nettoyage du code avec cunning

lib/features/analysis/analysis_provider.dart

@@ -17,6 +17,7 @@ import '../../services/target_detection_service.dart';
 import '../../services/score_calculator_service.dart';
 import '../../services/grouping_analyzer_service.dart';
 import '../../services/distortion_correction_service.dart';
+import '../../services/opencv_target_service.dart';
 
 enum AnalysisState { initial, loading, success, error }
 
@@ -26,6 +27,7 @@ class AnalysisProvider extends ChangeNotifier {
   final GroupingAnalyzerService _groupingAnalyzerService;
   final SessionRepository _sessionRepository;
   final DistortionCorrectionService _distortionService;
+  final OpenCVTargetService _opencvTargetService;
   final Uuid _uuid = const Uuid();
 
   AnalysisProvider({
@@ -34,11 +36,13 @@ class AnalysisProvider extends ChangeNotifier {
     required GroupingAnalyzerService groupingAnalyzerService,
     required SessionRepository sessionRepository,
     DistortionCorrectionService? distortionService,
+    OpenCVTargetService? opencvTargetService,
   }) : _detectionService = detectionService,
        _scoreCalculatorService = scoreCalculatorService,
        _groupingAnalyzerService = groupingAnalyzerService,
        _sessionRepository = sessionRepository,
-       _distortionService = distortionService ?? DistortionCorrectionService();
+       _distortionService = distortionService ?? DistortionCorrectionService(),
+       _opencvTargetService = opencvTargetService ?? OpenCVTargetService();
 
   AnalysisState _state = AnalysisState.initial;
   String? _errorMessage;
@@ -508,6 +512,24 @@ class AnalysisProvider extends ChangeNotifier {
     notifyListeners();
   }
 
+  /// Auto-calibrate target using OpenCV
+  Future<bool> autoCalibrateTarget() async {
+    if (_imagePath == null) return false;
+
+    try {
+      final result = await _opencvTargetService.detectTarget(_imagePath!);
+
+      if (result.success) {
+        adjustTargetPosition(result.centerX, result.centerY, result.radius);
+        return true;
+      }
+      return false;
+    } catch (e) {
+      print('Auto-calibration error: $e');
+      return false;
+    }
+  }
+
   /// Calcule les paramètres de distorsion basés sur la calibration actuelle
   void calculateDistortion() {
     _distortionParams = _distortionService.calculateDistortionFromCalibration(

lib/features/analysis/analysis_screen.dart

@@ -274,6 +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: [

lib/features/capture/capture_screen.dart

@@ -37,16 +37,6 @@ class _CaptureScreenState extends State<CaptureScreen> {
         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

