subset - Create subset of datastore or FileSet - MATLAB (original) (raw)

Create subset of datastore or FileSet

Syntax

Description

subds = subset([ds](#mw%5Fdb26d859-83b0-4d4b-a2ab-f663a43ec943),[indices](#mw%5Fc4088c28-75db-4a09-bee5-af9532d66ed0)) returns a subset containing reads corresponding to indices. The subsetsubds is of the same type as the input.

if the input ds is a datastore, then the outputoutds is a datastore of the same type.
if the input ds is a FileSet,DsFileSet, or BlockedFileSet object, then the output subds is also, respectively, a FileSet,DsFileSet, or BlockedFileSet object.

example

Examples

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Make an image datastore object and then create a subset of that image datastore.

Create an image datastore imds for all the image files in a sample folder. Then, display the Files property ofimds.

folders = fullfile(matlabroot,'toolbox','matlab',{'demos','imagesci'}); exts = {'.jpg','.png','.tif'}; imds = imageDatastore(folders,'LabelSource','foldernames','FileExtensions',exts); imds.Files

ans =

8×1 cell array

{'...\matlab\toolbox\matlab\demos\cloudCombined.jpg'}
{'...\matlab\toolbox\matlab\demos\example.tif'      }
{'...\matlab\toolbox\matlab\demos\landOcean.jpg'    }
{'...\matlab\toolbox\matlab\demos\ngc6543a.jpg'     }
{'...\matlab\toolbox\matlab\demos\street1.jpg'      }
{'...\matlab\toolbox\matlab\demos\street2.jpg'      }
{'...\matlab\toolbox\matlab\imagesci\corn.tif'      }
{'...\matlab\toolbox\matlab\imagesci\peppers.png'   }

Create a subset datastore subimds that contains the first four files of imds and examine the Files property ofsubimds.

indices = 1:4; subimds = subset(imds,indices); subimds.Files

ans =

4×1 cell array

{'...\matlab\toolbox\matlab\demos\cloudCombined.jpg'}
{'...\matlab\toolbox\matlab\demos\example.tif'      }
{'...\matlab\toolbox\matlab\demos\landOcean.jpg'    }
{'...\matlab\toolbox\matlab\demos\ngc6543a.jpg'     }

Make an image datastore, and then create subset datastore containing only a specified percentage of files, randomly selected from the original datastore.

Create imageDatastore for all the image files in a sample folder and display the Files property. This datastore contains 8 files.

folders = fullfile(matlabroot,'toolbox','matlab',{'demos','imagesci'}); exts = {'.jpg','.png','.tif'}; imds = imageDatastore(folders,'LabelSource','foldernames','FileExtensions',exts); imds.Files

ans =

8×1 cell array

{'...\matlab\toolbox\matlab\demos\cloudCombined.jpg'}
{'...\matlab\toolbox\matlab\demos\example.tif'      }
{'...\matlab\toolbox\matlab\demos\landOcean.jpg'    }
{'...\matlab\toolbox\matlab\demos\ngc6543a.jpg'     }
{'...\matlab\toolbox\matlab\demos\street1.jpg'      }
{'...\matlab\toolbox\matlab\demos\street2.jpg'      }
{'...\matlab\toolbox\matlab\imagesci\corn.tif'      }
{'...\matlab\toolbox\matlab\imagesci\peppers.png'   }

Create a set of indices that represents randomly selected subset containing60% of the files.

nFiles = length(imds.Files); RandIndices = randperm(nFiles); nSixtyPercent = round(0.6*nFiles); indices = RandIndices(1:nSixtyPercent)

Create a subset datastore submids usingindices and examine its Files property.

subimds = subset(imds,indices); subimds.Files

ans =

5×1 cell array

{'...\matlab\toolbox\matlab\imagesci\peppers.png'   }
{'...\matlab\toolbox\matlab\demos\street2.jpg'      }
{'...\matlab\toolbox\matlab\demos\ngc6543a.jpg'     }
{'...\matlab\toolbox\matlab\demos\street1.jpg'      }
{'...\matlab\toolbox\matlab\demos\cloudCombined.jpg'}

Compare a coarse-grained partition with a fine-grained subset.

Read all the frames in the video file xylophone.mp4 and construct an ArrayDatastore object to iterate over it. The resulting object has 141 frames.

v = VideoReader("xylophone.mp4"); allFrames = read(v); arrds = arrayDatastore(allFrames,IterationDimension=4,OutputType="cell",ReadSize=4);

To extract a specific set of adjacent frames, create four coarse-grained partitions of arrds. Extract the second partition, which has 35 frames.

partds = partition(arrds,4,2); imshow(imtile(partds.readall()))

Figure contains an axes object. The hidden axes object contains an object of type image.

Extract six nonadjacent frames from arrds at specified indices using a fine-grained subset.

subds = subset(arrds,[67 79 82 69 89 33]); imshow(imtile(subds.readall()))

Figure contains an axes object. The hidden axes object contains an object of type image.

Input Arguments

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Indices of files to include in subset, specified as a vector of indices or a logical vector.

The vector of indices must contain the indices of files to include in the subset subds.
The logical vector must be of the same length as the number of files in the input ds. The subset method creates a subsetsubds containing files corresponding to the elements in the logical vector that have a value of true.

Elements of indices must be unique.

Data Types: double | logical

Extended Capabilities

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Usage notes and limitations:

In a thread-based environment, you can use subset only with the following datastores:
- ImageDatastore objects
- CombinedDatastore, SequentialDatastore, orTransformedDatastore objects you create fromImageDatastore objects by usingcombine or transform
  You can use subset with other datastores if you have Parallel Computing Toolbox™. To do so, run the function using a process-backed parallel pool instead of using backgroundPool or ThreadPool (use eitherProcessPool or ClusterPool).

For more information, see Run MATLAB Functions in Thread-Based Environment.

Version History

Introduced in R2019a