Read data from a datastore
C — Output data
cell array of categorical matrices | M-by-2 cell array | table
Output data, returned as an M-by-2 cell array, cell array of categorical matrices, or a table.
N-by-3 cell matrix.
N must be less than or equal to
The first column can contain data, such as point cloud data for point cloud detectors, or images for object detectors.
The second column must be a cell vector that contains M-by-5 matrices of bounding boxes in the format[xcenter,ycenter,width,height,yaw].
The third column must be a cell vector that contains the label names corresponding to each bounding box. Label names are represented as an M-by-1 categorical vector.
You can use the
combine function to create a datastore to use for training.
imageDatastore— Create a datastore containing images.
PixelLabelDatastore— Create a datastore containing pixel data.
boxLabelDatastore— Create a datastore containing bounding boxes and labels.
blds) — Combine images, bounding boxes, and labels into one datastore.
blds) — Combine pixel data, bounding boxes, and labels into one datastore.
For more information, see Datastores for Deep Learning (Deep Learning Toolbox).
info — Information about read data
Information about read data, returned as a structure array. The structure array can contain the following fields.
|Fully resolved path containing the path string, name
of the file, and file extension. For
Total file size, in bytes. For MAT-files,
|Fully resolved path containing the path string, name of the image file, and file extension.|
|Fully resolved path containing the path string, name of the pixel label file, and file extension.|
|Starting position of each |
read(ds)returns an error if there is no more data in the input datastore,
read(ds)to avoid the error.
Introduced in R2017b