Drag and drop; 75. External images can be pasted in. You can even drag them out into little windows. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. collection of highly optimized building blocks for loading and processing We can pass a StandardCharsets.UTF_8 into the InputStreamReader constructor to read data from a UTF-8 file.. import java.nio.charset.StandardCharsets; // try (FileInputStream fis = new FileInputStream(file); InputStreamReader isr = new InputStreamReader(fis, Definition at line 188 of file point_cloud.h. And this is before the "submit" button on the form has been pressed so the image almost certainly resides Client side. Fix fieldset border in Firefox (but not supporting theme), Document individual system hooks and functions, Re-enable text selection in error details, Try to make Travis CI tests more reliable, Fully document set_theme and set_language, Update os-gui to 0.3.0, unifying windowing code, Check for and fix problems in news articles, async function systemHooks.showSaveFileDialog({ formats, defaultFileName, defaultPath, defaultFileFormatID, getBlob, savedCallbackUnreliable, dialogTitle }), async function systemHooks.showOpenFileDialog({ formats }), async function systemHooks.writeBlobToHandle(fileHandle, blob), async function systemHooks.readBlobFromHandle(fileHandle), function systemHooks.setWallpaperTiled(canvas), function systemHooks.setWallpaperCentered(canvas), function undoable({ name, icon }, actionFunction), function show_error_message(message, [error]), function open_from_file(blob, source_file_handle), https://jspaint.app/#load:https://i.imgur.com/zJMrWwb.png, Touch support: use two fingers to pan the view, and pinch to zoom, Click/tap the selected colors area to swap the foreground and background colors. You can also upload an image by clicking on the browse file button. legal basis for "discretionary spending" vs. "mandatory spending" in the USA, Position where neither player can force an *exact* outcome. How to use it: 1. Ap Image Zoom is a jQuery plugin which allows you to zoom in/out an image with mouse wheel or touch scroll. Include jQuery library together with jQuery ap image zoom plugin's JS and CSS files in the document. or the new skeuomorphic one with the interface that can take up nearly half the screen. Definition at line 434 of file point_cloud.h. When writing code for the Web, there are a large number of Web APIs available. Also inherits properties from its parent Event.. ProgressEvent.lengthComputable Read only . More bool is_dense True if no points are invalid (e.g., have NaN or Inf values). Ap Image Zoom is a jQuery plugin which allows you to zoom in/out an image with mouse wheel or touch scroll. Q: Where can I find more details on using the image decoder and doing image processing? OpenCSV Read and Parse CSV file. i put a couple log statements in the onload. they are fired multiple times, Going from engineer to entrepreneur takes more than just good code (Ep. Definition at line 444 of file point_cloud.h. 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. Dal click al MouseEvent: l'interazione con il mouse; 74. If "Write" is marked with , the format will appear in the file type dropdown but may not work when you try to save. I love to write on JavaScript, ECMAScript, React, Angular, Vue, Laravel. Form e dati della UI; 78. Hutoolhttps://github.com/looly/hutoolhttp://git.oschina.net/loolly/hutool In the Ribbon, select Data > Get and Transform Data > From Text/CSV.2. But actually it will show a prompt to the user to change the language, because the application needs to reload to apply the change. Now, import the ReactCrop module from the react-image-crop package also import the react crop CSS. To learn more, see our tips on writing great answers. Definition at line 468 of file point_cloud.h. go to, You can crop the image by making a selection while holding, Zoom to fit the canvas within the window with, Non-contiguous fill: Replace a color in the entire image by holding. 3 For Internet Explorer, one must use IE versions 10 and above. Whether it is maintaining the right balance between a product image's visual quality and its load time or delivering a pixel-perfect experience on all devices, ImageKit takes care of managing your product & marketing assets end-to-end. Not the answer you're looking for? Referenced by pcl::Registration< PointSource, PointTarget, Scalar >::align(), pcl::CovarianceSampling< PointT, PointNT >::applyFilter(), pcl::ConditionalRemoval< PointT >::applyFilter(), pcl::ESFEstimation< PointInT, PointOutT >::compute(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::VFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::Feature< PointInT, PointOutT >::compute(), pcl::features::computeApproximateNormals(), pcl::concatenateFields(), pcl::copyPointCloud(), pcl::demeanPointCloud(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::extractEuclideanClusters(), pcl::extractLabeledEuclideanClusters(), pcl::Filter< pcl::PointXYZRGBL >::filter(), pcl::fromPCLPointCloud2(), pcl::getPointCloudDifference(), pcl::PointCloud< ModelT >::operator+=(), pcl::operator<<(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::GridProjection< PointNT >::performReconstruction(), 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::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SurfaceReconstruction< PointInT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::SegmentDifferences< PointT >::segment(), pcl::toPCLPointCloud2(), pcl::transformPointCloud(), and pcl::transformPointCloudWithNormals(). Definition at line 415 of file point_cloud.h. Now, you require to install the React Image Crop package in react js application with the help of the given below command. can easily be retargeted to TensorFlow, PyTorch, MXNet and PaddlePaddle. PointCloud represents the base class in PCL for storing collections of 3D points. Whether it is maintaining the right balance between a product image's visual quality and its load time or delivering a pixel-perfect experience on all devices, ImageKit takes care of managing your product & marketing assets end-to-end. A boolean flag indicating if the total work to be done, and the amount of work already done, by the underlying process is calculable. 