[software] ImageMatching : rename and move tree to option param

src/aliceVision/matching/io.cpp

@@ -279,8 +279,6 @@ bool Load(
 
   if(maxNbMatches > 0)
     filterTopMatches(matches, maxNbMatches, minNbMatches);
-  if(minNbMatches <= maxNbMatches)
-    filterTopMatches(matches, maxNbMatches, minNbMatches);
 
   ALICEVISION_LOG_TRACE("Matches per image pair (after filtering):");
   logMatches(matches);

src/aliceVision/sfm/pipeline/structureFromKnownPoses/StructureEstimationFromKnownPoses.cpp

@@ -61,11 +61,11 @@ void PointsToMat(
 void StructureEstimationFromKnownPoses::run(SfMData& sfmData,
   const PairSet& pairs,
   const feature::RegionsPerView& regionsPerView,
-  double GeometricErrorMax)
+  double geometricErrorMax)
 {
   sfmData.structure.clear();
 
-  match(sfmData, pairs, regionsPerView, GeometricErrorMax);
+  match(sfmData, pairs, regionsPerView, geometricErrorMax);
   filter(sfmData, pairs, regionsPerView);
   triangulate(sfmData, regionsPerView);
 }
@@ -76,7 +76,7 @@ void StructureEstimationFromKnownPoses::run(SfMData& sfmData,
 void StructureEstimationFromKnownPoses::match(const SfMData& sfmData,
   const PairSet& pairs,
   const feature::RegionsPerView& regionsPerView,
-  double GeometricErrorMax)
+  double geometricErrorMax)
 {
   boost::progress_display my_progress_bar( pairs.size(), std::cout,
     "Compute pairwise fundamental guided matching:\n" );
@@ -140,7 +140,7 @@ void StructureEstimationFromKnownPoses::match(const SfMData& sfmData,
             regionsPerView.getRegions(it->second, descType),
             iterIntrinsicR->second->w(), iterIntrinsicR->second->h(),
             //descType,
-            Square(GeometricErrorMax), Square(0.8),
+            Square(geometricErrorMax), Square(0.8),
             matches
           );
       #endif

src/aliceVision/sfm/pipeline/structureFromKnownPoses/StructureEstimationFromKnownPoses.hpp

@@ -22,15 +22,15 @@ class StructureEstimationFromKnownPoses
   void run(sfmData::SfMData& sfmData,
     const PairSet& pairs,
     const feature::RegionsPerView& regionsPerView,
-    double GeometricErrorMax);
+    double geometricErrorMax);
 
 public:
 
   /// Use guided matching to find corresponding 2-view correspondences
   void match(const sfmData::SfMData& sfmData,
     const PairSet& pairs,
     const feature::RegionsPerView& regionsPerView,
-    double GeometricErrorMax);
+    double geometricErrorMax);
 
   /// Filter inconsistent correspondences by using 3-view correspondences on view triplets
   void filter(

src/software/pipeline/main_computeStructureFromKnownPoses.cpp

@@ -37,7 +37,7 @@ int main(int argc, char **argv)
   std::string sfmDataFilename;
   std::string outSfMDataFilename;
   std::vector<std::string> featuresFolders;
-  double GeometricErrorMax = 5.0;
+  double geometricErrorMax = 5.0;
   // user optional parameters
 
   std::string describerTypesName = feature::EImageDescriberType_enumToString(feature::EImageDescriberType::SIFT);
@@ -60,7 +60,7 @@ int main(int argc, char **argv)
       feature::EImageDescriberType_informations().c_str())
     ("matchesFolders,m", po::value<std::vector<std::string>>(&matchesFolders)->multitoken()->required(),
       "Path to folder(s) in which computed matches are stored.")
-    ("GeometricErrorMax", po::value<double>(&GeometricErrorMax)->default_value(GeometricErrorMax),
+    ("GeometricErrorMax", po::value<double>(&geometricErrorMax)->default_value(geometricErrorMax),
         "Maximum error (in pixels) allowed for features matching during geometric verification for known camera poses. "
         "If set to 0 it lets the ACRansac select an optimal value.");
 

src/software/pipeline/main_imageMatching.cpp

@@ -553,8 +553,6 @@ int main(int argc, char** argv)
   std::string sfmDataFilenameA;
   /// the folder(s) containing the extracted features with their associated descriptors
   std::vector<std::string> featuresFolders;
-  /// the filename of the voctree
-  std::string treeName="Vocabulary Tree";
   /// the file in which to save the results
   std::string outputFile;
 
