diff --git a/apps/traincascade/features.cpp b/apps/traincascade/features.cpp index 8ecdfcca90..effa4dcc56 100644 --- a/apps/traincascade/features.cpp +++ b/apps/traincascade/features.cpp @@ -24,7 +24,7 @@ CvParams::CvParams() : name( "params" ) {} void CvParams::printDefaults() const { cout << "--" << name << "--" << endl; } void CvParams::printAttrs() const {} -bool CvParams::scanAttr( const String prmName, const String val ) { return false; } +bool CvParams::scanAttr( const String, const String ) { return false; } //---------------------------- FeatureParams -------------------------------------- diff --git a/modules/contrib/include/opencv2/contrib/hybridtracker.hpp b/modules/contrib/include/opencv2/contrib/hybridtracker.hpp index 418a7b8dcd..3a1f722d70 100644 --- a/modules/contrib/include/opencv2/contrib/hybridtracker.hpp +++ b/modules/contrib/include/opencv2/contrib/hybridtracker.hpp @@ -59,151 +59,151 @@ namespace cv // To add Kalman filter struct CV_EXPORTS CvMotionModel { - enum {LOW_PASS_FILTER = 0, KALMAN_FILTER = 1, EM = 2}; + enum {LOW_PASS_FILTER = 0, KALMAN_FILTER = 1, EM = 2}; - CvMotionModel() - { - } + CvMotionModel() + { + } - float low_pass_gain; // low pass gain + float low_pass_gain; // low pass gain }; // Mean Shift Tracker parameters for specifying use of HSV channel and CamShift parameters. struct CV_EXPORTS CvMeanShiftTrackerParams { - enum { H = 0, HS = 1, HSV = 2 }; - CvMeanShiftTrackerParams(int tracking_type = CvMeanShiftTrackerParams::HS, - CvTermCriteria term_crit = CvTermCriteria()); - - int tracking_type; - vector h_range; - vector s_range; - vector v_range; - CvTermCriteria term_crit; + enum { H = 0, HS = 1, HSV = 2 }; + CvMeanShiftTrackerParams(int tracking_type = CvMeanShiftTrackerParams::HS, + CvTermCriteria term_crit = CvTermCriteria()); + + int tracking_type; + vector h_range; + vector s_range; + vector v_range; + CvTermCriteria term_crit; }; // Feature tracking parameters struct CV_EXPORTS CvFeatureTrackerParams { - enum { SIFT = 0, SURF = 1, OPTICAL_FLOW = 2 }; - CvFeatureTrackerParams(int featureType = 0, int windowSize = 0) - { - featureType = 0; - windowSize = 0; - } - - int feature_type; // Feature type to use - int window_size; // Window size in pixels around which to search for new window + enum { SIFT = 0, SURF = 1, OPTICAL_FLOW = 2 }; + CvFeatureTrackerParams(int featureType = 0, int windowSize = 0) + { + feature_type = featureType; + window_size = windowSize; + } + + int feature_type; // Feature type to use + int window_size; // Window size in pixels around which to search for new window }; // Hybrid Tracking parameters for specifying weights of individual trackers and motion model. struct CV_EXPORTS CvHybridTrackerParams { - CvHybridTrackerParams(float ft_tracker_weight = 0.5, float ms_tracker_weight = 0.5, - CvFeatureTrackerParams ft_params = CvFeatureTrackerParams(), - CvMeanShiftTrackerParams ms_params = CvMeanShiftTrackerParams(), - CvMotionModel model = CvMotionModel()); - - float ft_tracker_weight; - float ms_tracker_weight; - CvFeatureTrackerParams ft_params; - CvMeanShiftTrackerParams ms_params; - int motion_model; - float low_pass_gain; + CvHybridTrackerParams(float ft_tracker_weight = 0.5, float ms_tracker_weight = 0.5, + CvFeatureTrackerParams ft_params = CvFeatureTrackerParams(), + CvMeanShiftTrackerParams