: $_numClasses)');
     } catch (e) {
       print('Error loading YOLO model: $e');
     }
@@ -37,31 +53,35 @@ class YOLOImpactDetectionService {
 
     try {
       final bytes = File(imagePath).readAsBytesSync();
-      final originalImage = img.decodeImage(bytes);
+      final decodedImage = img.decodeImage(bytes);
-      if (originalImage == null) return [];
+      if (decodedImage == null) return [];
+
+      final originalImage = img.bakeOrientation(decodedImage);
 
-      // YOLOv8/v11 usually takes 640x640
-      const int inputSize = 640;
       final resizedImage = img.copyResize(
         originalImage,
-        width: inputSize,
+        width: _inputSize,
-        height: inputSize,
+        height: _inputSize,
       );
 
-      // Prepare input tensor
+      var input = _imageToByteListFloat32(resizedImage, _inputSize);
-      var input = _imageToByteListFloat32(resizedImage, inputSize);
       
-      // Raw YOLO output shape usually [1, 4 + num_classes, 8400]
+      // Allocate output buffer dynamically
-      // For single class "impact", it's [1, 5, 8400]
+      var output = List<double>.filled(
-      var output = List<double>.filled(1 * 5 * 8400, 0).reshape([1, 5, 8400]);
+        _outputShape.fold(1, (a, b) => a * b), 
+        0
+      ).reshape(_outputShape);
 
       _interpreter!.run(input, output);
 
-      return _processOutput(
+      final results = _processOutput(
         output[0],
         originalImage.width,
         originalImage.height,
       );
+
+      print('YOLO Detection result count: ${results.length}');
+      return results;
     } catch (e) {
       print('Error during YOLO inference: $e');
       return [];
@@ -76,33 +96,55 @@ class YOLOImpactDetectionService {
     final List<_Detection> candidates = [];
     const double threshold = 0.25;
 
-    // output is [5, 8400] -> [x, y, w, h, conf]
+    // output is typically [4 + numClasses, numBoxes]
-    for (int i = 0; i < 8400; i++) {
+    final int rows = output.length;
-      final double confidence = output[4][i];
+    final int numBoxes = output[0].length;
-      if (confidence > threshold) {
+
+    for (int i = 0; i < numBoxes; i++) {
+      double maxConfidence = 0;
+      int bestClass = 4;
+      
+      // Find best class among all classes (indices 4 to rows-1)
+      for (int c = 4; c < rows; c++) {
+        if (output[c][i] > maxConfidence) {
+          maxConfidence = output[c][i];
+          bestClass = c;
+        }
+      }
+
+      if (maxConfidence > threshold) {
+        final int classIndex = bestClass - 4;
+        
         candidates.add(
           _Detection(
-            x: output[0][i],
+            // Use dynamic mapping: 0,1,2,3 are typically x,y,w,h
-            y: output[1][i],
+            // We'll keep the current mapping for now as it matches user's previous model
+            y: output[0][i],
+            x: output[1][i],
             w: output[2][i],
             h: output[3][i],
-            confidence: confidence,
+            confidence: maxConfidence,
+            classIndex: classIndex,
           ),
         );
       }
     }
 
-    // Apply Non-Max Suppression (NMS)
     final List<_Detection> suppressed = _nms(candidates);
 
     return suppressed
         .map(
-          (det) => DetectedImpactResult(
+          (det) {
-            x: det.x / 640.0,
+            // Score = ClassIndex (0 to 10) for impact models
-            y: det.y / 640.0,
+            int score = det.classIndex;
+            
+            return DetectedImpactResult(
+              x: det.x, 
+              y: det.y,
               radius: 5.0,
-            suggestedScore: 0,
+              suggestedScore: score,
-          ),
+            );
+          },
         )
         .toList();
   }
@@ -110,7 +152,6 @@ class YOLOImpactDetectionService {
   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 = [];
@@ -164,11 +205,13 @@ class YOLOImpactDetectionService {
 
 class _Detection {
   final double x, y, w, h, confidence;
+  final int classIndex;
   _Detection({
     required this.x,
     required this.y,
     required this.w,
     required this.h,
     required this.confidence,
+    required this.classIndex,
   });
 }

pubspec.lock

@@ -665,10 +665,10 @@ packages:
     dependency: "direct main"
     description:
       name: tflite_flutter
-      sha256: ffb8651fdb116ab0131d6dc47ff73883e0f634ad1ab12bb2852eef1bbeab4a6a
+      sha256: "48e6fde2ad97162bb66a16a142f4c4698add9e8cd397ce9d1cc7451b55537ac1"
       url: "https://pub.dev"
     source: hosted
-    version: "0.10.4"
+    version: "0.11.0"
   typed_data:
     dependency: transitive
     description:

pubspec.yaml

@@ -65,7 +65,7 @@ dependencies:
   image: ^4.1.7
 
   # Machine Learning for YOLOv8
-  tflite_flutter: ^0.10.4
+  tflite_flutter: ^0.11.0
 
 dev_dependencies:
   flutter_test:
@@ -90,7 +90,8 @@ flutter:
   uses-material-design: true
 
   # To add assets to your application, add an assets section, like this:
-  # assets:
+  assets:
+    - assets/models/yolov8n_32.tflite
   #   - images/a_dot_burr.jpeg
   #   - images/a_dot_ham.jpeg