423 lines
14 KiB
C++
423 lines
14 KiB
C++
#pragma once
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#if defined(SG_API_LIBRARY)
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# define SG_APISHARED_EXPORT __declspec(dllexport)
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#else
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# define SG_APISHARED_EXPORT __declspec(dllimport)
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#endif
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#include "SG_baseDataType.h"
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#include <vector>
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#include <opencv2/opencv.hpp>
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//滤除离群点:z跳变门限方法（大于门限视为不连续，根据连续段点数量判断噪声）
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SG_APISHARED_EXPORT void sg_lineDataRemoveOutlier(
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SVzNL3DPosition* lineData,
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int dataSize,
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SSG_outlierFilterParam filterParam,
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std::vector<SVzNL3DPosition>& filerData,
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std::vector<int>& noisePts);
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//滤除离群点：z跳变门限方法,改变原始数据
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SG_APISHARED_EXPORT void sg_lineDataRemoveOutlier_changeOriginData(
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SVzNL3DPosition* lineData,
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int dataSize,
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SSG_outlierFilterParam filterParam);
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//滤除离群点：z跳变门限方法, vecotr对象
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SG_APISHARED_EXPORT void wd_vectorDataRemoveOutlier_overwrite(
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std::vector<SVzNL3DPosition>& a_line,
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SSG_outlierFilterParam filterParam);
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//滤除离群点：点距离门限方法（大于门限视为不连续，根据连续段点数量判断噪声）
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SG_APISHARED_EXPORT void sg_lineDataRemoveOutlier_ptDistMethod(
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SVzNL3DPosition* lineData,
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int dataSize,
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SSG_outlierFilterParam filterParam,
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std::vector<SVzNL3DPosition>& filerData,
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std::vector<int>& noisePts);
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//平滑
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SG_APISHARED_EXPORT void sg_lineDataSmoothing(
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std::vector<SVzNL3DPosition>& input,
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int smoothWin,
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std::vector<SVzNL3DPosition>& output);
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//分段平滑，这样不会影响分段端点
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SG_APISHARED_EXPORT void sg_lineSegSmoothing(
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std::vector<SVzNL3DPosition>& input,
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double seg_y_deltaTh, //分段的Y间隔。大于此间隔，为新的分段
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double seg_z_deltaTh,//分段的Z间隔。大于此间隔，为新的分段
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int smoothWin,
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std::vector<SVzNL3DPosition>& output);
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//VZ_APISHARED_EXPORT void sg_getLineMeanVar();
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SG_APISHARED_EXPORT void sg_getLineLVFeature(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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const SSG_slopeParam slopeParam,
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const SSG_VFeatureParam valleyPara,
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SSG_lineFeature* line_features);
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//获取扫描线拐点特征
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SG_APISHARED_EXPORT void sg_getLineCornerFeature(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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const SSG_cornerParam cornerPara, //scale通常取bagH的1/4
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SSG_lineFeature* line_features);
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SG_APISHARED_EXPORT void sg_getLineCornerFeature_BQ(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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double refSteppingZ,
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const SSG_cornerParam cornerPara,
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std::vector<SSG_basicFeature1D>& line_features);
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/// <summary>
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/// 提取激光线上的特征：跳变、低于z阈值、V及L型，用于粒径检测（PSM)
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/// seg端点：z距离大于门限
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/// nPointIdx被重新定义成Feature类型
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/// 算法流程：
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/// （1）逐点计算前向角和后向角
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/// （2）逐点计算拐角，顺时针为负，逆时针为正
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/// （3）搜索正拐角的极大值。
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/// （4）判断拐角是否为跳变
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/// </summary>
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SG_APISHARED_EXPORT void wd_getLineCornerFeature_PSM(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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const double groundZ,
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const SSG_cornerParam cornerPara,
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SSG_lineFeature* line_features);
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/// <summary>
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/// 提取激光线上的Jumping特征
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/// nPointIdx被重新定义成Feature类型
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/// 算法流程：
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/// （1）逐点计算前向角和后向角
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/// （2）逐点计算拐角，顺时针为负，逆时针为正
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/// （3）搜索正拐角的极大值。
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/// （4）判断拐角是否为跳变
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/// </summary>
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SG_APISHARED_EXPORT void sg_getLineJumpFeature_cornerMethod(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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const SSG_cornerParam cornerPara, //scale通常取bagH的1/4
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std::vector< SSG_basicFeature1D>& jumpFeatures);
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SG_APISHARED_EXPORT void wd_getLineGloveArcs(
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std::vector<SVzNL3DPosition>& lineData,
