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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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Alexander Alekhin
2022-02-19 21:04:35 +00:00
parent b9e5256cf9 2c83cfc14c
commit 5a86592e93
6 changed files with 57 additions and 19 deletions
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modules/objdetect/include/opencv2/objdetect.hpp
+13 -9
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@@ -383,7 +383,7 @@ public:
};
enum DescriptorStorageFormat { DESCR_FORMAT_COL_BY_COL, DESCR_FORMAT_ROW_BY_ROW };
/**@brief Creates the HOG descriptor and detector with default params.
/**@brief Creates the HOG descriptor and detector with default parameters.
aqual to HOGDescriptor(Size(64,128), Size(16,16), Size(8,8), Size(8,8), 9 )
*/
@@ -419,6 +419,8 @@ public:
{}
/** @overload
Creates the HOG descriptor and detector and loads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file.
@param filename The file name containing HOGDescriptor properties and coefficients for the linear SVM classifier.
*/
CV_WRAP HOGDescriptor(const String& filename)
@@ -457,19 +459,19 @@ public:
*/
CV_WRAP virtual void setSVMDetector(InputArray svmdetector);
/** @brief Reads HOGDescriptor parameters from a cv::FileNode.
/** @brief Reads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file node.
@param fn File node
*/
virtual bool read(FileNode& fn);
/** @brief Stores HOGDescriptor parameters in a cv::FileStorage.
/** @brief Stores HOGDescriptor parameters and coefficients for the linear SVM classifier in a file storage.
@param fs File storage
@param objname Object name
*/
virtual void write(FileStorage& fs, const String& objname) const;
/** @brief loads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file.
@param filename Path of the file to read.
/** @brief loads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file
@param filename Name of the file to read.
@param objname The optional name of the node to read (if empty, the first top-level node will be used).
*/
CV_WRAP virtual bool load(const String& filename, const String& objname = String());
@@ -542,13 +544,14 @@ public:
@param winStride Window stride. It must be a multiple of block stride.
@param padding Padding
@param scale Coefficient of the detection window increase.
@param finalThreshold Final threshold
@param groupThreshold Coefficient to regulate the similarity threshold. When detected, some objects can be covered
by many rectangles. 0 means not to perform grouping.
@param useMeanshiftGrouping indicates grouping algorithm
*/
CV_WRAP virtual void detectMultiScale(InputArray img, CV_OUT std::vector<Rect>& foundLocations,
CV_OUT std::vector<double>& foundWeights, double hitThreshold = 0,
Size winStride = Size(), Size padding = Size(), double scale = 1.05,
double finalThreshold = 2.0,bool useMeanshiftGrouping = false) const;
double groupThreshold = 2.0, bool useMeanshiftGrouping = false) const;
/** @brief Detects objects of different sizes in the input image. The detected objects are returned as a list
of rectangles.
@@ -560,13 +563,14 @@ public:
@param winStride Window stride. It must be a multiple of block stride.
@param padding Padding
@param scale Coefficient of the detection window increase.
@param finalThreshold Final threshold
@param groupThreshold Coefficient to regulate the similarity threshold. When detected, some objects can be covered
by many rectangles. 0 means not to perform grouping.
@param useMeanshiftGrouping indicates grouping algorithm
*/
virtual void detectMultiScale(InputArray img, CV_OUT std::vector<Rect>& foundLocations,
double hitThreshold = 0, Size winStride = Size(),
Size padding = Size(), double scale = 1.05,
double finalThreshold = 2.0, bool useMeanshiftGrouping = false) const;
double groupThreshold = 2.0, bool useMeanshiftGrouping = false) const;
/** @brief Computes gradients and quantized gradient orientations.
@param img Matrix contains the image to be computed