gpubgsegm module fixes
This commit is contained in:
Vladislav Vinogradov
parent
c0b3424a23
commit
f531dd839c
@ -4,6 +4,6 @@ endif()
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set(the_description "GPU-accelerated Background Segmentation")
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ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef -Wmissing-declarations)
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ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4127 /wd4324 /wd4512 -Wundef -Wmissing-declarations)
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ocv_define_module(gpubgsegm opencv_video opencv_legacy opencv_gpufilters opencv_gpuimgproc)
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ocv_define_module(gpubgsegm opencv_video opencv_imgproc opencv_legacy opencv_gpuarithm opencv_gpufilters opencv_gpuimgproc)
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@ -1,296 +1,10 @@
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Video Analysis
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==============
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Background Segmentation
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=======================
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.. highlight:: cpp
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gpu::BroxOpticalFlow
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--------------------
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.. ocv:class:: gpu::BroxOpticalFlow
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Class computing the optical flow for two images using Brox et al Optical Flow algorithm ([Brox2004]_). ::
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class BroxOpticalFlow
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{
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public:
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BroxOpticalFlow(float alpha_, float gamma_, float scale_factor_, int inner_iterations_, int outer_iterations_, int solver_iterations_);
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//! Compute optical flow
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//! frame0 - source frame (supports only CV_32FC1 type)
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//! frame1 - frame to track (with the same size and type as frame0)
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//! u - flow horizontal component (along x axis)
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//! v - flow vertical component (along y axis)
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void operator ()(const GpuMat& frame0, const GpuMat& frame1, GpuMat& u, GpuMat& v, Stream& stream = Stream::Null());
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//! flow smoothness
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float alpha;
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//! gradient constancy importance
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float gamma;
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//! pyramid scale factor
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float scale_factor;
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//! number of lagged non-linearity iterations (inner loop)
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int inner_iterations;
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//! number of warping iterations (number of pyramid levels)
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int outer_iterations;
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//! number of linear system solver iterations
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int solver_iterations;
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GpuMat buf;
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};
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gpu::GoodFeaturesToTrackDetector_GPU
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------------------------------------
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.. ocv:class:: gpu::GoodFeaturesToTrackDetector_GPU
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Class used for strong corners detection on an image. ::
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class GoodFeaturesToTrackDetector_GPU
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{
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public:
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explicit GoodFeaturesToTrackDetector_GPU(int maxCorners_ = 1000, double qualityLevel_ = 0.01, double minDistance_ = 0.0,
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int blockSize_ = 3, bool useHarrisDetector_ = false, double harrisK_ = 0.04);
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void operator ()(const GpuMat& image, GpuMat& corners, const GpuMat& mask = GpuMat());
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int maxCorners;
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double qualityLevel;
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double minDistance;
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int blockSize;
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bool useHarrisDetector;
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double harrisK;
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void releaseMemory();
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};
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The class finds the most prominent corners in the image.
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.. seealso:: :ocv:func:`goodFeaturesToTrack`
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gpu::GoodFeaturesToTrackDetector_GPU::GoodFeaturesToTrackDetector_GPU
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---------------------------------------------------------------------
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Constructor.
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.. ocv:function:: gpu::GoodFeaturesToTrackDetector_GPU::GoodFeaturesToTrackDetector_GPU(int maxCorners = 1000, double qualityLevel = 0.01, double minDistance = 0.0, int blockSize = 3, bool useHarrisDetector = false, double harrisK = 0.04)
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:param maxCorners: Maximum number of corners to return. If there are more corners than are found, the strongest of them is returned.
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:param qualityLevel: Parameter characterizing the minimal accepted quality of image corners. The parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue (see :ocv:func:`gpu::cornerMinEigenVal` ) or the Harris function response (see :ocv:func:`gpu::cornerHarris` ). The corners with the quality measure less than the product are rejected. For example, if the best corner has the quality measure = 1500, and the ``qualityLevel=0.01`` , then all the corners with the quality measure less than 15 are rejected.
