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11 // For Open Source Computer Vision Library
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41 //M*/
42
43 #include "precomp.hpp"
44
45 using namespace cv;
46 using namespace cv::cuda;
47
48 #if !defined HAVE_CUDA || defined(CUDA_DISABLER)
49
createBackgroundSubtractorMOG(int,int,double,double)50 Ptr<cuda::BackgroundSubtractorMOG> cv::cuda::createBackgroundSubtractorMOG(int, int, double, double) { throw_no_cuda(); return Ptr<cuda::BackgroundSubtractorMOG>(); }
51
52 #else
53
54 namespace cv { namespace cuda { namespace device
55 {
56 namespace mog
57 {
58 void mog_gpu(PtrStepSzb frame, int cn, PtrStepSzb fgmask, PtrStepSzf weight, PtrStepSzf sortKey, PtrStepSzb mean, PtrStepSzb var,
59 int nmixtures, float varThreshold, float learningRate, float backgroundRatio, float noiseSigma,
60 cudaStream_t stream);
61 void getBackgroundImage_gpu(int cn, PtrStepSzf weight, PtrStepSzb mean, PtrStepSzb dst, int nmixtures, float backgroundRatio, cudaStream_t stream);
62 }
63 }}}
64
65 namespace
66 {
67 const int defaultNMixtures = 5;
68 const int defaultHistory = 200;
69 const float defaultBackgroundRatio = 0.7f;
70 const float defaultVarThreshold = 2.5f * 2.5f;
71 const float defaultNoiseSigma = 30.0f * 0.5f;
72 const float defaultInitialWeight = 0.05f;
73
74 class MOGImpl : public cuda::BackgroundSubtractorMOG
75 {
76 public:
77 MOGImpl(int history, int nmixtures, double backgroundRatio, double noiseSigma);
78
79 void apply(InputArray image, OutputArray fgmask, double learningRate=-1);
80 void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream);
81
82 void getBackgroundImage(OutputArray backgroundImage) const;
83 void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const;
84
getHistory() const85 int getHistory() const { return history_; }
setHistory(int nframes)86 void setHistory(int nframes) { history_ = nframes; }
87
getNMixtures() const88 int getNMixtures() const { return nmixtures_; }
setNMixtures(int nmix)89 void setNMixtures(int nmix) { nmixtures_ = nmix; }
90
getBackgroundRatio() const91 double getBackgroundRatio() const { return backgroundRatio_; }
setBackgroundRatio(double backgroundRatio)92 void setBackgroundRatio(double backgroundRatio) { backgroundRatio_ = (float) backgroundRatio; }
93
getNoiseSigma() const94 double getNoiseSigma() const { return noiseSigma_; }
setNoiseSigma(double noiseSigma)95 void setNoiseSigma(double noiseSigma) { noiseSigma_ = (float) noiseSigma; }
96
97 private:
98 //! re-initiaization method
99 void initialize(Size frameSize, int frameType);
100
101 int history_;
102 int nmixtures_;
103 float backgroundRatio_;
104 float noiseSigma_;
105
106 float varThreshold_;
107
108 Size frameSize_;
109 int frameType_;
110 int nframes_;
111
112 GpuMat weight_;
113 GpuMat sortKey_;
114 GpuMat mean_;
115 GpuMat var_;
116 };
117
MOGImpl(int history,int nmixtures,double backgroundRatio,double noiseSigma)118 MOGImpl::MOGImpl(int history, int nmixtures, double backgroundRatio, double noiseSigma) :
119 frameSize_(0, 0), frameType_(0), nframes_(0)
120 {
121 history_ = history > 0 ? history : defaultHistory;
122 nmixtures_ = std::min(nmixtures > 0 ? nmixtures : defaultNMixtures, 8);
123 backgroundRatio_ = backgroundRatio > 0 ? (float) backgroundRatio : defaultBackgroundRatio;
124 noiseSigma_ = noiseSigma > 0 ? (float) noiseSigma : defaultNoiseSigma;
