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init: 64 bits version of the webcam

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This commit is contained in:
Nicolas RACOT
2026-07-13 16:31:52 +02:00
parent c0f3eeb00d
commit 07e526544d
381 changed files with 43996 additions and 9097 deletions
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25
include/opencv2/video/background_segm.hpp
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@ -41,8 +41,8 @@
//
//M*/
#ifndef __OPENCV_BACKGROUND_SEGM_HPP__
#define __OPENCV_BACKGROUND_SEGM_HPP__
#ifndef OPENCV_BACKGROUND_SEGM_HPP
#define OPENCV_BACKGROUND_SEGM_HPP
#include "opencv2/core.hpp"
@ -188,13 +188,24 @@ public:
A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in
the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel
is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiarra,
is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiara,
*Detecting Moving Shadows...*, IEEE PAMI,2003.
*/
CV_WRAP virtual double getShadowThreshold() const = 0;
/** @brief Sets the shadow threshold
*/
CV_WRAP virtual void setShadowThreshold(double threshold) = 0;
/** @brief Computes a foreground mask.
@param image Next video frame. Floating point frame will be used without scaling and should be in range \f$[0,255]\f$.
@param fgmask The output foreground mask as an 8-bit binary image.
@param learningRate The value between 0 and 1 that indicates how fast the background model is
learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
rate. 0 means that the background model is not updated at all, 1 means that the background model
is completely reinitialized from the last frame.
*/
CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
};
/** @brief Creates MOG2 Background Subtractor
@ -210,9 +221,9 @@ CV_EXPORTS_W Ptr<BackgroundSubtractorMOG2>
createBackgroundSubtractorMOG2(int history=500, double varThreshold=16,
bool detectShadows=true);
/** @brief K-nearest neigbours - based Background/Foreground Segmentation Algorithm.
/** @brief K-nearest neighbours - based Background/Foreground Segmentation Algorithm.
The class implements the K-nearest neigbours background subtraction described in @cite Zivkovic2006 .
The class implements the K-nearest neighbours background subtraction described in @cite Zivkovic2006 .
Very efficient if number of foreground pixels is low.
*/
class CV_EXPORTS_W BackgroundSubtractorKNN : public BackgroundSubtractor
@ -250,7 +261,7 @@ public:
pixel is matching the kNN background model.
*/
CV_WRAP virtual int getkNNSamples() const = 0;
/** @brief Sets the k in the kNN. How many nearest neigbours need to match.
/** @brief Sets the k in the kNN. How many nearest neighbours need to match.
*/
CV_WRAP virtual void setkNNSamples(int _nkNN) = 0;
@ -278,7 +289,7 @@ public:
A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in
the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel
is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiarra,
is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiara,
*Detecting Moving Shadows...*, IEEE PAMI,2003.
*/
CV_WRAP virtual double getShadowThreshold() const = 0;