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:param minDistance: Minimum possible Euclidean distance between the returned corners.
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:param blockSize: Size of an average block for computing a derivative covariation matrix over each pixel neighborhood. See :ocv:func:`cornerEigenValsAndVecs` .
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:param useHarrisDetector: Parameter indicating whether to use a Harris detector (see :ocv:func:`gpu::cornerHarris`) or :ocv:func:`gpu::cornerMinEigenVal`.
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:param harrisK: Free parameter of the Harris detector.
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gpu::GoodFeaturesToTrackDetector_GPU::operator ()
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-------------------------------------------------
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Finds the most prominent corners in the image.
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.. ocv:function:: void gpu::GoodFeaturesToTrackDetector_GPU::operator ()(const GpuMat& image, GpuMat& corners, const GpuMat& mask = GpuMat())
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:param image: Input 8-bit, single-channel image.
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:param corners: Output vector of detected corners (it will be one row matrix with CV_32FC2 type).
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:param mask: Optional region of interest. If the image is not empty (it needs to have the type ``CV_8UC1`` and the same size as ``image`` ), it specifies the region in which the corners are detected.
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.. seealso:: :ocv:func:`goodFeaturesToTrack`
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gpu::GoodFeaturesToTrackDetector_GPU::releaseMemory
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---------------------------------------------------
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Releases inner buffers memory.
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.. ocv:function:: void gpu::GoodFeaturesToTrackDetector_GPU::releaseMemory()
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gpu::FarnebackOpticalFlow
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-------------------------
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.. ocv:class:: gpu::FarnebackOpticalFlow
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Class computing a dense optical flow using the Gunnar Farneback’s algorithm. ::
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class CV_EXPORTS FarnebackOpticalFlow
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{
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public:
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FarnebackOpticalFlow()
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{
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numLevels = 5;
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pyrScale = 0.5;
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fastPyramids = false;
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winSize = 13;
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numIters = 10;
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polyN = 5;
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polySigma = 1.1;
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flags = 0;
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}
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int numLevels;
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double pyrScale;
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bool fastPyramids;
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int winSize;
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int numIters;
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int polyN;
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double polySigma;
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int flags;
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void operator ()(const GpuMat &frame0, const GpuMat &frame1, GpuMat &flowx, GpuMat &flowy, Stream &s = Stream::Null());
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void releaseMemory();
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private:
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/* hidden */
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};
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gpu::FarnebackOpticalFlow::operator ()
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--------------------------------------
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Computes a dense optical flow using the Gunnar Farneback’s algorithm.
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.. ocv:function:: void gpu::FarnebackOpticalFlow::operator ()(const GpuMat &frame0, const GpuMat &frame1, GpuMat &flowx, GpuMat &flowy, Stream &s = Stream::Null())
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:param frame0: First 8-bit gray-scale input image
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:param frame1: Second 8-bit gray-scale input image
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:param flowx: Flow horizontal component
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:param flowy: Flow vertical component
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:param s: Stream
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.. seealso:: :ocv:func:`calcOpticalFlowFarneback`
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gpu::FarnebackOpticalFlow::releaseMemory
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----------------------------------------
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Releases unused auxiliary memory buffers.
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.. ocv:function:: void gpu::FarnebackOpticalFlow::releaseMemory()
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gpu::PyrLKOpticalFlow
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---------------------
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.. ocv:class:: gpu::PyrLKOpticalFlow
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Class used for calculating an optical flow. ::
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class PyrLKOpticalFlow
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{
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public:
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PyrLKOpticalFlow();
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void sparse(const GpuMat& prevImg, const GpuMat& nextImg, const GpuMat& prevPts, GpuMat& nextPts,
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GpuMat& status, GpuMat* err = 0);
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void dense(const GpuMat& prevImg, const GpuMat& nextImg, GpuMat& u, GpuMat& v, GpuMat* err = 0);
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Size winSize;
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int maxLevel;
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int iters;
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bool useInitialFlow;
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void releaseMemory();
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};
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The class can calculate an optical flow for a sparse feature set or dense optical flow using the iterative Lucas-Kanade method with pyramids.