125
126 varThreshold_ = defaultVarThreshold;
127 }
128
apply(InputArray image,OutputArray fgmask,double learningRate)129 void MOGImpl::apply(InputArray image, OutputArray fgmask, double learningRate)
130 {
131 apply(image, fgmask, learningRate, Stream::Null());
132 }
133
apply(InputArray _frame,OutputArray _fgmask,double learningRate,Stream & stream)134 void MOGImpl::apply(InputArray _frame, OutputArray _fgmask, double learningRate, Stream& stream)
135 {
136 using namespace cv::cuda::device::mog;
137
138 GpuMat frame = _frame.getGpuMat();
139
140 CV_Assert( frame.depth() == CV_8U );
141
142 int ch = frame.channels();
143 int work_ch = ch;
144
145 if (nframes_ == 0 || learningRate >= 1.0 || frame.size() != frameSize_ || work_ch != mean_.channels())
146 initialize(frame.size(), frame.type());
147
148 _fgmask.create(frameSize_, CV_8UC1);
149 GpuMat fgmask = _fgmask.getGpuMat();
150
151 ++nframes_;
152 learningRate = learningRate >= 0 && nframes_ > 1 ? learningRate : 1.0 / std::min(nframes_, history_);
153 CV_Assert( learningRate >= 0 );
154
155 mog_gpu(frame, ch, fgmask, weight_, sortKey_, mean_, var_, nmixtures_,
156 varThreshold_, (float) learningRate, backgroundRatio_, noiseSigma_,
157 StreamAccessor::getStream(stream));
158 }
159
getBackgroundImage(OutputArray backgroundImage) const160 void MOGImpl::getBackgroundImage(OutputArray backgroundImage) const
161 {
162 getBackgroundImage(backgroundImage, Stream::Null());
163 }
164
getBackgroundImage(OutputArray _backgroundImage,Stream & stream) const165 void MOGImpl::getBackgroundImage(OutputArray _backgroundImage, Stream& stream) const
166 {
167 using namespace cv::cuda::device::mog;
168
169 _backgroundImage.create(frameSize_, frameType_);
170 GpuMat backgroundImage = _backgroundImage.getGpuMat();
171
172 getBackgroundImage_gpu(backgroundImage.channels(), weight_, mean_, backgroundImage, nmixtures_, backgroundRatio_, StreamAccessor::getStream(stream));
173 }
174
initialize(Size frameSize,int frameType)175 void MOGImpl::initialize(Size frameSize, int frameType)
176 {
177 CV_Assert( frameType == CV_8UC1 || frameType == CV_8UC3 || frameType == CV_8UC4 );
178
179 frameSize_ = frameSize;
180 frameType_ = frameType;
181
182 int ch = CV_MAT_CN(frameType);
183 int work_ch = ch;
184
185 // for each gaussian mixture of each pixel bg model we store
186 // the mixture sort key (w/sum_of_variances), the mixture weight (w),
187 // the mean (nchannels values) and
188 // the diagonal covariance matrix (another nchannels values)
189
190 weight_.create(frameSize.height * nmixtures_, frameSize_.width, CV_32FC1);
191 sortKey_.create(frameSize.height * nmixtures_, frameSize_.width, CV_32FC1);
192 mean_.create(frameSize.height * nmixtures_, frameSize_.width, CV_32FC(work_ch));
193 var_.create(frameSize.height * nmixtures_, frameSize_.width, CV_32FC(work_ch));
194
195 weight_.setTo(cv::Scalar::all(0));
196 sortKey_.setTo(cv::Scalar::all(0));
197 mean_.setTo(cv::Scalar::all(0));
198 var_.setTo(cv::Scalar::all(0));
199
200 nframes_ = 0;
201 }
202 }
203
createBackgroundSubtractorMOG(int history,int nmixtures,double backgroundRatio,double noiseSigma)204 Ptr<cuda::BackgroundSubtractorMOG> cv::cuda::createBackgroundSubtractorMOG(int history, int nmixtures, double backgroundRatio, double noiseSigma)
205 {
206 return makePtr<MOGImpl>(history, nmixtures, backgroundRatio, noiseSigma);
207 }
208
209 #endif
210