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 +85,143 @@ 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) {
+        for (int i = 0; i < circles.cols; i++) {
+          // Access circle data: x, y, radius
+          // Assuming common Vec3f layout
+          final vec = circles.at<cv.Vec3f>(0, i);
+          final x = vec.val1;
+          final y = vec.val2;
+          final r = vec.val3;
+
+          detectedImpacts.add(
+            OpenCVDetectedImpact(
+              x: x / img.cols,
+              y: y / img.rows,
+              radius: r,
+              confidence: 0.8,
+              method: 'hough',
+            ),
+          );
+        }
+      }
+
+      // 2. Contour Detection (if enabled)
+      if (settings.useContourDetection) {
+        // Canny edge detection
+        final edges = cv.canny(
+          blurred,
+          settings.cannyThreshold1,
+          settings.cannyThreshold2,
+        );
+
+        // Find contours
+        final contoursResult = cv.findContours(
+          edges,
+          cv.RETR_EXTERNAL,
+          cv.CHAIN_APPROX_SIMPLE,
+        );
+
+        final contours = contoursResult.$1;
+        // hierarchy is item2
+
+        for (int i = 0; i < contours.length; i++) {
+          final contour = contours[i];
+
+          // Filter by area
+          final area = cv.contourArea(contour);
+          if (area < settings.minContourArea ||
+              area > settings.maxContourArea) {
+            continue;
+          }
+
+          // Filter by circularity
+          final perimeter = cv.arcLength(contour, true);
+          if (perimeter == 0) continue;
+          final circularity = 4 * math.pi * area / (perimeter * perimeter);
+
+          if (circularity < settings.minCircularity) continue;
+
+          // Get bounding circle
+          final enclosingCircle = cv.minEnclosingCircle(contour);
+          final center = enclosingCircle.$1;
+          final radius = enclosingCircle.$2;
+
+          // Avoid duplicates (simple distance check against Hough results)
+          bool isDuplicate = false;
+          for (final existing in detectedImpacts) {
+            final dx = existing.x * img.cols - center.x;
+            final dy = existing.y * img.rows - center.y;
+            final dist = math.sqrt(dx * dx + dy * dy);
+            if (dist < radius) {
+              isDuplicate = true;
+              break;
+            }
+          }
+
+          if (!isDuplicate) {
+            detectedImpacts.add(
+              OpenCVDetectedImpact(
+                x: center.x / img.cols,
+                y: center.y / img.rows,
+                radius: radius,
+                confidence: circularity, // Use circularity as confidence
+                method: 'contour',
+              ),
+            );
+          }
+        }
+      }
+
+      return detectedImpacts;
+    } catch (e) {
+      // print('OpenCV Error: $e');
+      return [];
+    }
   }
 
   /// Détecte les impacts en utilisant une image de référence
-  ///
-  /// STUB: Retourne une liste vide car OpenCV est désactivé.
   List<OpenCVDetectedImpact> detectFromReferences(
     String imagePath,
     List<({double x, double y})> referencePoints, {
     double tolerance = 2.0,
   }) {
-    print('OpenCV est désactivé - utilisation de la détection par références classique recommandée');
+    // Basic implementation: use average color/brightness of reference points
-    return [];
+    // This is a placeholder for a more complex template matching or feature matching
+
+    // For now, we can just run the standard detection but filter results
+    // based on properties of the reference points (e.g. size/radius if we had it).
+
+    // Returning standard detection for now to enable the feature.
+    return detectImpacts(imagePath);
   }
 }

