i/rtabmap
1
0
Fork 0
mirror of https://github.com/introlab/rtabmap.git synced 2026-09-02 09:30:25 +08:00
Code Issues Packages Projects Releases Wiki Activity

Added SuperGlue support (Vis/CorNNType=6). Added rtabmap-matcher tool. DBViewer: show matches/inliers when refine also fails. SIFT: make sift always available on OpenCV 4.3.0 (#538). Parameters: changed SPTorch prefix to SuperPoint, replaced Vis/CorCrossCheck by Vis/CorNNType=5.

Browse Source
This commit is contained in:
matlabbe
2020-05-09 21:13:41 -04:00
parent abc3ebee8c
commit 91285e5e97
35 changed files with 1554 additions and 249 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
corelib/include/rtabmap/core/CameraModel.h
View File

@@ -50,7 +50,7 @@ public:
const cv::Mat & D,
const cv::Mat & R,
const cv::Mat & P,
const Transform & localTransform = Transform::getIdentity());
const Transform & localTransform = Transform(0,0,1,0, -1,0,0,0, 0,-1,0,0));
// minimal
CameraModel(
@@ -58,7 +58,7 @@ public:
double fy,
double cx,
double cy,
const Transform & localTransform = Transform::getIdentity(),
const Transform & localTransform = Transform(0,0,1,0, -1,0,0,0, 0,-1,0,0),
double Tx = 0.0f,
const cv::Size & imageSize = cv::Size(0,0));
// minimal to be saved
@@ -68,7 +68,7 @@ public:
double fy,
double cx,
double cy,
const Transform & localTransform = Transform::getIdentity(),
const Transform & localTransform = Transform(0,0,1,0, -1,0,0,0, 0,-1,0,0),
double Tx = 0.0f,
const cv::Size & imageSize = cv::Size(0,0));

31
corelib/include/rtabmap/core/Features2d.h
View File

@@ -116,6 +116,37 @@ public:
kFeatureKaze=9, //new 0.13.2
kFeatureOrbOctree=10, //new 0.19.2
kFeatureSuperPointTorch=11}; //new 0.19.7
static std::string typeName(Type type)
{
switch(type){
case kFeatureSurf:
return "SURF";
case kFeatureSift:
return "SIFT";
case kFeatureOrb:
return "ORB";
case kFeatureFastFreak:
return "FAST+FREAK";
case kFeatureFastBrief:
return "FAST+BRIEF";
case kFeatureGfttFreak:
return "GFTT+Freak";
case kFeatureGfttBrief:
return "GFTT+Brief";
case kFeatureBrisk:
return "BRISK";
case kFeatureGfttOrb:
return "GFTT+ORB";
case kFeatureKaze:
return "KAZE";
case kFeatureOrbOctree:
return "ORB-OCTREE";
case kFeatureSuperPointTorch:
return "SUPERPOINT";
default:
return "Unknown";
}
}
static Feature2D * create(const ParametersMap & parameters = ParametersMap());
static Feature2D * create(Feature2D::Type type, const ParametersMap & parameters = ParametersMap()); // for convenience

18
corelib/include/rtabmap/core/Parameters.h
View File

@@ -324,11 +324,16 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(KAZE, NOctaveLayers, int, 4, "Default number of sublevels per scale level.");
RTABMAP_PARAM(KAZE, Diffusivity, int, 1, "Diffusivity type: 0=DIFF_PM_G1, 1=DIFF_PM_G2, 2=DIFF_WEICKERT or 3=DIFF_CHARBONNIER.");
RTABMAP_PARAM_STR(SPTorch, ModelPath, "", "[Required] Path to pre-trained weights Torch file of SuperPoint (*.pt).");
RTABMAP_PARAM(SPTorch, Threshold, float, 0.200, "Detector response threshold to accept keypoint.");
RTABMAP_PARAM(SPTorch, NMS, bool, true, "If true, non-maximum suppression is applied to detected keypoints.");
RTABMAP_PARAM(SPTorch, MinDistance, int, 4, uFormat("[%s=true] Minimum distance (pixels) between keypoints.", kSPTorchNMS().c_str()));
RTABMAP_PARAM(SPTorch, Cuda, bool, false, "Use Cuda device for Torch, otherwise CPU device is used by default.");
RTABMAP_PARAM_STR(SuperPoint, ModelPath, "", "[Required] Path to pre-trained weights Torch file of SuperPoint (*.pt).");
RTABMAP_PARAM(SuperPoint, Threshold, float, 0.010, "Detector response threshold to accept keypoint.");
RTABMAP_PARAM(SuperPoint, NMS, bool, true, "If true, non-maximum suppression is applied to detected keypoints.");
RTABMAP_PARAM(SuperPoint, NMSRadius, int, 4, uFormat("[%s=true] Minimum distance (pixels) between keypoints.", kSuperPointNMS().c_str()));
RTABMAP_PARAM(SuperPoint, Cuda, bool, true, "Use Cuda device for Torch, otherwise CPU device is used by default.");
RTABMAP_PARAM_STR(SuperGlue, Path, "", "Path to python script file \"rtabmap_superglue.py\" (rtabmap/corelib/src/superglue_pytorch/rtabmap_superglue.py) copied in SuperGlue's Git folder.");
RTABMAP_PARAM(SuperGlue, Iterations, int, 20, "Sinkhorn iterations.");
RTABMAP_PARAM(SuperGlue, MatchThreshold, float, 0.2, "");
RTABMAP_PARAM(SuperGlue, Cuda, bool, true, "");
// BayesFilter
RTABMAP_PARAM(Bayes, VirtualPlacePriorThr, float, 0.9, "Virtual place prior");
@@ -604,9 +609,8 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Vis, GridRows, int, 1, uFormat("Number of rows of the grid used to extract uniformly \"%s / grid cells\" features from each cell.", kVisMaxFeatures().c_str()));
RTABMAP_PARAM(Vis, GridCols, int, 1, uFormat("Number of columns of the grid used to extract uniformly \"%s / grid cells\" features from each cell.", kVisMaxFeatures().c_str()));
RTABMAP_PARAM(Vis, CorType, int, 0, "Correspondences computation approach: 0=Features Matching, 1=Optical Flow");
RTABMAP_PARAM(Vis, CorNNType, int, 1, uFormat("[%s=0] kNNFlannNaive=0, kNNFlannKdTree=1, kNNFlannLSH=2, kNNBruteForce=3, kNNBruteForceGPU=4. Used for features matching approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorNNType, int, 1, uFormat("[%s=0] kNNFlannNaive=0, kNNFlannKdTree=1, kNNFlannLSH=2, kNNBruteForce=3, kNNBruteForceGPU=4, BruteForceCrossCheck=5, SuperGlue=6. Used for features matching approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorNNDR, float, 0.6, uFormat("[%s=0] NNDR: nearest neighbor distance ratio. Used for knn features matching approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorCrossCheck, bool, false, uFormat("[%s=0] If true, brute force crosscheck matching is done instead of knn matching approach (%s).", kVisCorType().c_str(), kVisCorNNDR().c_str()));
RTABMAP_PARAM(Vis, CorGuessWinSize, int, 20, uFormat("[%s=0] Matching window size (pixels) around projected points when a guess transform is provided to find correspondences. 0 means disabled.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorGuessMatchToProjection, bool, false, uFormat("[%s=0] Match frame's corners to source's projected points (when guess transform is provided) instead of projected points to frame's corners.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowWinSize, int, 16, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));

