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2 Commits
2e81f4b69e
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| Author | SHA1 | Date | |
|---|---|---|---|
| e32833e366 | |||
| d4cb179fde |
@@ -53,6 +53,7 @@ class AnalysisProvider extends ChangeNotifier {
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double _targetCenterX = 0.5;
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double _targetCenterY = 0.5;
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double _targetRadius = 0.4;
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double _targetInnerRadius = 0.04;
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int _ringCount = 10;
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List<double>? _ringRadii; // Individual ring radii multipliers
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double _imageAspectRatio = 1.0; // width / height
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@@ -83,6 +84,7 @@ class AnalysisProvider extends ChangeNotifier {
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double get targetCenterX => _targetCenterX;
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double get targetCenterY => _targetCenterY;
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double get targetRadius => _targetRadius;
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double get targetInnerRadius => _targetInnerRadius;
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int get ringCount => _ringCount;
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List<double>? get ringRadii =>
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_ringRadii != null ? List.unmodifiable(_ringRadii!) : null;
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@@ -138,6 +140,7 @@ class AnalysisProvider extends ChangeNotifier {
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_targetCenterX = 0.5;
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_targetCenterY = 0.5;
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_targetRadius = 0.4;
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_targetInnerRadius = 0.04;
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// Initialize empty shots list
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_shots = [];
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@@ -160,6 +163,7 @@ class AnalysisProvider extends ChangeNotifier {
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_targetCenterX = result.centerX;
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_targetCenterY = result.centerY;
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_targetRadius = result.radius;
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_targetInnerRadius = result.radius * 0.1;
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// Create shots from detected impacts
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_shots = result.impacts.map((impact) {
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@@ -488,12 +492,14 @@ class AnalysisProvider extends ChangeNotifier {
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void adjustTargetPosition(
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double centerX,
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double centerY,
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double innerRadius,
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double radius, {
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int? ringCount,
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List<double>? ringRadii,
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}) {
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_targetCenterX = centerX;
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_targetCenterY = centerY;
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_targetInnerRadius = innerRadius;
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_targetRadius = radius;
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if (ringCount != null) {
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_ringCount = ringCount;
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@@ -517,10 +523,29 @@ class AnalysisProvider extends ChangeNotifier {
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if (_imagePath == null) return false;
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try {
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// 1. Attempt to correct perspective/distortion first
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final correctedPath = await _distortionService
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.correctPerspectiveWithConcentricMesh(_imagePath!);
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if (correctedPath != _imagePath) {
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_imagePath = correctedPath;
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_correctedImagePath = correctedPath;
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_distortionCorrectionEnabled = true;
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_imageAspectRatio =
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1.0; // The corrected image is always square (side x side)
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notifyListeners();
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}
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// 2. Detect the target on the straight/corrected image
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final result = await _opencvTargetService.detectTarget(_imagePath!);
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if (result.success) {
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adjustTargetPosition(result.centerX, result.centerY, result.radius);
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adjustTargetPosition(
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result.centerX,
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result.centerY,
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result.radius * 0.1,
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result.radius,
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);
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return true;
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}
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return false;
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@@ -687,6 +712,7 @@ class AnalysisProvider extends ChangeNotifier {
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_targetCenterX = 0.5;
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_targetCenterY = 0.5;
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_targetRadius = 0.4;
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_targetInnerRadius = 0.04;
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_ringCount = 10;
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_ringRadii = null;
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_imageAspectRatio = 1.0;
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@@ -275,7 +275,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
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child: Column(
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children: [
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// Auto-calibrate button
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/*SizedBox(
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SizedBox(
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width: double.infinity,
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child: ElevatedButton.icon(
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onPressed: () async {
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@@ -334,7 +334,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
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foregroundColor: Colors.white,
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),
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),
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),*/
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),
