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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,137 @@ | ||
| function clusterCallback(jobID) | ||
| % Predict object pose between object model and segmentation point cloud by | ||
| % running RANSAC-based geometric registration between two sets of 3D | ||
| % keypoints and their descriptors | ||
| % | ||
| % --------------------------------------------------------- | ||
| % Copyright (c) 2016, Andy Zeng | ||
| % | ||
| % This file is part of the 3DMatch Toolbox and is available | ||
| % under the terms of the Simplified BSD License provided in | ||
| % LICENSE. Please retain this notice and LICENSE if you use | ||
| % this file (or any portion of it) in your project. | ||
| % --------------------------------------------------------- | ||
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| % Configuration options (change me) | ||
| descriptorName = '3dmatch'; | ||
| dataPath = '../../data/apc'; | ||
| addpath(genpath('../../core/external')); | ||
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| % List scenarios | ||
| scenarioIdx = jobID - 1; | ||
| scenarioList = dir(fullfile(dataPath,'scenarios/00*')); | ||
| if scenarioIdx >= length(scenarioList) | ||
| return; | ||
| end | ||
| scenarioPath = fullfile(dataPath,'scenarios',sprintf('%06d',scenarioIdx)); | ||
| fprintf('%s\n',scenarioPath); | ||
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| % Check if pose prediction file already exists | ||
| predictedRtFile = fullfile(scenarioPath,sprintf('ransac.%s.model2segm.txt',descriptorName)); | ||
| if exist(predictedRtFile,'file') | ||
| return; | ||
| end | ||
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| fileID = fopen(fullfile(scenarioPath,'info.txt'),'r'); | ||
| sceneName = fscanf(fileID,'scene: %s\n'); | ||
| objectName = fscanf(fileID,'object: %s\n'); | ||
| fclose(fileID); | ||
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| % Load segmentation from scene point cloud and its TDF voxel volume | ||
| segmPointCloud = pcread(fullfile(scenarioPath,'segmentation.ply')); | ||
| matchSegmVoxFile = fullfile(scenarioPath,'segmentation.TDF.bin'); | ||
| fileID = fopen(matchSegmVoxFile,'rb'); | ||
| matchSegmVoxSize = fread(fileID,3,'single'); | ||
| matchSegmOrigin = fread(fileID,3,'single'); | ||
| segm2model = reshape(fread(fileID,16,'single'),4,4)'; | ||
| matchSegmVox = fread(fileID,'single'); | ||
| fclose(fileID); | ||
| matchSegmVox = reshape(matchSegmVox,matchSegmVoxSize'); | ||
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| % Load object model point cloud and its TDF voxel volume | ||
| matchModelVoxFile = fullfile(dataPath,'objects',sprintf('%s.TDF.bin',objectName)); | ||
| modelPointCloud = pcread(fullfile(dataPath,'objects',sprintf('%s.ply',objectName))); | ||
| fileID = fopen(matchModelVoxFile,'rb'); | ||
| matchModelVoxSize = fread(fileID,3,'single'); | ||
| matchModelOrigin = fread(fileID,3,'single'); | ||
| matchModelVox = fread(fileID,'single'); | ||
| fclose(fileID); | ||
| matchModelVox = reshape(matchModelVox,matchModelVoxSize'); | ||
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| % Load segmentation keypoints | ||
| segmKeypointsFile = fullfile(scenarioPath,'segmentation.keypoints.bin'); | ||
| fileID = fopen(segmKeypointsFile,'rb'); | ||
| segmNumKeypoints = fread(fileID,1,'single'); | ||
| segmKeypointsCamData = fread(fileID,'single'); | ||
| fclose(fileID); | ||
| segmKeypointsCam = reshape(segmKeypointsCamData,3,segmNumKeypoints)'; | ||
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| % Load model keypoints | ||
| modelKeypointsFile = fullfile(dataPath,'objects',sprintf('%s.keypoints.bin',objectName)); | ||
| fileID = fopen(modelKeypointsFile,'rb'); | ||
| modelNumKeypoints = fread(fileID,1,'single'); | ||
| modelKeypointsCamData = fread(fileID,'single'); | ||
| fclose(fileID); | ||
| modelKeypointsCam = reshape(modelKeypointsCamData,3,modelNumKeypoints)'; | ||