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int lineIdx,
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const SSG_gloveArcParam arcPara,
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std::vector<SSG_basicFeature1D>& gloveArcs);
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/// 提取激光线上的圆柱形特征
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SG_APISHARED_EXPORT void sg_getLineUpperSemiCircleFeature(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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const double sieveDiameter,
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const SSG_slopeParam slopePara,
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std::vector< SSG_featureSemiCircle>& line_features,
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cv::Mat& holeMask);
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/// <summary>
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/// 提取激光线上的极值点（极大值点和极小值点）
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///
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/// </summary>
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SG_APISHARED_EXPORT void sg_getLineLocalPeaks(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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const double scaleWin,
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std::vector< SSG_basicFeature1D>& localMax,
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std::vector< SSG_basicFeature1D>& localMin);
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SG_APISHARED_EXPORT void sg_getFlatLineLocalPeaks_vector(
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std::vector<SVzNL3DPosition>& lineData,
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int lineIdx,
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const double scaleWin,
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const double minPkHeighth,
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const double holeR,
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std::vector< SSG_basicFeature1D>& localMax);
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SG_APISHARED_EXPORT void sg_getLineDownJumps(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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const double jumpTh,
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std::vector< SSG_basicFeature1D>& downJumps);
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//对feature进行生长
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SG_APISHARED_EXPORT void sg_getFeatureGrowingTrees(
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std::vector<SSG_lineFeature>& lineFeatures,
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std::vector<SSG_featureTree>& trees,
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SSG_treeGrowParam growParam);
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//对feature进行生长:不比较type，只判断位置是否相邻
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SG_APISHARED_EXPORT void wd_getFeatureGrowingTrees_noTypeMatch(
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std::vector<SSG_lineFeature>& lineFeatures,
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std::vector<SSG_featureTree>& feature_trees,
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std::vector<SSG_featureTree>& ending_trees,
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SSG_treeGrowParam growParam);
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SG_APISHARED_EXPORT void sg_lineFeaturesGrowing(
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int lineIdx,
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bool isLastLine,
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std::vector<SSG_basicFeature1D>& features,
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std::vector<SSG_featureTree>& trees,
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SSG_treeGrowParam growParam);
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//SG_APISHARED_EXPORT void sg_getTreeROI(SSG_featureTree* a_tree);
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//对ending进行生长
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SG_APISHARED_EXPORT void sg_getEndingGrowingTrees(
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std::vector<SSG_2DValueI>& lineEndings,
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SVzNL3DLaserLine* laser3DPoints,
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bool isVScan,
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int featureType,
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std::vector<SSG_featureTree>& trees,
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SSG_treeGrowParam growParam);
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//对ending进行生长，垂直扫描时只进行水平生长；水平扫描时只进行垂直生长
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SG_APISHARED_EXPORT void sg_getEndingGrowingTrees_angleCheck(
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std::vector<SSG_2DValueI>& lineEndings,
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SVzNL3DLaserLine* laser3DPoints,
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bool isVScan,
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int featureType,
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std::vector<SSG_featureTree>& trees,
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SSG_treeGrowParam growParam,
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double angleCheckScale);
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//对扫描线上的
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SG_APISHARED_EXPORT void sg_LVFeatureGrowing(
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std::vector<SSG_lineFeature>& lineFeatures,
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std::vector<SSG_featureTree>& trees,
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SSG_bagParam bagParam,
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SSG_treeGrowParam growParam,
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std::vector<SSG_2DValueI>& edgePts_0,
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std::vector<SSG_2DValueI>& edgePts_1);
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SG_APISHARED_EXPORT void sg_peakFeatureGrowing(
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std::vector<std::vector< SSG_basicFeature1D>>& lineFeatures,
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std::vector<SSG_featureTree>& trees,
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SSG_treeGrowParam growParam);
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//semiCircle特征生长
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SG_APISHARED_EXPORT void sg_getFeatureGrowingTrees_semiCircle(
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std::vector< SSG_featureSemiCircle>& lineFeatures,
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const int lineIdx,
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const int lineSize,
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std::vector<SSG_semiCircleFeatureTree>& trees,
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std::vector<SSG_semiCircleFeatureTree>& stopTrees,
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std::vector<SSG_semiCircleFeatureTree>& invalidTrees, //被移除的树，这些树可能将目标分成多个树，从而被移除。