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.. seealso:: :ocv:func:`calcOpticalFlowPyrLK`
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gpu::PyrLKOpticalFlow::sparse
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-----------------------------
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Calculate an optical flow for a sparse feature set.
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.. ocv:function:: void gpu::PyrLKOpticalFlow::sparse(const GpuMat& prevImg, const GpuMat& nextImg, const GpuMat& prevPts, GpuMat& nextPts, GpuMat& status, GpuMat* err = 0)
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:param prevImg: First 8-bit input image (supports both grayscale and color images).
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:param nextImg: Second input image of the same size and the same type as ``prevImg`` .
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:param prevPts: Vector of 2D points for which the flow needs to be found. It must be one row matrix with CV_32FC2 type.
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:param nextPts: Output vector of 2D points (with single-precision floating-point coordinates) containing the calculated new positions of input features in the second image. When ``useInitialFlow`` is true, the vector must have the same size as in the input.
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:param status: Output status vector (CV_8UC1 type). Each element of the vector is set to 1 if the flow for the corresponding features has been found. Otherwise, it is set to 0.
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:param err: Output vector (CV_32FC1 type) that contains the difference between patches around the original and moved points or min eigen value if ``getMinEigenVals`` is checked. It can be NULL, if not needed.
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.. seealso:: :ocv:func:`calcOpticalFlowPyrLK`
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gpu::PyrLKOpticalFlow::dense
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-----------------------------
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Calculate dense optical flow.
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.. ocv:function:: void gpu::PyrLKOpticalFlow::dense(const GpuMat& prevImg, const GpuMat& nextImg, GpuMat& u, GpuMat& v, GpuMat* err = 0)
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:param prevImg: First 8-bit grayscale input image.
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:param nextImg: Second input image of the same size and the same type as ``prevImg`` .
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:param u: Horizontal component of the optical flow of the same size as input images, 32-bit floating-point, single-channel
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:param v: Vertical component of the optical flow of the same size as input images, 32-bit floating-point, single-channel
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:param err: Output vector (CV_32FC1 type) that contains the difference between patches around the original and moved points or min eigen value if ``getMinEigenVals`` is checked. It can be NULL, if not needed.
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gpu::PyrLKOpticalFlow::releaseMemory
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------------------------------------
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Releases inner buffers memory.
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.. ocv:function:: void gpu::PyrLKOpticalFlow::releaseMemory()
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gpu::interpolateFrames
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----------------------
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Interpolates frames (images) using provided optical flow (displacement field).
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.. ocv:function:: void gpu::interpolateFrames(const GpuMat& frame0, const GpuMat& frame1, const GpuMat& fu, const GpuMat& fv, const GpuMat& bu, const GpuMat& bv, float pos, GpuMat& newFrame, GpuMat& buf, Stream& stream = Stream::Null())
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:param frame0: First frame (32-bit floating point images, single channel).
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:param frame1: Second frame. Must have the same type and size as ``frame0`` .
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:param fu: Forward horizontal displacement.
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:param fv: Forward vertical displacement.
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:param bu: Backward horizontal displacement.
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:param bv: Backward vertical displacement.
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:param pos: New frame position.
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:param newFrame: Output image.
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:param buf: Temporary buffer, will have width x 6*height size, CV_32FC1 type and contain 6 GpuMat: occlusion masks for first frame, occlusion masks for second, interpolated forward horizontal flow, interpolated forward vertical flow, interpolated backward horizontal flow, interpolated backward vertical flow.
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:param stream: Stream for the asynchronous version.
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gpu::FGDStatModel
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-----------------
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.. ocv:class:: gpu::FGDStatModel
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@ -687,7 +401,6 @@ Releases all inner buffer's memory.
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.. [Brox2004] T. Brox, A. Bruhn, N. Papenberg, J. Weickert. *High accuracy optical flow estimation based on a theory for warping*. ECCV 2004.