ms_params = CvMeanShiftTrackerParams(), + CvMotionModel model = CvMotionModel()); + + float ft_tracker_weight; + float ms_tracker_weight; + CvFeatureTrackerParams ft_params; + CvMeanShiftTrackerParams ms_params; + int motion_model; + float low_pass_gain; }; // Performs Camshift using parameters from MeanShiftTrackerParams class CV_EXPORTS CvMeanShiftTracker { private: - Mat hsv, hue; - Mat backproj; - Mat mask, maskroi; - MatND hist; - Rect prev_trackwindow; - RotatedRect prev_trackbox; - Point2f prev_center; + Mat hsv, hue; + Mat backproj; + Mat mask, maskroi; + MatND hist; + Rect prev_trackwindow; + RotatedRect prev_trackbox; + Point2f prev_center; public: - CvMeanShiftTrackerParams params; - - CvMeanShiftTracker(); - explicit CvMeanShiftTracker(CvMeanShiftTrackerParams _params); - ~CvMeanShiftTracker(); - void newTrackingWindow(Mat image, Rect selection); - RotatedRect updateTrackingWindow(Mat image); - Mat getHistogramProjection(int type); - void setTrackingWindow(Rect _window); - Rect getTrackingWindow(); - RotatedRect getTrackingEllipse(); - Point2f getTrackingCenter(); + CvMeanShiftTrackerParams params; + + CvMeanShiftTracker(); + explicit CvMeanShiftTracker(CvMeanShiftTrackerParams _params); + ~CvMeanShiftTracker(); + void newTrackingWindow(Mat image, Rect selection); + RotatedRect updateTrackingWindow(Mat image); + Mat getHistogramProjection(int type); + void setTrackingWindow(Rect _window); + Rect getTrackingWindow(); + RotatedRect getTrackingEllipse(); + Point2f getTrackingCenter(); }; // Performs SIFT/SURF feature tracking using parameters from FeatureTrackerParams class CV_EXPORTS CvFeatureTracker { private: - Ptr dd; - Ptr matcher; - vector matches; + Ptr dd; + Ptr matcher; + vector matches; - Mat prev_image; - Mat prev_image_bw; - Rect prev_trackwindow; - Point2d prev_center; + Mat prev_image; + Mat prev_image_bw; + Rect prev_trackwindow; + Point2d prev_center; - int ittr; - vector features[2]; + int ittr; + vector features[2]; public: - Mat disp_matches; - CvFeatureTrackerParams params; - - CvFeatureTracker(); - explicit CvFeatureTracker(CvFeatureTrackerParams params); - ~CvFeatureTracker(); - void newTrackingWindow(Mat image, Rect selection); - Rect updateTrackingWindow(Mat image); - Rect updateTrackingWindowWithSIFT(Mat image); - Rect updateTrackingWindowWithFlow(Mat image); - void setTrackingWindow(Rect _window); - Rect getTrackingWindow(); - Point2f getTrackingCenter(); + Mat disp_matches; + CvFeatureTrackerParams params; + + CvFeatureTracker(); + explicit CvFeatureTracker(CvFeatureTrackerParams params); + ~CvFeatureTracker(); + void newTrackingWindow(Mat image, Rect selection); + Rect updateTrackingWindow(Mat image); + Rect updateTrackingWindowWithSIFT(Mat image); + Rect updateTrackingWindowWithFlow(Mat image); + void setTrackingWindow(Rect _window); + Rect getTrackingWindow(); + Point2f getTrackingCenter(); }; // Performs Hybrid Tracking and combines individual trackers using EM or filters class CV_EXPORTS CvHybridTracker { private: - CvMeanShiftTracker* mstracker; - CvFeatureTracker* fttracker; + CvMeanShiftTracker* mstracker; + CvFeatureTracker* fttracker; - CvMat* samples; - CvMat* labels; + CvMat* samples; + CvMat* labels; - Rect prev_window; - Point2f prev_center; - Mat prev_proj; - RotatedRect trackbox; + Rect prev_window; + Point2f