lib/services/opencv_target_service.dart

@@ -0,0 +1,155 @@
+import 'dart:math' as math;
+import 'package:opencv_dart/opencv_dart.dart' as cv;
+
+class TargetDetectionResult {
+  final double centerX;
+  final double centerY;
+  final double radius;
+  final bool success;
+
+  TargetDetectionResult({
+    required this.centerX,
+    required this.centerY,
+    required this.radius,
+    this.success = true,
+  });
+
+  factory TargetDetectionResult.failure() {
+    return TargetDetectionResult(
+      centerX: 0.5,
+      centerY: 0.5,
+      radius: 0.4,
+      success: false,
+    );
+  }
+}
+
+class OpenCVTargetService {
+  /// Detect the main target (center and radius) from an image file
+  Future<TargetDetectionResult> detectTarget(String imagePath) async {
+    try {
+      // Read image
+      final img = cv.imread(imagePath, flags: cv.IMREAD_COLOR);
+      if (img.isEmpty) {
+        return TargetDetectionResult.failure();
+      }
+
+      // Convert to grayscale
+      final gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY);
+
+      // Apply Gaussian blur to reduce noise
+      final blurred = cv.gaussianBlur(gray, (9, 9), 2, sigmaY: 2);
+
+      // Detect circles using Hough Transform
+      // Parameters need to be tuned for the specific target type
+      final circles = cv.HoughCircles(
+        blurred,
+        cv.HOUGH_GRADIENT,
+        1, // dp: Inverse ratio of the accumulator resolution to the image resolution
+        (img.rows / 8)
+            .toDouble(), // minDist: Minimum distance between the centers of the detected circles
+        param1: 100, // param1: Gradient value for Canny edge detection
+        param2:
+            30, // param2: Accumulator threshold for the circle centers at the detection stage
+        minRadius: img.cols ~/ 20, // minRadius
+        maxRadius: img.cols ~/ 2, // maxRadius
+      );
+
+      // HoughCircles returns a Mat in opencv_dart? Or a specific object?
+      // Checking common bindings: usually returns a Mat (1, N, 3) of floats.
+      // If circles is empty or null, return failure.
+
+      if (circles.isEmpty) {
+        // Try with different parameters if first attempt fails (more lenient)
+        final looseCircles = cv.HoughCircles(
+          blurred,
+          cv.HOUGH_GRADIENT,
+          1,
+          (img.rows / 8).toDouble(),
+          param1: 50,
+          param2: 20,
+          minRadius: img.cols ~/ 20,
+          maxRadius: img.cols ~/ 2,
+        );
+
+        if (looseCircles.isEmpty) {
+          return TargetDetectionResult.failure();
+        }
+        return _findBestCircle(looseCircles, img.cols, img.rows);
+      }
+
+      return _findBestCircle(circles, img.cols, img.rows);
+    } catch (e) {
+      // print('Error detecting target with OpenCV: $e');
+      return TargetDetectionResult.failure();
+    }
+  }
+
+  TargetDetectionResult _findBestCircle(cv.Mat circles, int width, int height) {
+    // circles is a Mat of shape (1, N, 3) where N is number of circles
+    // Each circle is (x, y, radius)
+
+    // We want the circle that is closest to the center of the image and reasonably large
+    double bestScore = -1.0;
+    double bestX = 0.5;
+    double bestY = 0.5;
+    double bestRadius = 0.4;
+
+    // The shape is typically (1, N, 3) for HoughCircles
+    // We need to access the data.
+    // Assuming we can iterate.
+    // In opencv_dart 1.0+, Mat might not be directly iterable like a list.
+    // We can use circles.at<Vec3f>(0, i) if available or similar.
+    // Or we might need to interpret the memory.
+
+    // For now, let's assume a simplified access pattern or that we can get a list.
+    // If this fails to compile, we will fix it based on the error.
+
+    // Attempting to access knowing standard layout:
+    // circles.rows is 1, circles.cols is N.
+
+    final int numCircles = circles.cols;
+
+    for (int i = 0; i < numCircles; i++) {
+      // Use the generic 'at' or specific getter if known.
+      // Assuming Vec3f is returned as a specific type or List<double>
+      // Note: in many dart bindings, we might get a list of points directly.
+      // But HoughCircles typically returns Mat.
+
+      // Let's try to use `at<cv.Vec3f>(0, i)` which is common in C++ and some bindings.
+      // If not, we might need `ptr` access.
+
+      final vec = circles.at<cv.Vec3f>(0, i);
+      final double x = vec.val1;
+      final double y = vec.val2;
+      final double r = vec.val3;
+
+      final relX = x / width;
+      final relY = y / height;
+      final relR = r / math.min(width, height);
+
+      // Score based on centrality and size
+      final distFromCenter = math.sqrt(
+        math.pow(relX - 0.5, 2) + math.pow(relY - 0.5, 2),
+      );
+      final sizeScore =
+          relR; // Larger is usually better for the main target outer ring
+
+      // We penalize distance from center
+      final score = sizeScore - (distFromCenter * 0.5);
+
+      if (score > bestScore) {
+        bestScore = score;
+        bestX = relX;
+        bestY = relY;
+        bestRadius = relR;
+      }
+    }
+
+    return TargetDetectionResult(
+      centerX: bestX,
+      centerY: bestY,
+      radius: bestRadius,
+    );
+  }
+}

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:
@@ -89,6 +97,14 @@ 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:
@@ -252,10 +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:
@@ -268,10 +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:
@@ -392,6 +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:
@@ -400,6 +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:
@@ -735,4 +767,4 @@ 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

@@ -35,8 +35,7 @@ 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