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const SizedBox(height: 16),
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// Ring count slider
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Row(
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@@ -361,6 +361,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
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provider.adjustTargetPosition(
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provider.targetCenterX,
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provider.targetCenterY,
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provider.targetInnerRadius,
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provider.targetRadius,
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ringCount: value.round(),
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);
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@@ -411,6 +412,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
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provider.adjustTargetPosition(
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provider.targetCenterX,
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provider.targetCenterY,
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provider.targetInnerRadius,
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value,
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ringCount: provider.ringCount,
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);
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@@ -535,6 +537,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
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initialCenterX: provider.targetCenterX,
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initialCenterY: provider.targetCenterY,
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initialRadius: provider.targetRadius,
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initialInnerRadius: provider.targetInnerRadius,
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initialRingCount: provider.ringCount,
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initialRingRadii: provider.ringRadii,
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targetType: provider.targetType!,
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@@ -542,6 +545,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
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(
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centerX,
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centerY,
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innerRadius,
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radius,
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ringCount, {
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List<double>? ringRadii,
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@@ -549,6 +553,7 @@ class _AnalysisScreenContentState extends State<_AnalysisScreenContent> {
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provider.adjustTargetPosition(
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centerX,
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centerY,
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innerRadius,
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radius,
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ringCount: ringCount,
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ringRadii: ringRadii,
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@@ -13,16 +13,26 @@ class TargetCalibration extends StatefulWidget {
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final double initialCenterX;
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final double initialCenterY;
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final double initialRadius;
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final double initialInnerRadius;
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final int initialRingCount;
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final TargetType targetType;
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final List<double>? initialRingRadii;
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final Function(double centerX, double centerY, double radius, int ringCount, {List<double>? ringRadii}) onCalibrationChanged;
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final Function(
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double centerX,
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double centerY,
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double innerRadius,
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double radius,
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int ringCount, {
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List<double>? ringRadii,
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})
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onCalibrationChanged;
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const TargetCalibration({
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super.key,
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required this.initialCenterX,
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required this.initialCenterY,
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required this.initialRadius,
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required this.initialInnerRadius,
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this.initialRingCount = 10,
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required this.targetType,
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this.initialRingRadii,
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@@ -37,11 +47,13 @@ class _TargetCalibrationState extends State<TargetCalibration> {
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late double _centerX;
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late double _centerY;
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late double _radius;
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late double _innerRadius;
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late int _ringCount;
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late List<double> _ringRadii;
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bool _isDraggingCenter = false;
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bool _isDraggingRadius = false;
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bool _isDraggingInnerRadius = false;
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@override
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void initState() {
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@@ -49,28 +61,57 @@ class _TargetCalibrationState extends State<TargetCalibration> {
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_centerX = widget.initialCenterX;
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_centerY = widget.initialCenterY;
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_radius = widget.initialRadius;
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_innerRadius = widget.initialInnerRadius;
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_ringCount = widget.initialRingCount;
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_initRingRadii();
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}
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void _initRingRadii() {
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if (widget.initialRingRadii != null && widget.initialRingRadii!.length == _ringCount) {
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if (widget.initialRingRadii != null &&
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widget.initialRingRadii!.length == _ringCount) {
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_ringRadii = List.from(widget.initialRingRadii!);
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} else {
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// Initialize with default proportional radii