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.. [FGD2003] Liyuan Li, Weimin Huang, Irene Y.H. Gu, and Qi Tian. *Foreground Object Detection from Videos Containing Complex Background*. ACM MM2003 9p, 2003.
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.. [MOG2001] P. KadewTraKuPong and R. Bowden. *An improved adaptive background mixture model for real-time tracking with shadow detection*. Proc. 2nd European Workshop on Advanced Video-Based Surveillance Systems, 2001
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.. [MOG2004] Z. Zivkovic. *Improved adaptive Gausian mixture model for background subtraction*. International Conference Pattern Recognition, UK, August, 2004
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@ -1,6 +1,6 @@
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********************************************
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gpu. GPU-accelerated Background Segmentation
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********************************************
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**************************************************
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gpubgsegm. GPU-accelerated Background Segmentation
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**************************************************
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.. toctree::
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:maxdepth: 1
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@ -43,6 +43,10 @@
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#ifndef __OPENCV_GPUBGSEGM_HPP__
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#define __OPENCV_GPUBGSEGM_HPP__
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#ifndef __cplusplus
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# error gpubgsegm.hpp header must be compiled as C++
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#endif
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#include <memory>
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#include "opencv2/core/gpumat.hpp"
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@ -41,6 +41,7 @@
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//M*/
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#include "perf_precomp.hpp"
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#include "opencv2/legacy.hpp"
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using namespace std;
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using namespace testing;
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@ -73,7 +74,7 @@ namespace cv
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DEF_PARAM_TEST_1(Video, string);
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PERF_TEST_P(Video, Video_FGDStatModel,
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PERF_TEST_P(Video, FGDStatModel,
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Values(string("gpu/video/768x576.avi")))
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{
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declare.time(60);
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@ -146,7 +147,7 @@ PERF_TEST_P(Video, Video_FGDStatModel,
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DEF_PARAM_TEST(Video_Cn_LearningRate, string, MatCn, double);
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PERF_TEST_P(Video_Cn_LearningRate, Video_MOG,
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PERF_TEST_P(Video_Cn_LearningRate, MOG,
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Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
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GPU_CHANNELS_1_3_4,
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Values(0.0, 0.01)))
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@ -245,7 +246,7 @@ PERF_TEST_P(Video_Cn_LearningRate, Video_MOG,
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DEF_PARAM_TEST(Video_Cn, string, int);
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PERF_TEST_P(Video_Cn, Video_MOG2,
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PERF_TEST_P(Video_Cn, MOG2,
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Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
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GPU_CHANNELS_1_3_4))
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{
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@ -344,7 +345,7 @@ PERF_TEST_P(Video_Cn, Video_MOG2,
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#if BUILD_WITH_VIDEO_INPUT_SUPPORT
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PERF_TEST_P(Video_Cn, Video_MOG2GetBackgroundImage,
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PERF_TEST_P(Video_Cn, MOG2GetBackgroundImage,
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Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
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GPU_CHANNELS_1_3_4))
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{
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@ -428,7 +429,7 @@ PERF_TEST_P(Video_Cn, Video_MOG2GetBackgroundImage,
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DEF_PARAM_TEST(Video_Cn_MaxFeatures, string, MatCn, int);
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PERF_TEST_P(Video_Cn_MaxFeatures, Video_GMG,
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PERF_TEST_P(Video_Cn_MaxFeatures, GMG,
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Combine(Values(string("gpu/video/768x576.avi")),
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GPU_CHANNELS_1_3_4,