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SSG_treeGrowParam growParam);
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SSG_meanVar _computeMeanVar(double* data, int size);
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///搜索局部最高点（z最小点）。
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///搜索方法：每次步进搜索窗口长度的一半。对局部最高点进行标记，防止被重复记录。
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SG_APISHARED_EXPORT void sg_getLocalPeaks(
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SVzNL3DLaserLine* scanLines,
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int lineNum,
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std::vector<SSG_2DValueI>& peaks,
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SSG_localPkParam searchWin);
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/// <summary>
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/// 区域生长法：以局部最高点作为生长种子进行生长
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/// 生长方法与一般的区域生长不同：以种子点为圆心作圆周扫描，记录扫描到的边界
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/// </summary>
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//SG_APISHARED_EXPORT void sg_peakPolarScan(cv::Mat& edgeMask, SVzNL2DPoint a_peak, SSG_polarScanParam polarScanParam, std::vector< SSG_2DValueI>& rgnContour);
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//从Peak点进行水平垂直扫描得到区域边界
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SG_APISHARED_EXPORT void sg_peakXYScan(
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SVzNL3DLaserLine* laser3DPoints,
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int lineNum,
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cv::Mat& featureEdgeMask,
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SSG_2DValueI a_peak,
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SSG_treeGrowParam growParam,
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SSG_bagParam bagParam,
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bool rgnPtAsEdge,
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std::vector< SSG_lineConotours>& topContour,
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std::vector< SSG_lineConotours>& bottomContour,
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std::vector< SSG_lineConotours>& leftContour,
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std::vector< SSG_lineConotours>& rightContour,
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int* maxEdgeId_top,
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int* maxEdgeId_btm,
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int* maxEdgeId_left,
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int* maxEdgeId_right);
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//取出与给定edgeId相同的边界点
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SG_APISHARED_EXPORT void sg_getContourPts(
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std::vector< SSG_lineConotours>& contour_all,
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int vldEdgeId,
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std::vector< SSG_2DValueI>& contourFilter,
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int* lowLevelFlag);
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//从边界点对中取出与给定edgeId相同的边界点
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SG_APISHARED_EXPORT void sg_getPairingContourPts(
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std::vector<SSG_conotourPair>& contourPairs,
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std::vector<SSG_intPair>& idPairs,
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std::vector< SSG_conotourPair>& contourFilter,
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SVzNLRangeD range,
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bool isTBDir,
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int* lowLevelFlag_0,
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int* lowLevelFlag_1);
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//取出最短距离的边界点
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SG_APISHARED_EXPORT void sg_contourPostProc(
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std::vector< SSG_contourPtInfo>& contour,
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int maxEdgeIdx,
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double sameConturDistTh,
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std::vector< SSG_2DValueI>& contourFilter,
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int sideID,
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int* blockFlag);
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//距离变换
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//input, output均为float型
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SG_APISHARED_EXPORT void sg_distanceTrans(const cv::Mat input, cv::Mat& output, int distType);
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/// <summary>
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/// 以5x5方式寻找localPeaks
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/// </summary>
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/// <param name="input"></param>
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/// <param name="peaks"></param>
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SG_APISHARED_EXPORT void sg_getLocalPeaks_distTransform(
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cv::Mat& input,
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std::vector<SSG_2DValueI>& peaks,
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SSG_localPkParam searchWin);
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/// <summary>
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/// 使用模板法提取直角特征
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/// 水平向下直角特征：拐点左侧deltaZ在一个很小的范围内；拐点右侧deltaY在一个很小的范围内
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/// </summary>
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SG_APISHARED_EXPORT void sg_getLineRigthAngleFeature(
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SVzNL3DPosition* lineData,
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int dataSize,
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int lineIdx,
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const SSG_lineRightAngleParam templatePara_HF,
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const SSG_lineRightAngleParam templatePara_FH,
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const SSG_lineRightAngleParam templatePara_HR,
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const SSG_lineRightAngleParam templatePara_RH,
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SSG_lineFeature* line_features);
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//计算扫描ROI
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SG_APISHARED_EXPORT SVzNL3DRangeD sg_getScanDataROI(
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SVzNL3DLaserLine* laser3DPoints,
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int lineNum);
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//计算扫描ROI: vecotr格式
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SG_APISHARED_EXPORT SVzNL3DRangeD sg_getScanDataROI_vector(
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std::vector< std::vector<SVzNL3DPosition>>& scanLines
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);
