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Copy the cloud to the heap and return a smart pointer Note that deep copy is performed, so avoid using this function on non-empty clouds. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Would this be possible using a custom DALI function? it can specify the total number of points in the cloud (equal with POINTS see below) for unorganized datasets; it can specify the width (total number of points in a row) of an organized point cloud dataset. 3. Use the event name in methods like addEventListener(), or set an event handler property. Anyone know why the image file is not being created? It can be used as a portable drop-in replacement for built in data loaders and data iterators in popular deep learning frameworks. bicubic, bilinear) but I don't know if these are built into canvas or not. We shall see how to remove the Event Listener from the element. Why don't math grad schools in the U.S. use entrance exams? Features such as prefetching, parallel execution, and batch processing Form e dati della UI; 78. Resize, crop and save is completely a different need from drag and dropping elements. In the future there may be a query string parameter to specify the default theme. How to Crop Image Size in React Js App. How to use it: 1. The locale file .js can be optionally included for translating for your language if needed.. For example, to create a point cloud that holds 4 random XYZ data points, use: The PointCloud class contains the following elements: Definition at line 53 of file projection_matrix.h. Then, you can use the transform tool to resize your image, as shown below: Check out this feature on the PhotoEditorSDK demo page. Use this to show an error message dialog box, optionally with expandable error details. But actually it will show a prompt to the user to change the language, because the application needs to reload to apply the change. Define this function to tell JS Paint how to save a file. Referenced by pcl::compute3DCentroid(), pcl::computeNDCentroid(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::PCDWriter::writeASCII(), and pcl::PCDWriter::writeBinary(). How to use it: 1. There's no special API for this at the moment. Try scribbling with the Free-Form Select tool and then doing Image > Invert. This function takes a snapshot of the canvas, and some other state, and then calls the actionFunction function. The file will appear in a dialog box with the delimiter already automatically selected, and the text divided by Excel according to the data stored in the .csv file.. Once you select one, you can click on the folder icon to browse to the desired library: Let us get to see some of the Common Event Listeners, Load: when the page loads Click: when users click on something on the page Mouseover: when users hover their mouse over the specified element. React js image resize tutorial; In this quick guide, we will learn how to crop an image in React js app using the react image crop package. Definition at line 466 of file point_cloud.h. DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the Note the inversion of control here: controllers: home.js returns views/index.html; upload.js handles upload, store, display and When you release your image file in the drag area, immediately the preview of that image will appear. Select the file to be imported, and then click Import. And this is before the "submit" button on the form has been pressed so the image almost certainly resides Client side. Definition at line 401 of file point_cloud.h. FileInput supports configuration of the bootstrap library version so that you can use this either with any Bootstrap version 3.x and above. You can also upload an image by clicking on the browse file button. Definition at line 322 of file point_cloud.h. Additionally, DALI relies on its own execution engine, built to maximize the throughput Remember to save with. I am trying to let users add and upload an image to firebase. 2. Multiplayer support currently relies on Firebase, There's already a query string parameter to load from a URL: But this won't set up the file handle for saving. Obtain the point given by the (column, row) coordinates. Are you sure you want to create this branch? It creates an entry in the history so it can be undone. Definition at line 536 of file point_cloud.h. Definition at line 563 of file point_cloud.h. The API is new, and parts of it have not been designed at all. We will show you how to set or update the height and width of an image in react js after upload, and we will primarily crop the image in react app. How to use it: 1. In addition, the deep learning frameworks have multiple data pre-processing implementations, Saving as JPEG will introduce artifacts that cause problems when using the Fill tool or transparent selections. More bool is_dense True if no points are invalid (e.g., have NaN or Inf values). Controlli e valori; 79. Definition at line 435 of file point_cloud.h. There's a black and white mode with patterns instead of colors in the palette, This will resize each browser version cell to be relative to the amount of support it has for the selected usage source. Form e dati della UI; 78. You signed in with another tab or window. Collectives on Stack Overflow. Also inherits properties from its parent Event.. ProgressEvent.lengthComputable Read only . Begin the first step with installing the new react application using the npx create react cli command. use npm run dev to start a live-reloading server. In the future there may be a query string parameter to specify the default language. 