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_ringRadii = List.generate(_ringCount, (i) => (i + 1) / _ringCount);
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// Initialize with default proportional radii interpolated between inner and outer
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_ringRadii = List.generate(_ringCount, (i) {
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if (_ringCount <= 1) return 1.0;
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final ratio = _innerRadius / _radius;
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return ratio + (1.0 - ratio) * i / (_ringCount - 1);
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});
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}
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}
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@override
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void didUpdateWidget(TargetCalibration oldWidget) {
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super.didUpdateWidget(oldWidget);
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bool shouldReinit = false;
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if (widget.initialCenterX != oldWidget.initialCenterX &&
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!_isDraggingCenter) {
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_centerX = widget.initialCenterX;
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}
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if (widget.initialCenterY != oldWidget.initialCenterY &&
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!_isDraggingCenter) {
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_centerY = widget.initialCenterY;
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}
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if (widget.initialRingCount != oldWidget.initialRingCount) {
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_ringCount = widget.initialRingCount;
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_initRingRadii();
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shouldReinit = true;
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}
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if (widget.initialRadius != oldWidget.initialRadius && !_isDraggingRadius) {
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_radius = widget.initialRadius;
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shouldReinit = true;
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}
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if (widget.initialInnerRadius != oldWidget.initialInnerRadius &&
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!_isDraggingInnerRadius) {
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_innerRadius = widget.initialInnerRadius;
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shouldReinit = true;
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}
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if (widget.initialRingRadii != oldWidget.initialRingRadii) {
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shouldReinit = true;
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}
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if (shouldReinit) {
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_initRingRadii();
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}
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}
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@@ -90,11 +131,13 @@ class _TargetCalibrationState extends State<TargetCalibration> {
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centerX: _centerX,
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centerY: _centerY,
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radius: _radius,
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innerRadius: _innerRadius,
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ringCount: _ringCount,
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ringRadii: _ringRadii,
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targetType: widget.targetType,
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isDraggingCenter: _isDraggingCenter,
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isDraggingRadius: _isDraggingRadius,
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isDraggingInnerRadius: _isDraggingInnerRadius,
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),
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),
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);
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@@ -109,21 +152,42 @@ class _TargetCalibrationState extends State<TargetCalibration> {
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// Check if tapping on center handle
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final distToCenter = _distance(tapX, tapY, _centerX, _centerY);
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// Check if tapping on radius handle (on the right edge of the outermost circle)
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// Check if tapping on outer radius handle
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final minDim = math.min(size.width, size.height);
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final outerRadius = _radius * (_ringRadii.isNotEmpty ? _ringRadii.last : 1.0);
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final outerRadius = _radius;
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final radiusHandleX = _centerX + outerRadius * minDim / size.width;
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final radiusHandleY = _centerY;
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final distToRadiusHandle = _distance(tapX, tapY, radiusHandleX.clamp(0.0, 1.0), radiusHandleY.clamp(0.0, 1.0));
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final distToOuterHandle = _distance(
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tapX,
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tapY,
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radiusHandleX.clamp(0.0, 1.0),
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radiusHandleY.clamp(0.0, 1.0),
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);
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// Check if tapping on inner radius handle (top edge of innermost circle)
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final actualInnerRadius = _innerRadius;
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final innerHandleX = _centerX;
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final innerHandleY = _centerY - actualInnerRadius * minDim / size.height;
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final distToInnerHandle = _distance(
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tapX,
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tapY,
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innerHandleX.clamp(0.0, 1.0),
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innerHandleY.clamp(0.0, 1.0),
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);
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// Increase touch target size slightly for handles
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if (distToCenter < 0.05) {
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setState(() {
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_isDraggingCenter = true;
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});
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} else if (distToRadiusHandle < 0.05) {
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} else if (distToOuterHandle < 0.05) {
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setState(() {
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_isDraggingRadius = true;
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});
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} else if (distToInnerHandle < 0.05) {
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setState(() {
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_isDraggingInnerRadius = true;
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});