prev_center; + Mat prev_proj; + RotatedRect trackbox; - int ittr; - Point2f curr_center; + int ittr; + Point2f curr_center; - inline float getL2Norm(Point2f p1, Point2f p2); - Mat getDistanceProjection(Mat image, Point2f center); - Mat getGaussianProjection(Mat image, int ksize, double sigma, Point2f center); - void updateTrackerWithEM(Mat image); - void updateTrackerWithLowPassFilter(Mat image); + inline float getL2Norm(Point2f p1, Point2f p2); + Mat getDistanceProjection(Mat image, Point2f center); + Mat getGaussianProjection(Mat image, int ksize, double sigma, Point2f center); + void updateTrackerWithEM(Mat image); + void updateTrackerWithLowPassFilter(Mat image); public: - CvHybridTrackerParams params; - CvHybridTracker(); - explicit CvHybridTracker(CvHybridTrackerParams params); - ~CvHybridTracker(); - - void newTracker(Mat image, Rect selection); - void updateTracker(Mat image); - Rect getTrackingWindow(); + CvHybridTrackerParams params; + CvHybridTracker(); + explicit CvHybridTracker(CvHybridTrackerParams params); + ~CvHybridTracker(); + + void newTracker(Mat image, Rect selection); + void updateTracker(Mat image); + Rect getTrackingWindow(); }; typedef CvMotionModel MotionModel; diff --git a/modules/flann/include/opencv2/flann/any.h b/modules/flann/include/opencv2/flann/any.h index e1c78b6f35..dc0b9481a2 100644 --- a/modules/flann/include/opencv2/flann/any.h +++ b/modules/flann/include/opencv2/flann/any.h @@ -12,6 +12,7 @@ * Adapted for FLANN by Marius Muja */ +#include "defines.h" #include #include #include @@ -95,6 +96,16 @@ struct big_any_policy : typed_base_any_policy virtual void print(std::ostream& out, void* const* src) { out << *reinterpret_cast(*src); } }; +template<> inline void big_any_policy::print(std::ostream& out, void* const* src) +{ + out << int(*reinterpret_cast(*src)); +} + +template<> inline void big_any_policy::print(std::ostream& out, void* const* src) +{ + out << int(*reinterpret_cast(*src)); +} + template struct choose_policy { diff --git a/modules/flann/src/flann.cpp b/modules/flann/src/flann.cpp index 36ee6694a3..fa1fdaf418 100644 --- a/modules/flann/src/flann.cpp +++ b/modules/flann/src/flann.cpp @@ -36,7 +36,7 @@ namespace cvflann */ flann_distance_t flann_distance_type_ = FLANN_DIST_L2; flann_distance_t flann_distance_type() { return flann_distance_type_; } - + /** * Set distance type to used * \deprecated @@ -52,6 +52,6 @@ namespace cvflann } flann_distance_type_ = distance_type; } - + void dummyfunc() {} } \ No newline at end of file diff --git a/modules/flann/src/precomp.hpp b/modules/flann/src/precomp.hpp index 88df36b455..72731af92f 100644 --- a/modules/flann/src/precomp.hpp +++ b/modules/flann/src/precomp.hpp @@ -1,7 +1,3 @@ -#ifdef __GNUC__ -# pragma GCC diagnostic ignored "-Wsign-promo" -#endif - #ifndef _OPENCV_FLANN_PRECOMP_HPP_ #define _OPENCV_FLANN_PRECOMP_HPP_ diff --git a/modules/highgui/src/grfmt_jpeg.cpp b/modules/highgui/src/grfmt_jpeg.cpp index 24318cad85..5b4c9e83d4 100644 --- a/modules/highgui/src/grfmt_jpeg.cpp +++ b/modules/highgui/src/grfmt_jpeg.cpp @@ -542,8 +542,6 @@ bool JpegEncoder::write( const Mat& img, const vector& params ) }; bool result = false; fileWrapper fw; - int _channels = img.channels(); - int channels = _channels > 1 ? 