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Values(20, 40, 60)))
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@ -44,4 +44,4 @@
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using namespace perf;
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CV_PERF_TEST_MAIN(gpuarithm, printCudaInfo())
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CV_PERF_TEST_MAIN(gpubgsegm, printCudaInfo())
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@ -55,9 +55,7 @@
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#include "opencv2/ts/gpu_perf.hpp"
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#include "opencv2/gpubgsegm.hpp"
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#include "opencv2/video.hpp"
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#include "opencv2/legacy.hpp"
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#ifdef GTEST_CREATE_SHARED_LIBRARY
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#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined
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@ -48,7 +48,7 @@
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#include "opencv2/core/cuda/utility.hpp"
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#include "opencv2/core/cuda/reduce.hpp"
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#include "opencv2/core/cuda/functional.hpp"
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#include "fgd_bgfg_common.hpp"
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#include "fgd.hpp"
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using namespace cv::gpu;
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using namespace cv::gpu::cudev;
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@ -59,7 +59,7 @@ int cv::gpu::FGDStatModel::update(const cv::gpu::GpuMat&) { throw_no_cuda(); ret
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#else
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#include "fgd_bgfg_common.hpp"
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#include "cuda/fgd.hpp"
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#include "opencv2/imgproc/imgproc_c.h"
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namespace
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@ -46,23 +46,10 @@
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#include <limits>
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#include "opencv2/gpubgsegm.hpp"
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#include "opencv2/gpuarithm.hpp"
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#include "opencv2/gpufilters.hpp"
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#include "opencv2/gpuimgproc.hpp"
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#include "opencv2/imgproc/imgproc_c.h"
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#include "opencv2/video.hpp"
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#include "opencv2/core/gpu_private.hpp"
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#include "opencv2/opencv_modules.hpp"
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#ifdef HAVE_OPENCV_GPULEGACY
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# include "opencv2/gpulegacy/private.hpp"
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#endif
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#ifdef HAVE_CUDA
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# include "cuda/fgd_bgfg_common.hpp"
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#endif
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#endif /* __OPENCV_PRECOMP_H__ */
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@ -143,7 +143,7 @@ GPU_TEST_P(FGDStatModel, Update)
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}
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}
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INSTANTIATE_TEST_CASE_P(GPU_Video, FGDStatModel, testing::Combine(
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INSTANTIATE_TEST_CASE_P(GPU_BgSegm, FGDStatModel, testing::Combine(
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ALL_DEVICES,
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testing::Values(std::string("768x576.avi")),
|
||||
testing::Values(Channels(3), Channels(4))));
|
||||
@ -219,7 +219,7 @@ GPU_TEST_P(MOG, Update)
|
||||
}
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_CASE_P(GPU_Video, MOG, testing::Combine(
|
||||
INSTANTIATE_TEST_CASE_P(GPU_BgSegm, MOG, testing::Combine(
|
||||
ALL_DEVICES,
|
||||
testing::Values(std::string("768x576.avi")),
|
||||
testing::Values(UseGray(true), UseGray(false)),
|
||||
@ -339,7 +339,7 @@ GPU_TEST_P(MOG2, getBackgroundImage)
|
||||
ASSERT_MAT_NEAR(background_gold, background, 0);
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_CASE_P(GPU_Video, MOG2, testing::Combine(
|
||||
INSTANTIATE_TEST_CASE_P(GPU_BgSegm, MOG2, testing::Combine(
|
||||
ALL_DEVICES,
|
||||
testing::Values(std::string("768x576.avi")),
|
||||
testing::Values(UseGray(true), UseGray(false)),
|
||||
@ -395,7 +395,7 @@ GPU_TEST_P(GMG, Accuracy)
|
||||
ASSERT_MAT_NEAR(fullfg, d_fgmask, 0);
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_CASE_P(GPU_Video, GMG, testing::Combine(
|
||||
INSTANTIATE_TEST_CASE_P(GPU_BgSegm, GMG, testing::Combine(
|
||||
ALL_DEVICES,
|
||||
DIFFERENT_SIZES,
|
||||
testing::Values(MatType(CV_8U), MatType(CV_16U), MatType(CV_32F)),
|
||||
@ -57,8 +57,6 @@
|
||||
#include "opencv2/ts/gpu_test.hpp"
|
||||
|
||||
#include "opencv2/gpubgsegm.hpp"
|
||||
|
||||
#include "opencv2/video.hpp"
|
||||
#include "opencv2/legacy.hpp"
|
||||
|
||||
#endif
|
||||
|
||||
Loading…
Reference in New Issue
Block a user