feat: implement base architecture and core repositories for weapon tracking and target analysis functionality

lib/services/image_processing_service.dart

@@ -1,4 +1,5 @@
 import 'dart:io';
+import 'package:flutter/foundation.dart';
 import 'dart:math' as math;
 import 'package:image/image.dart' as img;
 
@@ -189,7 +190,7 @@ class ImageProcessingService {
         );
       }).toList();
     } catch (e) {
-      print('Error detecting impacts: $e');
+      debugPrint('Error detecting impacts: $e');
       return [];
     }
   }
@@ -236,14 +237,14 @@ class ImageProcessingService {
       final fillRatios = <double>[];
       final thresholds = <double>[];
 
-      print('Analyzing ${references.length} reference impacts...');
+      debugPrint('Analyzing ${references.length} reference impacts...');
 
       for (int refIndex = 0; refIndex < references.length; refIndex++) {
         final ref = references[refIndex];
         final centerX = (ref.x * width).round().clamp(0, width - 1);
         final centerY = (ref.y * height).round().clamp(0, height - 1);
 
-        print('Reference $refIndex at ($centerX, $centerY)');
+        debugPrint('Reference $refIndex at ($centerX, $centerY)');
 
         // AMÉLIORATION : Recherche du point le plus sombre dans une zone plus large
         int darkestX = centerX;
@@ -275,7 +276,7 @@ class ImageProcessingService {
           if (darkestLum < 50 && r > 5) break;
         }
 
-        print('  Darkest point at ($darkestX, $darkestY), lum=$darkestLum');
+        debugPrint('  Darkest point at ($darkestX, $darkestY), lum=$darkestLum');
 
         // Now find the blob at the darkest point using adaptive threshold
         final blobResult = _findBlobAtPoint(blurred, darkestX, darkestY, width, height);
@@ -286,15 +287,15 @@ class ImageProcessingService {
           circularities.add(blobResult.circularity);
           fillRatios.add(blobResult.fillRatio);
           thresholds.add(blobResult.threshold);
-          print('  Found blob: size=${blobResult.size}, circ=${blobResult.circularity.toStringAsFixed(2)}, '
+          debugPrint('  Found blob: size=${blobResult.size}, circ=${blobResult.circularity.toStringAsFixed(2)}, '
                 'fill=${blobResult.fillRatio.toStringAsFixed(2)}, threshold=${blobResult.threshold.toStringAsFixed(0)}');
         } else {
-          print('  No valid blob found at this reference');
+          debugPrint('  No valid blob found at this reference');
         }
       }
 
       if (luminances.isEmpty) {
-        print('ERROR: No valid blobs found from any reference!');
+        debugPrint('ERROR: No valid blobs found from any reference!');
         return null;
       }
 
@@ -329,11 +330,11 @@ class ImageProcessingService {
         avgDarkThreshold: avgThreshold,
       );
 
-      print('Learned characteristics: $result');
+      debugPrint('Learned characteristics: $result');
 
       return result;
     } catch (e) {
-      print('Error analyzing reference impacts: $e');
+      debugPrint('Error analyzing reference impacts: $e');
       return null;
     }
   }
@@ -680,7 +681,7 @@ class ImageProcessingService {
       // Calculate minimum fill ratio - impacts pleins
       final minFillRatio = (characteristics.avgFillRatio - 0.2).clamp(0.35, 0.85);
 
-      print('Detection params: thresholds=$thresholds, size=$minSize-$maxSize, '
+      debugPrint('Detection params: thresholds=$thresholds, size=$minSize-$maxSize, '
             'circ>=$effectiveMinCircularity, fill>=$minFillRatio');
 
       // Détecter avec plusieurs seuils et combiner les résultats
@@ -722,7 +723,7 @@ class ImageProcessingService {
         return true;
       }).toList();
 
-      print('Found ${filteredBlobs.length} impacts after filtering (from ${mergedBlobs.length} merged)');
+      debugPrint('Found ${filteredBlobs.length} impacts after filtering (from ${mergedBlobs.length} merged)');
 
       // Convert to relative coordinates
       return filteredBlobs.map((blob) {
@@ -733,7 +734,7 @@ class ImageProcessingService {
         );
       }).toList();
     } catch (e) {
-      print('Error detecting impacts from references: $e');
+      debugPrint('Error detecting impacts from references: $e');
       return [];
     }
   }
@@ -776,50 +777,6 @@ class ImageProcessingService {
     return merged;
   }
 
-  /// Detect dark spots with adaptive luminance range
-  List<_Blob> _detectDarkSpotsAdaptive(
-    img.Image image,
-    int minLuminance,
-    int maxLuminance,
-    int minSize,
-    int maxSize, {
-    double minCircularity = 0.5,
-    double minFillRatio = 0.5,
-  }) {
-    final width = image.width;
-    final height = image.height;
-
-    // Create binary mask of pixels within luminance range
-    final mask = List.generate(height, (_) => List.filled(width, false));
-
-    for (int y = 0; y < height; y++) {
-      for (int x = 0; x < width; x++) {
-        final pixel = image.getPixel(x, y);
-        final luminance = img.getLuminance(pixel);
-        mask[y][x] = luminance >= minLuminance && luminance <= maxLuminance;
-      }
-    }
-
-    // Find connected components
-    final visited = List.generate(height, (_) => List.filled(width, false));
-    final blobs = <_Blob>[];
-
-    for (int y = 0; y < height; y++) {
-      for (int x = 0; x < width; x++) {
-        if (mask[y][x] && !visited[y][x]) {
-          final blob = _floodFill(mask, visited, x, y, width, height);
-          if (blob.size >= minSize &&
-              blob.size <= maxSize &&
-              blob.circularity >= minCircularity &&
-              blob.fillRatio >= minFillRatio) {
-            blobs.add(blob);
-          }
-        }
-      }
-    }
-
-    return _filterOverlappingBlobs(blobs);
-  }
 
   /// Detect dark spots in a grayscale image using blob detection
   List<_Blob> _detectDarkSpots(