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} else if (distToCenter < _radius + 0.02) {
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// Tapping inside the target - move center
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setState(() {
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@@ -143,19 +207,36 @@ class _TargetCalibrationState extends State<TargetCalibration> {
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_centerX = _centerX + deltaX;
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_centerY = _centerY + deltaY;
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} else if (_isDraggingRadius) {
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// Adjust outer radius (scales all rings proportionally)
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// Adjust outer radius
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final newRadius = _radius + deltaX * (size.width / minDim);
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_radius = newRadius.clamp(0.05, 3.0);
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_radius = newRadius.clamp(math.max(0.05, _innerRadius + 0.01), 3.0);
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_initRingRadii(); // Recalculate linear separation
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} else if (_isDraggingInnerRadius) {
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// Adjust inner radius (sliding up reduces Y, so deltaY is negative when growing. Thus we subtract deltaY)
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final newInnerRadius = _innerRadius - deltaY * (size.height / minDim);
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_innerRadius = newInnerRadius.clamp(
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0.01,
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math.max(0.01, _radius - 0.01),
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);
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_initRingRadii(); // Recalculate linear separation
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}
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});
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widget.onCalibrationChanged(_centerX, _centerY, _radius, _ringCount, ringRadii: _ringRadii);
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widget.onCalibrationChanged(
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_centerX,
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_centerY,
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_innerRadius,
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_radius,
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_ringCount,
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ringRadii: _ringRadii,
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);
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}
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void _onPanEnd() {
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setState(() {
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_isDraggingCenter = false;
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_isDraggingRadius = false;
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_isDraggingInnerRadius = false;
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});
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}
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@@ -170,21 +251,25 @@ class _CalibrationPainter extends CustomPainter {
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final double centerX;
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final double centerY;
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final double radius;
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final double innerRadius;
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final int ringCount;
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final List<double> ringRadii;
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final TargetType targetType;
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final bool isDraggingCenter;
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final bool isDraggingRadius;
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final bool isDraggingInnerRadius;
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_CalibrationPainter({
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required this.centerX,
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required this.centerY,
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required this.radius,
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required this.innerRadius,
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required this.ringCount,
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required this.ringRadii,
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required this.targetType,
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required this.isDraggingCenter,
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required this.isDraggingRadius,
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required this.isDraggingInnerRadius,
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});
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@override
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@@ -192,6 +277,7 @@ class _CalibrationPainter extends CustomPainter {
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final centerPx = Offset(centerX * size.width, centerY * size.height);
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final minDim = size.width < size.height ? size.width : size.height;
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final baseRadiusPx = radius * minDim;
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final innerRadiusPx = innerRadius * minDim;
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if (targetType == TargetType.concentric) {
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_drawConcentricZones(canvas, size, centerPx, baseRadiusPx);
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@@ -199,17 +285,42 @@ class _CalibrationPainter extends CustomPainter {
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_drawSilhouetteZones(canvas, size, centerPx, baseRadiusPx);
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}
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// Fullscreen crosshairs when dragging center
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if (isDraggingCenter) {
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final crosshairLinePaint = Paint()
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..color = AppTheme.successColor.withValues(alpha: 0.5)
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..strokeWidth = 1;
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canvas.drawLine(
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Offset(0, centerPx.dy),
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Offset(size.width, centerPx.dy),
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crosshairLinePaint,
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);
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canvas.drawLine(
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Offset(centerPx.dx, 0),
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Offset(centerPx.dx, size.height),
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crosshairLinePaint,
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);
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}
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// Draw center handle
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_drawCenterHandle(canvas, centerPx);
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// Draw radius handle (for outer ring)
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_drawRadiusHandle(canvas, size, centerPx, baseRadiusPx);
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// Draw inner radius handle
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_drawInnerRadiusHandle(canvas, size, centerPx, innerRadiusPx);
