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Merge branch 'master' into fix_warning_win_ci
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fspindle authored Oct 27, 2023
2 parents 44ad9cf + af97521 commit 3022e67
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2 changes: 1 addition & 1 deletion cmake/templates/vpConfig.h.in
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Expand Up @@ -167,7 +167,7 @@
// OpenCV version in hexadecimal (for example 2.1.0 gives 0x020100).
#ifdef VISP_HAVE_OPENCV
# define VISP_HAVE_OPENCV_VERSION ${VISP_HAVE_OPENCV_VERSION}
# include <opencv2/opencv.hpp>
# include <opencv2/opencv_modules.hpp>
#endif

// For compat with previous releases
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118 changes: 99 additions & 19 deletions modules/core/include/visp3/core/vpCannyEdgeDetection.h
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Expand Up @@ -56,23 +56,34 @@ class VISP_EXPORT vpCannyEdgeDetection
ON_CHECK /*!< This pixel is currently tested to know if it is linked to a strong edge point.*/
} EdgeType;

// Filtering + gradient methods choice
vpImageFilter::vpCannyFilteringAndGradientType m_filteringAndGradientType; /*!< Choice of the filter and
gradient operator to apply before the edge detection step*/

// // Gaussian smoothing attributes
int m_gaussianKernelSize; /*!< Size of the Gaussian filter kernel used to smooth the input image. Must be an odd number.*/
float m_gaussianStdev; /*!< Standard deviation of the Gaussian filter.*/
vpArray2D<float> m_fg; /*!< Array that contains the Gaussian kernel.*/

// // Gradient computation attributes
bool m_areGradientAvailable; /*!< Set to true if the user provides the gradient images, false otherwise. In the latter case, the class will compute the gradients.*/
vpArray2D<float> m_fg; /*!< Array that contains the Gaussian kernel.*/
vpArray2D<float> m_fgDg; /*!< Array that contains the derivative of the Gaussian kernel.*/
unsigned int m_gradientFilterKernelSize; /*!< The size of the Sobel kernels used to compute the gradients of the image.*/
vpArray2D<float> m_gradientFilterX; /*!< Array that contains the gradient filter kernel (Sobel or Scharr) along the X-axis.*/
vpArray2D<float> m_gradientFilterY; /*!< Array that contains the gradient filter kernel (Sobel or Scharr) along the Y-axis.*/
vpImage<float> m_dIx; /*!< X-axis gradient.*/
vpImage<float> m_dIy; /*!< Y-axis gradient.*/

// // Edge thining attributes
std::map<std::pair<unsigned int, unsigned int>, float> m_edgeCandidateAndGradient; /*!< Map that contains point image coordinates and corresponding gradient value.*/

// // Hysteresis thresholding attributes
float m_lowerThreshold; /*!< Lower threshold for the hysteresis step. If negative, it will be deduced as from m_upperThreshold. */
float m_lowerThreshold; /*!< Lower threshold for the hysteresis step. If negative, it will be deduced
as from m_upperThreshold. */
float m_lowerThresholdRatio; /*!< If the thresholds must be computed, the ratio of the upper threshold the lower
threshold is equal: m_lowerThreshold = m_lowerThresholdRatio * m_upperThreshold. */
float m_upperThreshold; /*!< Upper threshold for the hysteresis step.*/
float m_upperThresholdRatio; /*!< If the thresholds must be computed, the ratio of pixels of the gradient image that
must be lower than the upper threshold \b m_upperThreshold.*/

// // Edge tracking attributes
std::map<std::pair<unsigned int, unsigned int>, EdgeType> m_edgePointsCandidates; /*!< Map that contains the strong edge points, i.e. the points for which we know for sure they are edge points,
Expand All @@ -82,10 +93,14 @@ class VISP_EXPORT vpCannyEdgeDetection
/** @name Constructors and initialization */
//@{
/**
* \brief Initialize the Gaussian filters used to filter the input image and
* to compute its gradients.
* \brief Initialize the Gaussian filters used to filter the input image.
*/
void initGaussianFilters();

/**
* \brief Initialize the gradient filters (Sobel or Scharr) used to compute the input image gradients.
*/
void initGradientFilters();
//@}

/** @name Different steps methods */
Expand All @@ -112,15 +127,15 @@ class VISP_EXPORT vpCannyEdgeDetection
* \b m_weakEdgePoints and will be kept in the final edge map only if they are connected
* to a strong edge point.
* Edge candidates that are below \b m_lowerThreshold are discarded.
* \param lowerThreshold Edge candidates that are below this threshold are definitely not
* \param[in] lowerThreshold Edge candidates that are below this threshold are definitely not
* edges.
* \param upperThreshold Edge candidates that are greater than this threshold are classified
* \param[in] upperThreshold Edge candidates that are greater than this threshold are classified
* as strong edges.
*/
void performHysteresisThresholding(const float &lowerThreshold, const float &upperThreshold);