@@ -568,8 +566,10 @@ int main(int argc, char** argv)
   std::size_t numImageQuery = 50;
   /// the number of neighbors to retrieve for each image in Sequential Mode
   std::size_t numImageQuerySequential = 50;
+  /// the filename of the voctree
+  std::string treeFilepath;
   /// the filename for the voctree weights
-  std::string weightsName;
+  std::string weightsFilepath;
   /// flag for the optional weights file
   bool withWeights = false;
 
@@ -598,9 +598,6 @@ int main(int argc, char** argv)
       "SfMData file.")
     ("featuresFolders,f", po::value<std::vector<std::string>>(&featuresFolders)->multitoken()->required(),
       "Path to folder(s) containing the extracted features.")
-    ("tree,t", po::value<std::string>(&treeName)->default_value(treeName),
-      "Input file path of the vocabulary tree. This file can be generated by createVoctree. "
-      "This software is intended to be used with a generic, pre-trained vocabulary tree.")
     ("output,o", po::value<std::string>(&outputFile)->required(),
       "Filepath to the output file with the list of selected image pairs.");
 
@@ -618,7 +615,10 @@ int main(int argc, char** argv)
     ("nbNeighbors", po::value<std::size_t>(&numImageQuerySequential)->default_value(numImageQuerySequential),
       "The number of neighbors to retrieve for each image (If 0 it will "
       "retrieve all the neighbors).")
-    ("weights,w", po::value<std::string>(&weightsName),
+    ("tree,t", po::value<std::string>(&treeFilepath)->default_value(treeFilepath),
+      "Input file path of the vocabulary tree. This file can be generated by 'createVoctree'. "
+      "This software is intended to be used with a generic, pre-trained vocabulary tree.")
+    ("weights,w", po::value<std::string>(&weightsFilepath)->default_value(weightsFilepath),
       "Input name for the vocabulary tree weight file, if not provided all voctree leaves will have the same weight.");
 
   po::options_description multiSfMParams("Multiple SfM");
@@ -731,7 +731,7 @@ int main(int argc, char** argv)
     }
     case EImageMatchingMethod::VOCABULARYTREE:
     {
-      conditionVocTree(treeName, withWeights, weightsName, matchingMode,featuresFolders, sfmDataA, nbMaxDescriptors, sfmDataFilenameA, sfmDataB,
+      conditionVocTree(treeFilepath, withWeights, weightsFilepath, matchingMode,featuresFolders, sfmDataA, nbMaxDescriptors, sfmDataFilenameA, sfmDataB,
                        sfmDataFilenameB, useMultiSfM, descriptorsFilesA,  numImageQuery, selectedPairs);
       break;
     }
@@ -743,7 +743,7 @@ int main(int argc, char** argv)
     case EImageMatchingMethod::SEQUENTIAL_AND_VOCABULARYTREE:
     {
       generateSequentialMatches(sfmDataA, numImageQuerySequential, selectedPairs);
-      conditionVocTree(treeName, withWeights, weightsName, matchingMode,featuresFolders, sfmDataA, nbMaxDescriptors, sfmDataFilenameA, sfmDataB,
+      conditionVocTree(treeFilepath, withWeights, weightsFilepath, matchingMode,featuresFolders, sfmDataA, nbMaxDescriptors, sfmDataFilenameA, sfmDataB,
                        sfmDataFilenameB, useMultiSfM, descriptorsFilesA,  numImageQuery, selectedPairs);
       break;
     }