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// Draw instructions
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_drawInstructions(canvas, size);
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}
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void _drawConcentricZones(Canvas canvas, Size size, Offset center, double baseRadius) {
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void _drawConcentricZones(
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Canvas canvas,
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Size size,
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Offset center,
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double baseRadius,
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) {
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// Generate colors for zones
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List<Color> zoneColors = [];
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for (int i = 0; i < ringCount; i++) {
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@@ -235,7 +346,9 @@ class _CalibrationPainter extends CustomPainter {
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// Draw from outside to inside
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for (int i = ringCount - 1; i >= 0; i--) {
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final ringRadius = ringRadii.length > i ? ringRadii[i] : (i + 1) / ringCount;
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final ringRadius = ringRadii.length > i
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? ringRadii[i]
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: (i + 1) / ringCount;
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final zoneRadius = baseRadius * ringRadius;
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zonePaint.color = zoneColors[i];
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@@ -244,12 +357,12 @@ class _CalibrationPainter extends CustomPainter {
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}
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// Draw zone labels (only if within visible area)
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final textPainter = TextPainter(
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textDirection: TextDirection.ltr,
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);
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final textPainter = TextPainter(textDirection: TextDirection.ltr);
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for (int i = 0; i < ringCount; i++) {
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final ringRadius = ringRadii.length > i ? ringRadii[i] : (i + 1) / ringCount;
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final ringRadius = ringRadii.length > i
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? ringRadii[i]
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: (i + 1) / ringCount;
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final prevRingRadius = i > 0
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? (ringRadii.length > i - 1 ? ringRadii[i - 1] : i / ringCount)
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: 0.0;
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@@ -268,9 +381,7 @@ class _CalibrationPainter extends CustomPainter {
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color: Colors.white.withValues(alpha: 0.9),
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fontSize: 12,
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fontWeight: FontWeight.bold,
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shadows: const [
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Shadow(color: Colors.black, blurRadius: 2),
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],
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shadows: const [Shadow(color: Colors.black, blurRadius: 2)],
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),
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);
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textPainter.layout();
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@@ -278,14 +389,24 @@ class _CalibrationPainter extends CustomPainter {
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// Draw label on the right side of each zone
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final labelY = center.dy - textPainter.height / 2;
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||||
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(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);
|
||||
canvas.drawLine(
|
||||
Offset(center.dx - 20, center.dy),
|
||||
Offset(center.dx - 8, center.dy),
|
||||
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 actualRadius = baseRadius * outerRingRadius;
|
||||
final actualHandleX = center.dx + actualRadius;
|
||||
final actualHandleX = center.dx + baseRadius;
|
||||
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;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -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>(
|
||||
create: (_) => SessionRepository(),
|
||||
),
|
||||
Provider<SessionRepository>(create: (_) => SessionRepository()),
|
||||
],
|
||||
child: const BullyApp(),
|
||||
),
|
||||
|
||||
@@ -676,4 +676,399 @@ class DistortionCorrectionService {
|
||||
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);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -153,7 +153,7 @@ class OpenCVImpactDetectionService {
|
||||
);
|
||||
|
||||
final contours = contoursResult.$1;
|
||||
// hierarchy is item2
|
||||
// hierarchy is $2
|
||||
|
||||
for (int i = 0; i < contours.length; i++) {
|
||||
final contour = contours[i];
|
||||
|
||||
@@ -45,14 +45,14 @@ class OpenCVTargetService {
|
||||
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
|
||||
1, // dp
|
||||
(img.rows / 16)
|
||||
.toDouble(), // minDist decreased to allow more rings in same general area
|
||||
param1: 100, // 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
|
||||
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.
|
||||
@@ -79,8 +79,8 @@ class OpenCVTargetService {
|
||||
cv.HOUGH_GRADIENT,
|
||||
1,
|
||||
(img.rows / 8).toDouble(),
|
||||
param1: 50,
|
||||
param2: 20,
|
||||
param1: 100,
|
||||
param2: 40,
|
||||
minRadius: img.cols ~/ 20,
|
||||
maxRadius: img.cols ~/ 2,
|
||||
);
|
||||
@@ -137,18 +137,22 @@ class OpenCVTargetService {
|
||||
for (final circle in detected) {
|
||||
bool added = false;
|
||||
for (final cluster in clusters) {
|
||||
// Check distance to cluster center (average of existing)
|
||||
double clusterX = 0;
|
||||
double clusterY = 0;
|
||||
// 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) {
|
||||
clusterX += c.x;
|
||||
clusterY += c.y;
|
||||
if (c.r < minRadiusInCluster) {
|
||||
minRadiusInCluster = c.r;
|
||||
clusterCenterX = c.x;
|
||||
clusterCenterY = c.y;
|
||||
}
|
||||
}
|
||||
clusterX /= cluster.length;
|
||||
clusterY /= cluster.length;
|
||||
|
||||
final dist = math.sqrt(
|
||||
math.pow(circle.x - clusterX, 2) + math.pow(circle.y - clusterY, 2),
|
||||
math.pow(circle.x - clusterCenterX, 2) +
|
||||
math.pow(circle.y - clusterCenterY, 2),
|
||||
);
|
||||
|
||||
if (dist < tolerance) {
|
||||
@@ -171,10 +175,10 @@ class OpenCVTargetService {
|
||||
|
||||
for (final cluster in clusters) {
|
||||
// Score calculation
|
||||
// Base score = number of circles * 10
|
||||
double score = cluster.length * 10.0;
|
||||
// Base score = number of circles squared (heavily favor concentric rings)
|
||||
double score = math.pow(cluster.length, 2).toDouble() * 10.0;
|
||||
|
||||
// Penalize distance from center
|
||||
// Small penalty for distance from center (only as tie-breaker)
|
||||
double cx = 0, cy = 0;
|
||||
for (final c in cluster) {
|
||||
cx += c.x;
|
||||
@@ -188,7 +192,8 @@ class OpenCVTargetService {
|
||||
);
|
||||
final relDist = distFromCenter / math.min(width, height);
|
||||
|
||||
score -= relDist * 5.0; // Moderate penalty for off-center
|
||||
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?)