/**
* @brief Search recursively for a strong edge in the neighborhood of a weak edge.
* \brief Search recursively for a strong edge in the neighborhood of a weak edge.
*
* \param[in] coordinates : The coordinates we are checking.
* \return true We found a strong edge point in its 8-connected neighborhood.
Expand All @@ -147,15 +162,28 @@ class VISP_EXPORT vpCannyEdgeDetection
vpCannyEdgeDetection();

/**
* \brief Construct a new vpCannyEdgeDetection object.
* \brief Construct a new vpCannyEdgeDetection object that uses Gaussian blur + Sobel operators to compute
* the edge map.
*
* \param[in] gaussianKernelSize : The size of the Gaussian filter kernel. Must be odd.
* \param[in] gaussianStdev : The standard deviation of the Gaussian filter.
* \param[in] lowerThreshold : The lower threshold of the hysteresis thresholding step. If negative, will be computed from the upper threshold.
* \param[in] upperThreshold : The upper threshold of the hysteresis thresholding step. If negative, will be computed from the median of the gray values of the image.
* \param[in] sobelAperture : The size of the Sobel filters kernel. Must be odd.
* \param[in] lowerThreshold : The lower threshold of the hysteresis thresholding step. If negative, will be computed
* from the upper threshold.
* \param[in] upperThreshold : The upper threshold of the hysteresis thresholding step. If negative, will be computed
* from the histogram of the absolute gradient.
* \param[in] lowerThresholdRatio : If the thresholds must be computed,the lower threshold will be equal to the upper
* threshold times \b lowerThresholdRatio .
* \param[in] upperThresholdRatio : If the thresholds must be computed,the upper threshold will be equal to the value
* such as the number of pixels of the image times \b upperThresholdRatio have an absolute gradient lower than the
* upper threshold.
* \param[in] filteringType : The filtering and gradient operators to apply to the image before the edge detection
* operation.
*/
vpCannyEdgeDetection(const int &gaussianKernelSize, const float &gaussianStdev,
const float &lowerThreshold = -1., const float &upperThreshold = -1.);
vpCannyEdgeDetection(const int &gaussianKernelSize, const float &gaussianStdev, const unsigned int &sobelAperture,
const float &lowerThreshold = -1.f, const float &upperThreshold = -1.f,
const float &lowerThresholdRatio = 0.6f, const float &upperThresholdRatio = 0.8f,
const vpImageFilter::vpCannyFilteringAndGradientType &filteringType = vpImageFilter::CANNY_GBLUR_SOBEL_FILTERING);

// // Configuration from files
#ifdef VISP_HAVE_NLOHMANN_JSON
Expand All @@ -179,30 +207,42 @@ class VISP_EXPORT vpCannyEdgeDetection
* \brief Read the detector configuration from JSON. All values are optional and if an argument is not present,
* the default value defined in the constructor is kept
*
* \param j : The JSON object, resulting from the parsing of a JSON file.
* \param detector : The detector that will be initialized from the JSON data.
* \param[in] j : The JSON object, resulting from the parsing of a JSON file.
* \param[out] detector : The detector that will be initialized from the JSON data.
*/
inline friend void from_json(const json &j, vpCannyEdgeDetection &detector)
{
std::string filteringAndGradientName = vpImageFilter::vpCannyFilteringAndGradientTypeToString(detector.m_filteringAndGradientType);
filteringAndGradientName = j.value("filteringAndGradientType", filteringAndGradientName);
detector.m_filteringAndGradientType = vpImageFilter::vpCannyFilteringAndGradientTypeFromString(filteringAndGradientName);
detector.m_gaussianKernelSize = j.value("gaussianSize", detector.m_gaussianKernelSize);
detector.m_gaussianStdev = j.value("gaussianStdev", detector.m_gaussianStdev);
detector.m_lowerThreshold = j.value("lowerThreshold", detector.m_lowerThreshold);
detector.m_lowerThresholdRatio = j.value("lowerThresholdRatio", detector.m_lowerThresholdRatio);
detector.m_gradientFilterKernelSize = j.value("gradientFilterKernelSize", detector.m_gradientFilterKernelSize);
detector.m_upperThreshold = j.value("upperThreshold", detector.m_upperThreshold);
detector.m_upperThresholdRatio = j.value("upperThresholdRatio", detector.m_upperThresholdRatio);
}