3 : 1; int width = img.cols, height = img.rows; vector out_buf(1 << 12); @@ -580,6 +578,9 @@ bool JpegEncoder::write( const Mat& img, const vector& params ) { cinfo.image_width = width; cinfo.image_height = height; + + int _channels = img.channels(); + int channels = _channels > 1 ? 3 : 1; cinfo.input_components = channels; cinfo.in_color_space = channels > 1 ? JCS_RGB : JCS_GRAYSCALE; diff --git a/modules/ml/test/test_mltests2.cpp b/modules/ml/test/test_mltests2.cpp index a5dfbe8553..80776b4ced 100644 --- a/modules/ml/test/test_mltests2.cpp +++ b/modules/ml/test/test_mltests2.cpp @@ -52,7 +52,7 @@ void nbayes_check_data( CvMLData* _data ) CV_Error( CV_StsBadArg, "missing values are not supported" ); const CvMat* var_types = _data->get_var_types(); bool is_classifier = var_types->data.ptr[var_types->cols-1] == CV_VAR_CATEGORICAL; - if( ( fabs( cvNorm( var_types, 0, CV_L1 ) - + if( ( fabs( cvNorm( var_types, 0, CV_L1 ) - (var_types->rows + var_types->cols - 2)*CV_VAR_ORDERED - CV_VAR_CATEGORICAL ) > FLT_EPSILON ) || !is_classifier ) CV_Error( CV_StsBadArg, "incorrect types of predictors or responses" ); @@ -89,7 +89,7 @@ float nbayes_calc_error( CvNormalBayesClassifier* nbayes, CvMLData* _data, int t { CvMat sample; int si = sidx ? sidx[i] : i; - cvGetRow( values, &sample, si ); + cvGetRow( values, &sample, si ); float r = (float)nbayes->predict( &sample, 0 ); if( pred_resp ) pred_resp[i] = r; @@ -151,7 +151,7 @@ float knearest_calc_error( CvKNearest* knearest, CvMLData* _data, int k, int typ { CvMat sample; int si = sidx ? sidx[i] : i; - cvGetRow( &predictors, &sample, si ); + cvGetRow( &predictors, &sample, si ); float r = knearest->find_nearest( &sample, k ); if( pred_resp ) pred_resp[i] = r; @@ -166,14 +166,14 @@ float knearest_calc_error( CvKNearest* knearest, CvMLData* _data, int k, int typ { CvMat sample; int si = sidx ? sidx[i] : i; - cvGetRow( &predictors, &sample, si ); + cvGetRow( &predictors, &sample, si ); float r = knearest->find_nearest( &sample, k ); if( pred_resp ) pred_resp[i] = r; float d = r - response->data.fl[si*r_step]; err += d*d; } - err = sample_count ? err / (float)sample_count : -FLT_MAX; + err = sample_count ? err / (float)sample_count : -FLT_MAX; } return err; } @@ -239,7 +239,7 @@ bool svm_train_auto( CvSVM* svm, CvMLData* _data, CvSVMParams _params, const CvMat* _responses = _data->get_responses(); const CvMat* _var_idx = _data->get_var_idx(); const CvMat* _sample_idx = _data->get_train_sample_idx(); - return svm->train_auto( _train_data, _responses, _var_idx, + return svm->train_auto( _train_data, _responses, _var_idx, _sample_idx, _params, k_fold, C_grid, gamma_grid, p_grid, nu_grid, coef_grid, degree_grid ); } float svm_calc_error( CvSVM* svm, CvMLData* _data, int type, vector *resp ) @@ -268,7 +268,7 @@ float svm_calc_error( CvSVM* svm, CvMLData* _data, int type, vector *resp { CvMat sample; int si = sidx ? sidx[i] : i; - cvGetRow( values, &sample, si ); + cvGetRow( values, &sample, si ); float r = svm->predict( &sample ); if( pred_resp ) pred_resp[i] = r; @@ -290,7 +290,7 @@ float svm_calc_error( CvSVM* svm, CvMLData* _data, int type, vector *resp float d = r - response->data.fl[si*r_step]; err += d*d; } - err = sample_count ? err / (float)sample_count : -FLT_MAX; + err = sample_count ? err / (float)sample_count : -FLT_MAX; } return err; } @@ -395,7 +395,7 @@ float