|
||||
|
||||
@@ -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 'opencv_impact_detection_service.dart' show OpenCVDetectionSettings, OpenCVDetectedImpact;
|
||||
export 'image_processing_service.dart'
|
||||
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(),
|
||||
_opencvService = opencvService ?? OpenCVImpactDetectionService();
|
||||
YOLOImpactDetectionService? yoloService,
|
||||
}) : _imageProcessingService =
|
||||
imageProcessingService ?? ImageProcessingService(),
|
||||
_opencvService = opencvService ?? OpenCVImpactDetectionService(),
|
||||
_yoloService = yoloService ?? YOLOImpactDetectionService();
|
||||
|
||||
/// Detect target and impacts from an image file
|
||||
TargetDetectionResult detectTarget(
|
||||
String imagePath,
|
||||
TargetType targetType,
|
||||
) {
|
||||
TargetDetectionResult detectTarget(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 < 0.15) return 4; // Body
|
||||
if (dy < 0.35) return 3; // Lower body
|
||||
if (dy < 0.0) return 5; // Center mass (upper body)
|
||||
if (dy < 0.15) return 4; // 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
|
||||
.map((r) => (x: r.x, y: r.y))
|
||||
.toList();
|
||||
final refPoints = references.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 [];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
174
lib/services/yolo_impact_detection_service.dart
Normal file
174
lib/services/yolo_impact_detection_service.dart
Normal file
@@ -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,
|
||||
});
|
||||
}
|
||||
@@ -7,6 +7,7 @@ list(APPEND FLUTTER_PLUGIN_LIST
|
||||
)
|
||||
|
||||
list(APPEND FLUTTER_FFI_PLUGIN_LIST
|
||||
tflite_flutter
|
||||
)
|
||||
|
||||
set(PLUGIN_BUNDLED_LIBRARIES)
|
||||
|
||||
16
pubspec.lock
16
pubspec.lock
@@ -536,6 +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
|
||||
@@ -653,6 +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:
|
||||
|
||||
@@ -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
|
||||
|
||||
12
tests/find_homography_test.dart
Normal file
12
tests/find_homography_test.dart
Normal file
@@ -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);
|
||||
}
|
||||
7
tests/opencv_quad_test.dart
Normal file
7
tests/opencv_quad_test.dart
Normal file
@@ -0,0 +1,7 @@
|
||||
import 'package:opencv_dart/opencv_dart.dart' as cv;
|
||||
|
||||
void main() {
|
||||
print(cv.approxPolyDP);
|
||||
print(cv.arcLength);
|
||||
print(cv.contourArea);
|
||||
}
|
||||
5
tests/test_homography.dart
Normal file
5
tests/test_homography.dart
Normal file
@@ -0,0 +1,5 @@
|
||||
import 'package:opencv_dart/opencv_dart.dart' as cv;
|
||||
|
||||
void main() {
|
||||
print(cv.findHomography);
|
||||
}
|
||||
@@ -7,6 +7,7 @@ list(APPEND FLUTTER_PLUGIN_LIST
|
||||
)
|
||||
|
||||
list(APPEND FLUTTER_FFI_PLUGIN_LIST
|
||||
tflite_flutter
|
||||
)
|
||||
|
||||
set(PLUGIN_BUNDLED_LIBRARIES)
|
||||
|
||||
Reference in New Issue
Block a user