/**
* \brief Parse a vpCannyEdgeDetection object into JSON format.
*
* \param j : A JSON parser object.
* \param detector : The vpCannyEdgeDetection object that must be parsed into JSON format.
* \param[out] j : A JSON parser object.
* \param[in] detector : The vpCannyEdgeDetection object that must be parsed into JSON format.
*/
inline friend void to_json(json &j, const vpCannyEdgeDetection &detector)
{
std::string filteringAndGradientName = vpImageFilter::vpCannyFilteringAndGradientTypeToString(detector.m_filteringAndGradientType);
j = json {
{"filteringAndGradientType", filteringAndGradientName},
{"gaussianSize", detector.m_gaussianKernelSize},
{"gaussianStdev", detector.m_gaussianStdev},
{"lowerThreshold", detector.m_lowerThreshold},
{"upperThreshold", detector.m_upperThreshold} };
{"lowerThresholdRatio", detector.m_lowerThresholdRatio},
{"gradientFilterKernelSize", detector.m_gradientFilterKernelSize},
{"upperThreshold", detector.m_upperThreshold},
{"upperThresholdRatio", detector.m_upperThresholdRatio}
};
}
#endif
//@}
Expand Down Expand Up @@ -240,6 +280,17 @@ class VISP_EXPORT vpCannyEdgeDetection

/** @name Setters */
//@{
/**
* \brief Set the Filtering And Gradient operators to apply to the image before the edge detection operation.
*
* \param[in] type The operators to apply.
*/
inline void setFilteringAndGradientType(const vpImageFilter::vpCannyFilteringAndGradientType &type)
{
m_filteringAndGradientType = type;
initGradientFilters();
}

/**
* \brief Set the Gradients of the image that will be processed.
*
Expand Down Expand Up @@ -271,7 +322,25 @@ class VISP_EXPORT vpCannyEdgeDetection
}

/**
* @brief Set the Gaussian Filters kernel size and standard deviation
* \brief Set the lower and upper Canny Thresholds ratio that are used to compute them automatically. To ask to
* compute automatically the thresholds, you must set the lower and upper thresholds with negative values using the
* appropriate setter.
*
* \sa \ref vpCannyEdgeDetection::setCannyThresholds() "vpCannyEdgeDetection::setCannyThresholds(const float&, const float&)"
* \param[in] lowerThreshRatio : The lower threshold ratio: if the thresholds are computed automatically, the lower
* threshold will be equal to the upper threshold multiplied by \b lowerThreshRatio.
* \param[in] upperThreshRatio : The upper threshold ratio: if the thresholds are computed automatically, the upper
* threshold will be set such as \b upperThreshRatio times the number of pixels of the image have their absolute
* gradient lower then the upper threshold.
*/
inline void setCannyThresholdsRatio(const float &lowerThreshRatio, const float &upperThreshRatio)
{
m_lowerThresholdRatio = lowerThreshRatio;
m_upperThresholdRatio = upperThreshRatio;
}

/**
* \brief Set the Gaussian Filters kernel size and standard deviation
* and initialize the aforementioned filters.
*
* \param[in] kernelSize : The size of the Gaussian filters kernel.
Expand All @@ -284,6 +353,17 @@ class VISP_EXPORT vpCannyEdgeDetection
m_gaussianStdev = stdev;
initGaussianFilters();
}

/**
* \brief Set the parameters of the gradient filter (Sobel or Scharr) kernel size filters.
*
* \param[in] apertureSize The size of the gradient filters kernel. Must be an odd value.
*/
inline void setGradientFilterAperture(const unsigned int &apertureSize)
{
m_gradientFilterKernelSize = apertureSize;
initGradientFilters();
}
//@}
};
#endif
1 change: 1 addition & 0 deletions modules/core/include/visp3/core/vpHistogram.h
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Expand Up @@ -234,6 +234,7 @@ class VISP_EXPORT vpHistogram
};

void calculate(const vpImage<unsigned char> &I, unsigned int nbins = 256, unsigned int nbThreads = 1);
void equalize(const vpImage<unsigned char> &I, vpImage<unsigned char> &Iout);

void display(const vpImage<unsigned char> &I, const vpColor &color = vpColor::white, unsigned int thickness = 2,
unsigned int maxValue_ = 0);
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2 changes: 2 additions & 0 deletions modules/core/include/visp3/core/vpImageConvert.h
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Expand Up @@ -111,11 +111,13 @@ class VISP_EXPORT vpImageConvert
static void convert(const cv::Mat &src, vpImage<vpRGBa> &dest, bool flip = false);
static void convert(const cv::Mat &src, vpImage<unsigned char> &dest, bool flip = false, unsigned int nThreads = 0);
static void convert(const cv::Mat &src, vpImage<float> &dest, bool flip = false);
static void convert(const cv::Mat &src, vpImage<double> &dest, bool flip = false);
static void convert(const cv::Mat &src, vpImage<vpRGBf> &dest, bool flip = false);
static void convert(const cv::Mat &src, vpImage<uint16_t> &dest, bool flip = false);
static void convert(const vpImage<vpRGBa> &src, cv::Mat &dest);
static void convert(const vpImage<unsigned char> &src, cv::Mat &dest, bool copyData = true);
static void convert(const vpImage<float> &src, cv::Mat &dest, bool copyData = true);
static void convert(const vpImage<double> &src, cv::Mat &dest, bool copyData = true);
static void convert(const vpImage<vpRGBf> &src, cv::Mat &dest);
#endif

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