ann_calc_error( CvANN_MLP* ann, CvMLData* _data, map& cls_map, i { CvMat sample; int si = sidx ? sidx[i] : i; - cvGetRow( &predictors, &sample, si ); + cvGetRow( &predictors, &sample, si ); ann->predict( &sample, &_output ); CvPoint best_cls = {0,0}; cvMinMaxLoc( &_output, 0, 0, 0, &best_cls, 0 ); @@ -417,7 +417,7 @@ int str_to_boost_type( string& str ) if ( !str.compare("DISCRETE") ) return CvBoost::DISCRETE; if ( !str.compare("REAL") ) - return CvBoost::REAL; + return CvBoost::REAL; if ( !str.compare("LOGIT") ) return CvBoost::LOGIT; if ( !str.compare("GENTLE") ) @@ -480,7 +480,7 @@ CV_MLBaseTest::~CV_MLBaseTest() validationFS.release(); if( nbayes ) delete nbayes; - if( knearest ) + if( knearest ) delete knearest; if( svm ) delete svm; @@ -519,15 +519,14 @@ int CV_MLBaseTest::read_params( CvFileStorage* _fs ) return cvtest::TS::OK;; } -void CV_MLBaseTest::run( int start_from ) +void CV_MLBaseTest::run( int ) { string filename = ts->get_data_path(); filename += get_validation_filename(); validationFS.open( filename, FileStorage::READ ); read_params( *validationFS ); - + int code = cvtest::TS::OK; - start_from = 0; for (int i = 0; i < test_case_count; i++) { int temp_code = run_test_case( i ); @@ -594,7 +593,7 @@ string& CV_MLBaseTest::get_validation_filename() int CV_MLBaseTest::train( int testCaseIdx ) { bool is_trained = false; - FileNode modelParamsNode = + FileNode modelParamsNode = validationFS.getFirstTopLevelNode()["validation"][modelName][dataSetNames[testCaseIdx]]["model_params"]; if( !modelName.compare(CV_NBAYES) ) @@ -651,7 +650,7 @@ int CV_MLBaseTest::train( int testCaseIdx ) modelParamsNode["max_categories"] >> MAX_CATEGORIES; modelParamsNode["cv_folds"] >> CV_FOLDS; modelParamsNode["is_pruned"] >> IS_PRUNED; - is_trained = dtree->train( &data, + is_trained = dtree->train( &data, CvDTreeParams(MAX_DEPTH, MIN_SAMPLE_COUNT, REG_ACCURACY, USE_SURROGATE, MAX_CATEGORIES, CV_FOLDS, false, IS_PRUNED, 0 )) != 0; } @@ -683,7 +682,7 @@ int CV_MLBaseTest::train( int testCaseIdx ) modelParamsNode["is_pruned"] >> IS_PRUNED; modelParamsNode["nactive_vars"] >> NACTIVE_VARS; modelParamsNode["max_trees_num"] >> MAX_TREES_NUM; - is_trained = rtrees->train( &data, CvRTParams( MAX_DEPTH, MIN_SAMPLE_COUNT, REG_ACCURACY, + is_trained = rtrees->train( &data, CvRTParams( MAX_DEPTH, MIN_SAMPLE_COUNT, REG_ACCURACY, USE_SURROGATE, MAX_CATEGORIES, 0, true, // (calc_var_importance == true) <=> RF processes variable importance NACTIVE_VARS, MAX_TREES_NUM, OOB_EPS, CV_TERMCRIT_ITER)) != 0; } @@ -713,7 +712,7 @@ int CV_MLBaseTest::train( int testCaseIdx ) return cvtest::TS::OK; } -float CV_MLBaseTest::get_error( int testCaseIdx, int type, vector *resp ) +float CV_MLBaseTest::get_error( int /*testCaseIdx*/, int type, vector *resp ) { float err = 0; if( !modelName.compare(CV_NBAYES) ) @@ -721,8 +720,8 @@ float CV_MLBaseTest::get_error( int testCaseIdx, int type, vector *resp ) else if( !modelName.compare(CV_KNEAREST) ) { assert( 0 ); - testCaseIdx = 0; - /*int k = 2; + /*testCaseIdx = 0; + int k = 2; validationFS.getFirstTopLevelNode()["validation"][modelName][dataSetNames[testCaseIdx]]["model_params"]["k"] >> k; err = knearest->calc_error( &data, k, type, resp );*/ } diff --git a/modules/python/src2/cv2.cpp b/modules/python/src2/cv2.cpp index ebef099e69..4924e9b982 100644 --- a/modules/python/src2/cv2.cpp +++ b/modules/python/src2/cv2.cpp @@ -181,7 +181,7 @@ public: datastart = data = (uchar*)PyArray_DATA(o); } - void deallocate(int* refcount, uchar* datastart, uchar* data) + void deallocate(int* refcount, uchar*, uchar*) { PyEnsureGIL gil; if( !refcount ) @@ -349,6 +349,7 @@ static PyObject* pyopencv_from(bool value) static bool pyopencv_to(PyObject* obj, bool& value, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; int _val = PyObject_IsTrue(obj); @@ -365,6 +366,7 @@ static PyObject* pyopencv_from(size_t value) static bool pyopencv_to(PyObject* obj, size_t& value, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; value = (int)PyLong_AsUnsignedLong(obj); @@ -376,8 +378,19 @@ static PyObject* pyopencv_from(int value) return PyInt_FromLong(value); } +static PyObject* pyopencv_from(cvflann_flann_algorithm_t value) +{ + return PyInt_FromLong(int(value)); +} + +static PyObject* pyopencv_from(cvflann_flann_distance_t value) +{ + return PyInt_FromLong(int(value)); +} + static bool pyopencv_to(PyObject* obj, int& value, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; value = (int)PyInt_AsLong(obj); @@ -391,6 +404,7 @@ static PyObject* pyopencv_from(uchar value) static bool pyopencv_to(PyObject* obj, uchar& value, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; int ivalue = (int)PyInt_AsLong(obj); @@ -405,6 +419,7 @@ static PyObject* pyopencv_from(double value) static bool pyopencv_to(PyObject* obj, double& value, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; if(PyInt_CheckExact(obj)) @@ -421,6 +436,7 @@ static PyObject* pyopencv_from(float value) static bool pyopencv_to(PyObject* obj, float& value, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; if(PyInt_CheckExact(obj)) @@ -442,6 +458,7 @@ static PyObject* pyopencv_from(const string& value) static bool pyopencv_to(PyObject* obj, string& value, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; char* str = PyString_AsString(obj); @@ -453,6 +470,7 @@ static bool pyopencv_to(PyObject* obj, string& value, const char* name = " 0; @@ -465,6 +483,7 @@ static inline PyObject* pyopencv_from(const Size& sz) static inline bool pyopencv_to(PyObject* obj, Rect& r, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; return PyArg_ParseTuple(obj, "iiii", &r.x, &r.y, &r.width, &r.height) > 0; @@ -477,6 +496,7 @@ static inline PyObject* pyopencv_from(const Rect& r) static inline bool pyopencv_to(PyObject* obj, Range& r, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; if(PyObject_Size(obj) == 0) @@ -494,6 +514,7 @@ static inline PyObject* pyopencv_from(const Range& r) static inline bool pyopencv_to(PyObject* obj, CvSlice& r, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; if(PyObject_Size(obj) == 0) @@ -511,6 +532,7 @@ static inline PyObject* pyopencv_from(const CvSlice& r) static inline bool pyopencv_to(PyObject* obj, Point& p, const char* name = "") { + (void)name; if(!obj || obj == Py_None) return true; if(PyComplex_CheckExact(obj)) @@ -525,6 +547,7 @@ static inline bool pyopencv_to(PyObject* obj, Point& p, const char* name = " 0; @@ -792,6 +816,7 @@ template<> struct pyopencvVecConverter static inline bool pyopencv_to(PyObject *obj, CvTermCriteria& dst, const char *name="") { + (void)name; if(!obj) return true; return PyArg_ParseTuple(obj, "iid", &dst.type, &dst.max_iter, &dst.epsilon) > 