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. How e-commerce companies use ImageKit for faster, high-quality visual experiences. For Internet Explorer, one must use IE versions 10 and above. In addition, the deep learning frameworks have multiple data pre-processing implementations, This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. A boolean flag indicating if the total work to be done, and the amount of work already done, by the underlying process is calculable. FileInput supports configuration of the bootstrap library version so that you can use this either with any Bootstrap version 3.x and above. Capabilities marked with are currently left up to the browser to support or not. It is a powerful plugin and an image cropping tool for React that requires no dependencies, offers responsiveness, is touch-enabled, does fixed-aspect crops, supports min and max crop size. 3 Multiplayer support currently relies on Firebase, Also provides a simple image pan functionality which which allows to move an image via mouse drag or touch swipe. Referenced by pcl::visualization::ImageViewer::addMask(), pcl::visualization::ImageViewer::addPlanarPolygon(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::LineRGBD< PointXYZT, PointRGBT >::addTemplate(), pcl::recognition::TrimmedICP< pcl::pcl::PointXYZ, float >::align(), pcl::FastBilateralFilterOMP< PointT >::applyFilter(), pcl::CovarianceSampling< PointT, PointNT >::applyFilter(), pcl::approximatePolygon(), pcl::approximatePolygon2D(), pcl::calculatePolygonArea(), pcl::PlaneClipper3D< PointT >::clipPointCloud3D(), pcl::BoxClipper3D< PointT >::clipPointCloud3D(), pcl::compute3DCentroid(), pcl::computeCentroid(), pcl::computeCovarianceMatrix(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::computeMeanAndCovarianceMatrix(), pcl::computeNDCentroid(), pcl::computePointNormal(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::copyPointCloud(), pcl::LineRGBD< PointXYZT, PointRGBT >::createAndAddTemplate(), pcl::demeanPointCloud(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::derivatives(), pcl::Edge< PointInT, PointOutT >::detectEdgePrewitt(), pcl::Edge< PointInT, PointOutT >::detectEdgeRoberts(), pcl::Edge< PointInT, PointOutT >::detectEdgeSobel(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::estimateRigidTransformation(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::gpu::extractEuclideanClusters(), pcl::gpu::extractLabeledEuclideanClusters(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::findObjects(), pcl::kernel< PointT >::gaussianKernel(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::getBoundaryPoints(), pcl::getMeanPointDensity(), pcl::Morphology< PointT >::intersectionBinary(), pcl::LineRGBD< PointXYZT, PointRGBT >::loadTemplates(), pcl::kernel< PointT >::loGKernel(), pcl::search::Search< PointT >::nearestKSearch(), pcl::search::FlannSearch< PointT, FlannDistance >::nearestKSearch(), pcl::search::Search< PointXYZRGB >::nearestKSearchT(), pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::PointCloud< ModelT >::PointCloud(), pcl::io::pointCloudTovtkPolyData(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::PCA< PointT >::project(), pcl::search::FlannSearch< PointT, FlannDistance >::radiusSearch(), pcl::search::Search< PointT >::radiusSearch(), pcl::search::Search< PointXYZRGB >::radiusSearchT(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::PCA< PointT >::reconstruct(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::refineCorners(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseHarris(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseLowe(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseNoble(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseTomasi(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setEdgeDataCloud(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setFaceDataCloud(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setHalfEdgeDataCloud(), pcl::SupervoxelClustering< PointT >::setInputCloud(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setInputSource(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setVertexDataCloud(), pcl::Edge< PointInT, PointOutT >::sobelMagnitudeDirection(), pcl::Morphology< PointT >::structuringElementRectangle(), pcl::Morphology< PointT >::subtractionBinary(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track(), pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::transformCloud(), pcl::Morphology< PointT >::unionBinary(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation(). These data processing pipelines, which are currently executed on the CPU, have become a 2. Definition at line 390 of file point_cloud.h. of the input pipeline. So let's look at how to upload and retrieve images in ASP. How to Upload and Store Base64 Image in React Js with PHP. models/index.js: uses configuration above to initialize Sequelize, models/image.model.js for Sequelize model Image. 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. Enable JavaScript to view data. A 64-bit unsigned integer value indicating the amount of work already performed by the underlying process. "some-folder/some-image-15x11-pixels.png". It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. When writing code for the Web, there are a large number of Web APIs available. Step 4 : Create a folder named UploadedFiles or as you wish to save uploaded files. You can define two functions to set the wallpaper, which will be used by File > Set As Wallpaper (Tiled) and File > Set As Wallpaper (Centered). 503), Fighting to balance identity and anonymity on the web(3) (Ep. Definition at line 494 of file point_cloud.h. Ap Image Zoom is a jQuery plugin which allows you to zoom in/out an image with mouse wheel or touch scroll. How to Crop Image Size in React Js App. Eventi della tastiera; 76. 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: Connect and share knowledge within a single location that is structured and easy to search. On photoshop, browsers etc.. there are a few algorithms they use (e.g. How to Crop Image Size in React Js App. Maybe they've improved this?). How to use it: 1. Like by just using data URLs. Learn more about Collectives In this article, we learned how to downscale an image in JavaScript before uploading it to your server. When downloading a resource using HTTP, this only counts the body of the HTTP message, and doesn't include headers and other overhead. It can be any type, or maybe it needs to be a string, I forget. controllers: home.js returns views/index.html; upload.js handles upload, store, display and Also inherits properties from its parent Event.. ProgressEvent.lengthComputable Read only . Controlli e valori; 79. Note that this function is responsible for loading the contents of the file, not just picking a file. It provides a Definition at line 283 of file point_cloud.h. Collectives on Stack Overflow. 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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