3 Begin the first step with installing the new react application using the npx create react cli command. 1. The image is displayed properly in the img element but the File command does not create the myfile.jpg image file. Also provides a simple image pan functionality which which allows to move an image via mouse drag or touch swipe. Only one backup per image tho, which doesn't give you a lot of safety. Full clipboard support in the web app requires a browser supporting the Async Clipboard API w/ Images, namely Chrome 76+ at the time of writing. It's very easy, just wrap your action in a call to undoable. But we want to undo more than three actions. Use this to change the look of the application. Default Value: 'jpeg,jpg,jpe,jfi,jif,jfif,png,gif,bmp,webp' Possible Values: A list of valid web image file extensions. It can be used as a portable drop-in replacement Copyright 2018-2022, NVIDIA Corporation. PointCloud represents the base class in PCL for storing collections of 3D points. Which image file formats are recognized and placed in an img element by the Paste and PowerPaste smart_paste functionality. It is fired once the image is fully loaded. If "Write" is marked with , the format will appear in the file type dropdown but may not work when you try to save. Accelerates image classification (ResNet-50), object detection (SSD) workloads as well as ASR models (Jasper, RNN-T). Run npm run accept to accept any visual changes. Definition at line 509 of file point_cloud.h. If you define only systemHooks.setWallpaperCentered, JS Paint will attempt to guess your screen's dimensions and tile the image, applying it by calling your systemHooks.setWallpaperCentered function. Below is a list of all the APIs and interfaces (object types) that you may be able to use while developing your Web app or site. 2. Anyone know why the image file is not being created? Definition at line 471 of file point_cloud.h. Definition at line 480 of file point_cloud.h. 3 IE9 and below will work as a normal file input, and will not support multiple file selection or the HTML 5 FileReader API. Try it out! routes/web.js: defines routes for endpoints that is called from views, use controllers to handle Q: Can I use DALI in the Triton server through a Python model? When writing code for the Web, there are a large number of Web APIs available. I love to write on JavaScript, ECMAScript, React, Angular, Vue, Laravel. // If you setState the crop in here you should return false. You can use the Text tool at any zoom level (and it previews the exact pixels that will end up on the canvas). Frequently asked questions about MDN Plus. BCD tables only load in the browser with JavaScript enabled. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. This is used for opening images and palettes. Once you have a concept of a file handle, you can implement file pickers using the system hooks, and functions to read and write files. Sunshine!!. Definition at line 472 of file point_cloud.h. This is basically ready for release, but as of yet unreleased. When downloading a resource using HTTP, this is the Content-Length (the size of the body of the message), and doesn't include the headers and other overhead. Except where otherwise noted, the PointClouds.org web pages are licensed under Creative Commons Attribution 3.0. It provides a 2.1 The OpenCSV is simple and easy to use CSV parser for Java. You can also upload an image by clicking on the browse file button. routes/index.js: defines routes for endpoints that is called from views, use controllers to handle requests. FileReader library: After the installation, we. Definition at line 211 of file point_cloud.h. or a measly 50 in Windows 7), Automatically keeps a backup of your image. 