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| % Load segmentation keypoint descriptors | ||
| fileID = fopen(fullfile(scenarioPath,sprintf('segmentation.keypoints.%s.descriptors.bin',descriptorName)),'rb'); | ||
| segmKeypointDescriptorsData = fread(fileID,'single'); | ||
| segmNumKeypoints = segmKeypointDescriptorsData(1); | ||
| segmDescriptorSize = segmKeypointDescriptorsData(2); | ||
| fclose(fileID); | ||
| segmKeypointDescriptors = reshape(segmKeypointDescriptorsData(3:end),segmDescriptorSize,segmNumKeypoints)'; | ||
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| % Load model keypoint descriptors | ||
| fileID = fopen(fullfile(dataPath,'objects',sprintf('%s.keypoints.%s.descriptors.bin',objectName,descriptorName)),'rb'); | ||
| modelKeypointDescriptorsData = fread(fileID,'single'); | ||
| modelNumKeypoints = modelKeypointDescriptorsData(1); | ||
| modelDescriptorSize = modelKeypointDescriptorsData(2); | ||
| fclose(fileID); | ||
| modelKeypointDescriptors = reshape(modelKeypointDescriptorsData(3:end),modelDescriptorSize,modelNumKeypoints)'; | ||
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| % Find mutually closest keypoints in descriptor space | ||
| modelKDT = KDTreeSearcher(modelKeypointDescriptors); | ||
| segmKDT = KDTreeSearcher(segmKeypointDescriptors); | ||
| nnSegmIdx = knnsearch(modelKDT,segmKeypointDescriptors); | ||
| nnModelIdx = knnsearch(segmKDT,modelKeypointDescriptors); | ||
| matchModelIdx = find((1:size(nnModelIdx,1))' == nnSegmIdx(nnModelIdx)); | ||
| modelKeypointsCam = modelKeypointsCam(matchModelIdx,:); | ||
| segmKeypointsCam = segmKeypointsCam(nnModelIdx(matchModelIdx),:); | ||
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| % Use RANSAC to estimate rigid transformation from model to segmentation | ||
| try | ||
| [estModel2SegmRt, inliers] = ransacfitRt([segmKeypointsCam';modelKeypointsCam'], 0.05, 0); | ||
| catch | ||
| estModel2SegmRt = [1,0,0,0;0,1,0,0;0,0,1,0]; | ||
| fprintf(' Broken\n'); | ||
| end | ||
| estModel2SegmRt = [estModel2SegmRt;[0,0,0,1]]; | ||
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| % % Visualize results | ||
| % checkObjModelPts = estModel2SegmRt(1:3,1:3) * modelPointCloud.Location' + repmat(estModel2SegmRt(1:3,4),1,size(modelPointCloud.Location',2)); | ||
| % checkObjSegmPts = segmPointCloud.Location'; | ||
| % pcwrite(pointCloud([checkObjModelPts';checkObjSegmPts'],'Color',[repmat(uint8([0,0,255]),size(checkObjModelPts,2),1);repmat(uint8([255,0,0]),size(checkObjSegmPts,2),1)]),'check','PLYformat','binary'); | ||
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| % Save results to pose prediction file | ||
| fileID = fopen(predictedRtFile,'w'); | ||
| for i = 1:4 | ||
| fprintf(fileID,'%15.8e\t',estModel2SegmRt(i,:)); | ||
| fprintf(fileID,'\n'); | ||
| end | ||
| fclose(fileID); | ||
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| end | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,28 @@ | ||
| #!/bin/bash | ||
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| export PATH=$PATH:/usr/local/cuda/bin | ||
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| if uname | grep -q Darwin; then | ||
| CUDA_LIB_DIR=/usr/local/cuda/lib | ||
| CUDNN_LIB_DIR=/usr/local/cudnn/v5.1/lib | ||
| elif uname | grep -q Linux; then | ||
| CUDA_LIB_DIR=/usr/local/cuda/lib64 | ||
| CUDNN_LIB_DIR=/usr/local/cudnn/v5.1/lib64 | ||
| fi | ||
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| CUDNN_INC_DIR=/usr/local/cudnn/v5.1/include | ||
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| # if use opencv, add this into the command line | ||
| # `pkg-config --cflags --libs opencv` | ||
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| nvcc -std=c++11 -O3 -o get3DMatchDescriptors get3DMatchDescriptors.cu -I/usr/local/cuda/include -I$CUDNN_INC_DIR -L$CUDA_LIB_DIR -L$CUDNN_LIB_DIR -lcudart -lcublas -lcudnn -lcurand -D_MWAITXINTRIN_H_INCLUDED `pkg-config --cflags --libs opencv` | ||
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