0; @@ -804,6 +829,7 @@ static inline PyObject* pyopencv_from(const CvTermCriteria& src) static inline bool pyopencv_to(PyObject *obj, TermCriteria& dst, const char *name="") { + (void)name; if(!obj) return true; return PyArg_ParseTuple(obj, "iid", &dst.type, &dst.maxCount, &dst.epsilon) > 0; @@ -816,6 +842,7 @@ static inline PyObject* pyopencv_from(const TermCriteria& src) static inline bool pyopencv_to(PyObject *obj, RotatedRect& dst, const char *name="") { + (void)name; if(!obj) return true; return PyArg_ParseTuple(obj, "(ff)(ff)f", &dst.center.x, &dst.center.y, &dst.size.width, &dst.size.height, &dst.angle) > 0; @@ -847,6 +874,7 @@ static inline PyObject* pyopencv_from(const CvDTreeNode* node) static bool pyopencv_to(PyObject *o, cv::flann::IndexParams& p, const char *name="") { + (void)name; bool ok = false; PyObject* keys = PyObject_CallMethod(o,(char*)"keys",0); PyObject* values = PyObject_CallMethod(o,(char*)"values",0); @@ -927,7 +955,7 @@ static void OnMouse(int event, int x, int y, int flags, void* param) PyGILState_Release(gstate); } -static PyObject *pycvSetMouseCallback(PyObject *self, PyObject *args, PyObject *kw) +static PyObject *pycvSetMouseCallback(PyObject*, PyObject *args, PyObject *kw) { const char *keywords[] = { "window_name", "on_mouse", "param", NULL }; char* name; @@ -961,7 +989,7 @@ static void OnChange(int pos, void *param) PyGILState_Release(gstate); } -static PyObject *pycvCreateTrackbar(PyObject *self, PyObject *args) +static PyObject *pycvCreateTrackbar(PyObject*, PyObject *args) { PyObject *on_change; char* trackbar_name; @@ -983,6 +1011,11 @@ static PyObject *pycvCreateTrackbar(PyObject *self, PyObject *args) #define MKTYPE2(NAME) pyopencv_##NAME##_specials(); if (!to_ok(&pyopencv_##NAME##_Type)) return +#ifdef __GNUC__ +# pragma GCC diagnostic ignored "-Wunused-parameter" +# pragma GCC diagnostic ignored "-Wmissing-field-initializers" +#endif + #include "pyopencv_generated_types.h" #include "pyopencv_generated_funcs.h" diff --git a/modules/stitching/perf/perf_stich.cpp b/modules/stitching/perf/perf_stich.cpp index c7c3f62c51..bf62f86805 100644 --- a/modules/stitching/perf/perf_stich.cpp +++ b/modules/stitching/perf/perf_stich.cpp @@ -1,9 +1,4 @@ #include "perf_precomp.hpp" - -#ifdef __GNUC__ -# pragma GCC diagnostic ignored "-Wsign-promo" -#endif - #include "opencv2/highgui/highgui.hpp" #include "opencv2/core/internal.hpp" #include "opencv2/flann/flann.hpp" diff --git a/samples/gpu/cascadeclassifier_nvidia_api.cpp b/samples/gpu/cascadeclassifier_nvidia_api.cpp index bc12bf52de..349476dbc4 100644 --- a/samples/gpu/cascadeclassifier_nvidia_api.cpp +++ b/samples/gpu/cascadeclassifier_nvidia_api.cpp @@ -18,7 +18,7 @@ using namespace cv; #if !defined(HAVE_CUDA) -int main( int argc, const char** argv ) +int main( int, const char** ) { cout << "Please compile the library with CUDA support" << endl; return -1; diff --git a/samples/gpu/opticalflow_nvidia_api.cpp b/samples/gpu/opticalflow_nvidia_api.cpp index e40f059b5f..f48b13a3ed 100644 --- a/samples/gpu/opticalflow_nvidia_api.cpp +++ b/samples/gpu/opticalflow_nvidia_api.cpp @@ -20,7 +20,7 @@ #endif #if !defined(HAVE_CUDA) -int main( int argc, const char** argv ) +int main( int, const char** ) { std::cout << "Please compile the library with CUDA support" << std::endl; return -1;