Open Source Computer Vision Library
https://opencv.org/
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103 lines
5.6 KiB
103 lines
5.6 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "precomp.hpp" |
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#include "opencv2/video/video.hpp" |
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namespace cv |
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{ |
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/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
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CV_INIT_ALGORITHM(BackgroundSubtractorMOG, "BackgroundSubtractor.MOG", |
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obj.info()->addParam(obj, "history", obj.history); |
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obj.info()->addParam(obj, "nmixtures", obj.nmixtures); |
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obj.info()->addParam(obj, "backgroundRatio", obj.backgroundRatio); |
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obj.info()->addParam(obj, "noiseSigma", obj.noiseSigma)) |
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/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
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CV_INIT_ALGORITHM(BackgroundSubtractorMOG2, "BackgroundSubtractor.MOG2", |
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obj.info()->addParam(obj, "history", obj.history); |
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obj.info()->addParam(obj, "nmixtures", obj.nmixtures); |
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obj.info()->addParam(obj, "varThreshold", obj.varThreshold); |
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obj.info()->addParam(obj, "detectShadows", obj.bShadowDetection); |
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obj.info()->addParam(obj, "backgroundRatio", obj.backgroundRatio); |
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obj.info()->addParam(obj, "varThresholdGen", obj.varThresholdGen); |
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obj.info()->addParam(obj, "fVarInit", obj.fVarInit); |
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obj.info()->addParam(obj, "fVarMin", obj.fVarMin); |
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obj.info()->addParam(obj, "fVarMax", obj.fVarMax); |
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obj.info()->addParam(obj, "fCT", obj.fCT); |
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obj.info()->addParam(obj, "nShadowDetection", obj.nShadowDetection); |
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obj.info()->addParam(obj, "fTau", obj.fTau)) |
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/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
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CV_INIT_ALGORITHM(BackgroundSubtractorGMG, "BackgroundSubtractor.GMG", |
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obj.info()->addParam(obj, "maxFeatures", obj.maxFeatures,false,0,0, |
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"Maximum number of features to store in histogram. Harsh enforcement of sparsity constraint."); |
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obj.info()->addParam(obj, "learningRate", obj.learningRate,false,0,0, |
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"Adaptation rate of histogram. Close to 1, slow adaptation. Close to 0, fast adaptation, features forgotten quickly."); |
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obj.info()->addParam(obj, "initializationFrames", obj.numInitializationFrames,false,0,0, |
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"Number of frames to use to initialize histograms of pixels."); |
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obj.info()->addParam(obj, "quantizationLevels", obj.quantizationLevels,false,0,0, |
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"Number of discrete colors to be used in histograms. Up-front quantization."); |
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obj.info()->addParam(obj, "backgroundPrior", obj.backgroundPrior,false,0,0, |
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"Prior probability that each individual pixel is a background pixel."); |
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obj.info()->addParam(obj, "smoothingRadius", obj.smoothingRadius,false,0,0, |
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"Radius of smoothing kernel to filter noise from FG mask image."); |
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obj.info()->addParam(obj, "decisionThreshold", obj.decisionThreshold,false,0,0, |
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"Threshold for FG decision rule. Pixel is FG if posterior probability exceeds threshold."); |
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obj.info()->addParam(obj, "updateBackgroundModel", obj.updateBackgroundModel,false,0,0, |
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"Perform background model update.")) |
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bool initModule_video(void) |
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{ |
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bool all = true; |
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all &= !BackgroundSubtractorMOG_info_auto.name().empty(); |
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all &= !BackgroundSubtractorMOG2_info_auto.name().empty(); |
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all &= !BackgroundSubtractorGMG_info_auto.name().empty(); |
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return all; |
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} |
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}
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