15
corelib/include/rtabmap/core/RegistrationVis.h
View File

@@ -37,6 +37,10 @@ namespace rtabmap {
class Feature2D;
#ifdef RTABMAP_SUPERGLUE_PYTORCH
class SuperGlue;
#endif
// Visual registration
class RTABMAP_EXP RegistrationVis : public Registration
{
@@ -50,6 +54,11 @@ public:
float getInlierDistance() const {return _inlierDistance;}
int getIterations() const {return _iterations;}
int getMinInliers() const {return _minInliers;}
int getNNType() const {return _nnType;}
float getNNDR() const {return _nndr;}
int getEstimationType() const {return _estimationType;}
const Feature2D * getDetector() const {return _detectorFrom;}
protected:
virtual Transform computeTransformationImpl(
@@ -78,8 +87,8 @@ private:
int _flowIterations;
float _flowEps;
int _flowMaxLevel;
bool _bfCrossCheck;
float _nndr;
int _nnType;
int _guessWinSize;
bool _guessMatchToProjection;
int _bundleAdjustment;
@@ -92,6 +101,10 @@ private:
Feature2D * _detectorFrom;
Feature2D * _detectorTo;
#ifdef RTABMAP_SUPERGLUE_PYTORCH
SuperGlue * _superGlueMatcher;
#endif
};
}

6
corelib/include/rtabmap/core/StereoCameraModel.h
View File

@@ -43,7 +43,7 @@ public:
const cv::Size & imageSize2,
const cv::Mat & K2, const cv::Mat & D2, const cv::Mat & R2, const cv::Mat & P2,
const cv::Mat & R, const cv::Mat & T, const cv::Mat & E, const cv::Mat & F,
const Transform & localTransform = Transform::getIdentity());
const Transform & localTransform = Transform(0,0,1,0, -1,0,0,0, 0,-1,0,0));
// if R and T are not null, left and right camera models should be valid to be rectified.
StereoCameraModel(
@@ -68,7 +68,7 @@ public:
double cx,
double cy,
double baseline,
const Transform & localTransform = Transform::getIdentity(),
const Transform & localTransform = Transform(0,0,1,0, -1,0,0,0, 0,-1,0,0),
const cv::Size & imageSize = cv::Size(0,0));
//minimal to be saved
StereoCameraModel(
@@ -78,7 +78,7 @@ public:
double cx,
double cy,
double baseline,
const Transform & localTransform = Transform::getIdentity(),
const Transform & localTransform = Transform(0,0,1,0, -1,0,0,0, 0,-1,0,0),
const cv::Size & imageSize = cv::Size(0,0));
virtual ~StereoCameraModel() {}

17
corelib/include/rtabmap/core/VWDictionary.h
View File

@@ -55,6 +55,23 @@ public:
kNNUndef};
static const int ID_START;
static const int ID_INVALID;
static std::string nnStrategyName(NNStrategy strategy)
{
switch(strategy) {
case kNNFlannNaive:
return "FLANN NAIVE";
case kNNFlannKdTree:
return "FLANN KD-TREE";
case kNNFlannLSH:
return "FLANN LSH";
case kNNBruteForce:
return "BRUTE FORCE";
case kNNBruteForceGPU:
return "BRUTE FORCE GPU";
default:
return "Unknown";
}
}
public:
VWDictionary(const ParametersMap & parameters = ParametersMap());

3
corelib/include/rtabmap/core/util3d_features.h
View File

@@ -85,7 +85,8 @@ std::map<int, cv::Point3f> RTABMAP_EXP generateWords3DMono(
float ransacParam1 = 3.0f,
float ransacParam2 = 0.99f,
const std::map<int, cv::Point3f> & refGuess3D = std::map<int, cv::Point3f>(),
double * variance = 0);
double * variance = 0,
std::vector<int> * matchesOut = 0);
std::multimap<int, cv::KeyPoint> RTABMAP_EXP aggregate(
const std::list<int> & wordIds,