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//计算点云的ROI和scale: vecotr格式
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SG_APISHARED_EXPORT SWD_pointCloudPara wd_getPointCloudPara(
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std::vector< std::vector<SVzNL3DPosition>>& scanLines);
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//XY平面直线拟合
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SG_APISHARED_EXPORT void lineFitting(
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std::vector< SVzNL3DPoint>& inliers,
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double* _k,
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double* _b);
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SG_APISHARED_EXPORT SVzNL2DPointD sx_getFootPoint(
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double x0,
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double y0,
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double k,
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double b);
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//Bresenham算法
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SG_APISHARED_EXPORT void drawLine(
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int x0,
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int y0,
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int x1,
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int y1,
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std::vector<SVzNL2DPoint>& pts);
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/// <summary>
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/// 两步法标注
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/// </summary>
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/// <param name="bwImg"> 目标点为“1”， 空白点为“0”</param>
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/// <param name="labImg"> 标注结果。每个点为rgnID, ID从2开始 </param>
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/// <param name="labelRgns"></param>
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SG_APISHARED_EXPORT void SG_TwoPassLabel(
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const cv::Mat& bwImg,
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cv::Mat& labImg,
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std::vector<SSG_Region>& labelRgns,
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int connectivity = 4);
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//计算一个平面调平参数。
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//数据输入中可以有一个地平面和参考调平平面，以最高的平面进行调平
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//旋转矩阵为调平参数，即将平面法向调整为垂直向量的参数
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SG_APISHARED_EXPORT SSG_planeCalibPara sg_getPlaneCalibPara(
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SVzNL3DLaserLine* laser3DPoints,
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int lineNum);
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//计算一个平面调平参数。
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//数据输入中可以有一个地平面和参考调平平面，以最高的平面进行调平
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//旋转矩阵为调平参数，即将平面法向调整为垂直向量的参数
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SG_APISHARED_EXPORT SSG_planeCalibPara sg_getPlaneCalibPara2(
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std::vector< std::vector<SVzNL3DPosition>>& scanLines);
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//计算一个平面调平参数。
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//以数据输入中ROI以内的点进行平面拟合，计算调平参数
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//旋转矩阵为调平参数，即将平面法向调整为垂直向量的参数
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SG_APISHARED_EXPORT SSG_planeCalibPara sg_getPlaneCalibPara_ROIs(
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SVzNL3DLaserLine* laser3DPoints,
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int lineNum,
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std::vector<SVzNL3DRangeD>& ROIs);
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//计算一个平面调平参数。
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//以数据输入中ROI以内的点进行平面拟合，计算调平参数
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//旋转矩阵为调平参数，即将平面法向调整为垂直向量的参数
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SSG_planeCalibPara sg_getPlaneCalibPara2_ROI(
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std::vector< std::vector<SVzNL3DPosition>>& scanLines,
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SVzNL3DRangeD roi);
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// 从旋转矩阵计算欧拉角（Z-Y-X顺序）
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SG_APISHARED_EXPORT SSG_EulerAngles rotationMatrixToEulerZYX(const double R[3][3]);
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// 从欧拉角计算旋转矩阵（Z-Y-X顺序）
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SG_APISHARED_EXPORT void eulerToRotationMatrixZYX(const SSG_EulerAngles& angles, double R[3][3]);
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//相机姿态调平，并去除地面
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///camPoseR为3x3矩阵
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SG_APISHARED_EXPORT void lineDataRT(
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SVzNL3DLaserLine* a_line,
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const double* camPoseR,
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double groundH);
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SG_APISHARED_EXPORT void lineDataRT_vector(
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std::vector< SVzNL3DPosition>& a_line,
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const double* camPoseR,
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double groundH);
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SG_APISHARED_EXPORT void lineDataRT_RGBD(
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SVzNLXYZRGBDLaserLine* a_line,
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const double* camPoseR,
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double groundH);
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SG_APISHARED_EXPORT void sg_pointClustering(
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std::vector< SVzNL3DPosition>& pts,
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double clusterDist,
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std::vector<std::vector< SVzNL3DPosition>>& objClusters //result
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);
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//对栅格化数据进行XY平面上的投影量化，并对量化产生的空白点进行插值
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SG_APISHARED_EXPORT void pointClout2DProjection(
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std::vector< std::vector<SVzNL3DPosition>>& gridScanData,
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SVzNLRangeD x_range,
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SVzNLRangeD y_range,
|
||
double scale,
|
||
int edgeSkip,
|
||
double inerPolateDistTh, //插值阈值。大于此阈值的不进行量化插值
|
||
cv::Mat& projectionData,//投影量化数据，初始化为一个极大值1e+6
|
||
cv::Mat& backIndexing //标记坐标索引，用于回找3D坐标
|
||
);
|
||
|
||
//分水岭算法
|
||
SG_APISHARED_EXPORT void watershed(SWD_waterShedImage& img);
|
||
// 根据输入的种子点进行分水岭算法
|
||
SG_APISHARED_EXPORT void wd_seedWatershed(
|
||
SWD_waterShedImage& img,
|
||
std::vector<SSG_2DValueI>& watershedSeeds, //种子点
|
||
int maxLevel, //最大水位
|
||
int startMakerID //起始Marker的ID
|
||
); |