77. So let's look at how to upload and retrieve images in ASP. Use Git or checkout with SVN using the web URL. Definition at line 283 of file point_cloud.h. Definition at line 468 of file point_cloud.h. Connect and share knowledge within a single location that is structured and easy to search. Make sure any layout-important styles go in layout.css. We want to edit transparent images. Step 1: Set Up New React App Step 2: Add React Image Crop Package Step 3: Implement Image Resizing in React Step 4: Update App Js File Step 5: Start React App Set Up New React App. but data copied from JS Paint can only be pasted into other instances of JS Paint. Anyone know why the image file is not being created? Sunshine!!. Q: Are there any examples of using DALI for volumetric data? It contains information about the acquisition time. collection of highly optimized building blocks for loading and processing Definition at line 588 of file point_cloud.h. App has been created, next, go inside the project. A boolean flag indicating if the total work to be done, and the amount of work already done, by the underlying process is calculable. Load, scroll e resize: eventi di "interfaccia" 73. For Internet Explorer, one must use IE versions 10 and above. I don't understand the use of diodes in this diagram, Sci-Fi Book With Cover Of A Person Driving A Ship Saying "Look Ma, No Hands!". After starting the development server, you may see the app on the browser: In this stalwart tutorial, we profoundly learned how to create the image resize component for cropping and resizing the image size in react js application using the third party package called react image resize. You can apply image transformations like Flip/Rotate, Stretch/Skew or Invert (in the Image menu) either to the whole image or to a selection. The file will appear in a dialog box with the delimiter already automatically selected, and the text divided by Excel according to the data stored in the .csv file.. Once you select one, you can click on the folder icon to browse to the desired library: Q: How easy is it to integrate DALI with existing pipelines such as PyTorch Lightning? Learn more about Collectives If you don't specify systemHooks.setWallpaperCentered, JS Paint will default to saving a file ( wallpaper.png) using systemHooks.showSaveFileDialog and systemHooks.writeBlobToHandle. models/index.js: uses configuration above to initialize Sequelize, models/image.model.js for Sequelize model Image. Try scribbling with the Free-Form Select tool and then doing Image > Invert. When downloading a resource using HTTP, this is the Content-Length (the size of the body of the message), and doesn't include the headers and other overhead. Q: What to do if DALI doesnt cover my use case? The NVIDIA Data Loading Library (DALI) is a library for data loading and Referenced by pcl::visualization::PCLVisualizer::addCorrespondences(), pcl::visualization::PCLHistogramVisualizer::addFeatureHistogram(), pcl::visualization::PCLPlotter::addFeatureHistogram(), pcl::visualization::PCLVisualizer::addPointCloudIntensityGradients(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::PCLVisualizer::addPointCloudPrincipalCurvatures(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::visualization::ImageViewer::addRectangle(), pcl::LineRGBD< PointXYZT, PointRGBT >::addTemplate(), pcl::recognition::TrimmedICP< pcl::pcl::PointXYZ, float >::align(), pcl::Registration< PointSource, PointTarget, Scalar >::align(), pcl::BilateralFilter< PointT >::applyFilter(), pcl::LocalMaximum< PointT >::applyFilter(), pcl::GridMinimum< PointT >::applyFilter(), pcl::ShadowPoints< PointT, NormalT >::applyFilter(), pcl::ExtractIndices< PointT >::applyFilter(), pcl::UniformSampling< PointT >::applyFilter(), pcl::SamplingSurfaceNormal< PointT >::applyFilter(), pcl::ProjectInliers< PointT >::applyFilter(), pcl::RadiusOutlierRemoval< PointT >::applyFilter(), pcl::StatisticalOutlierRemoval< PointT >::applyFilter(), pcl::NormalSpaceSampling< PointT, NormalT >::applyFilter(), pcl::CropBox< PointT >::applyFilter(), pcl::PassThrough< PointT >::applyFilter(), pcl::ModelOutlierRemoval< PointT >::applyFilter(), pcl::ApproximateVoxelGrid< PointT >::applyFilter(), pcl::VoxelGrid< PointT >::applyFilter(), pcl::VoxelGridCovariance< PointT >::applyFilter(), pcl::ConditionalRemoval< PointT >::applyFilter(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::approxNearestSearch(), pcl::UnaryClassifier< PointT >::assignLabels(), pcl::RangeImageBorderExtractor::calculateBorderDirection(), pcl::RangeImageBorderExtractor::calculateMainPrincipalCurvature(), pcl::ESFEstimation< PointInT, PointOutT >::cleanup9(), pcl::OrganizedEdgeBase< PointT, PointLT >::compute(), pcl::ESFEstimation< PointInT, PointOutT >::compute(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::VFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::Feature< PointInT, PointOutT >::compute(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::compute(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::OrganizedEdgeFromRGBNormals< PointT, PointNT, PointLT >::compute(), pcl::features::computeApproximateCovariances(), pcl::features::computeApproximateNormals(), pcl::occlusion_reasoning::ZBuffering< ModelT, SceneT >::computeDepthMap(), pcl::ESFEstimation< PointInT, PointOutT >::computeESF(), pcl::PFHRGBEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::IntensityGradientEstimation< PointInT, PointNT, PointOutT, IntensitySelectorT >::computeFeature(), pcl::ESFEstimation< PointInT, PointOutT >::computeFeature(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computeFeature(), pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::DifferenceOfNormalsEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::computeFeature(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::IntensitySpinEstimation< PointInT, PointOutT >::computeFeature(), pcl::RIFTEstimation< PointInT, GradientT, PointOutT >::computeFeature(), pcl::NormalBasedSignatureEstimation< PointT, PointNT, PointFeature >::computeFeature(), pcl::UniqueShapeContext< PointInT, PointOutT, PointRFT >::computeFeature(), pcl::BoundaryEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTColorEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::RSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SpinImageEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::NormalEstimation< PointInT, PointOutT >::computeFeature(), pcl::SHOTColorEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::IntegralImageNormalEstimation< PointInT, PointOutT >::computeFeaturePart(), pcl::IntensitySpinEstimation< PointInT, PointOutT >::computeIntensitySpinImage(), pcl::ColorGradientModality< PointInT >::computeMaxColorGradients(), pcl::ColorGradientModality< PointInT >::computeMaxColorGradientsSobel(), pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computePairFeatures(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePairFeatures(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computePointMomentInvariants(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePointPFHSignature(), pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::computePointPrincipalCurvatures(), pcl::VFHEstimation< PointInT, PointNT, PointOutT >::computePointSPFHSignature(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::computeRFAndShapeDistribution(), pcl::PFHRGBEstimation< PointInT, PointNT, PointOutT >::computeRGBPairFeatures(), pcl::RIFTEstimation< PointInT, GradientT, PointOutT >::computeRIFT(), pcl::CRHAlignment< PointT, nbins_ >::computeRollAngle(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::concatenateFields(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::visualization::ImageViewer::convertRGBCloudToUChar(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTrianglesToMesh(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTsdfVectors(), pcl::GaussianKernel::convolveCols(), pcl::GaussianKernel::convolveRows(), pcl::copyPointCloud(), pcl::LineRGBD< PointXYZT, PointRGBT >::createAndAddTemplate(), pcl::visualization::createPolygon(), pcl::demeanPointCloud(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::derivatives(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::registration::TransformationEstimationDQ< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationDualQuaternion< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimation2D< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationPointToPlaneLLS< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationPointToPlaneLLSWeighted< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationSVD< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimation3Point< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationLM< PointSource, PointTarget, MatScalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::estimateRigidTransformation(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::ApproximateProgressiveMorphologicalFilter< PointT >::extract(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges(), pcl::extractEuclideanClusters(), pcl::io::PointCloudImageExtractorWithScaling< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromNormalField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromRGBField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromLabelField< PointT >::extractImpl(), pcl::extractLabeledEuclideanClusters(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::extractRGBFromPointCloud(), pcl::occlusion_reasoning::ZBuffering< ModelT, SceneT >::filter(), pcl::occlusion_reasoning::filter(), pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature(), pcl::UnaryClassifier< PointT >::findClusters(), pcl::gpu::DataSource::findKNNeghbors(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::findObjects(), pcl::gpu::DataSource::findRadiusNeghbors(), pcl::ApproximateVoxelGrid< PointT >::flush(), pcl::fromPCLPointCloud2(), pcl::gpu::DataSource::generateColor(), pcl::PCDWriter::generateHeader(), pcl::gpu::DataSource::generateIndices(), pcl::gpu::DataSource::generateSurface(), pcl::getApproximateIndices(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::getBoundaryPoints(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::features::ISMVoteList< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloudRGBA(), pcl::kinfuLS::WorldModel< PointT >::getExistingData(), pcl::getFeaturePointCloud(), pcl::Registration< PointSource, PointTarget, Scalar >::getFitnessScore(), pcl::getMaxDistance(), pcl::getMaxSegment(), pcl::getMeanPointDensity(), pcl::getMinMax3D(), pcl::occlusion_reasoning::getOccludedCloud(), pcl::getPointCloudDifference(), pcl::getPointsInBox(), pcl::RFFaceDetectorTrainer::getVotes(), pcl::RFFaceDetectorTrainer::getVotes2(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::BoundaryEstimation< PointInT, PointNT, PointOutT >::isBoundaryPoint(), pcl::isPointIn2DPolygon(), pcl::isXYPointIn2DXYPolygon(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::LineRGBD< PointXYZT, PointRGBT >::loadTemplates(), pcl::TextureMapping< PointInT >::mapMultipleTexturesToMeshUV(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::mismatchVector(), pcl::KdTree< FeatureT >::nearestKSearch(), pcl::search::Search< PointT >::nearestKSearch(), pcl::VoxelGridCovariance< PointTarget >::nearestKSearch(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::OptimizationFunctor::operator()(), pcl::registration::TransformationEstimationLM< PointSource, PointTarget, MatScalar >::OptimizationFunctor::operator()(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::OptimizationFunctorWithIndices::operator()(), pcl::registration::TransformationEstimationLM< PointSource, PointTarget, MatScalar >::OptimizationFunctorWithIndices::operator()(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()(), pcl::PointCloud< ModelT >::operator+=(), pcl::operator<<(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::Poisson< PointNT >::performReconstruction(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::PointCloud< ModelT >::PointCloud(), pcl::PointCloudDepthAndRGBtoXYZRGBA(), pcl::PointCloudRGBtoI(), pcl::io::pointCloudTovtkPolyData(), pcl::PointCloudXYZRGBAtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZI(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::SampleConsensusModelLine< PointT >::projectPoints(), pcl::SampleConsensusModelStick< PointT >::projectPoints(), pcl::SampleConsensusModelCircle2D< PointT >::projectPoints(), pcl::SampleConsensusModelCircle3D< PointT >::projectPoints(), pcl::SampleConsensusModelSphere< PointT >::projectPoints(), pcl::SampleConsensusModelCylinder< PointT, PointNT >::projectPoints(), pcl::SampleConsensusModelPlane< PointT >::projectPoints(), pcl::SampleConsensusModelCone< PointT, PointNT >::projectPoints(), pcl::PCDGrabber< PointT >::publish(), pcl::UnaryClassifier< PointT >::queryFeatureDistances(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::radiusSearch(), pcl::KdTree< FeatureT >::radiusSearch(), pcl::search::Search< PointT >::radiusSearch(), pcl::VoxelGridCovariance< PointTarget >::radiusSearch(), pcl::io::LZFDepth16ImageReader::read(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFYUV422ImageReader::read(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFYUV422ImageReader::readOMP(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::readRange(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::refineCorners(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseCurvature(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseHarris(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseLowe(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseNoble(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseTomasi(), pcl::seededHueSegmentation(), pcl::OrganizedConnectedComponentSegmentation< PointT, PointLT >::segment(), pcl::SegmentDifferences< PointT >::segment(), pcl::ExtractPolygonalPrismData< PointT >::segment(), pcl::OrganizedMultiPlaneSegmentation< PointT, PointNT, PointLT >::segment(), pcl::OrganizedMultiPlaneSegmentation< PointT, PointNT, PointLT >::segmentAndRefine(), pcl::CrfSegmentation< PointT >::segmentPoints(), pcl::PlanarPolygon< PointT >::setContour(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::shiftCloud(), pcl::TextureMapping< PointInT >::showOcclusions(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::simplifyCloud(), pcl::TextureMapping< PointInT >::sortFacesByCamera(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::spatialGradient(), pcl::PointCloud< ModelT >::swap(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::swapDimensions(), pcl::toPCLPointCloud2(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::visualization::PCLHistogramVisualizer::updateFeatureHistogram(), pcl::visualization::PCLVisualizer::updatePointCloud(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateMatch(), pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::validateTransformation(), pcl::ESFEstimation< PointInT, PointOutT >::voxelize9(), pcl::io::vtkPolyDataToPointCloud(), pcl::io::vtkStructuredGridToPointCloud(), pcl::PCDWriter::writeASCII(), pcl::PCDWriter::writeBinary(), and pcl::PCDWriter::writeBinaryCompressed().

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