m.neural_network.preparedata_part1

NAME

m.neural_network.preparedata_part1 - Prepare training data for creating a neuronal network

KEYWORDS

raster, vector, export, neural network, preparation

SYNOPSIS

m.neural_network.preparedata_part1

m.neural_network.preparedata_part1 --help

m.neural_network.preparedata_part1 [-tl] tindex=name image_bands=name[,name,...] [ndsm=name] [dsm=name] [dtm=name] [ndsm_out=name] [reference=name] [segmentation_minsize=integer] [segmentation_threshold=float] [imagery_scale_min=integer] [imagery_scale_max=integer] output_dir=name [nprocs=integer] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-t: Only training and testing tiles; Option for only exporting training and testing tiles
-l: Prepare labels for training and testing data; Option for preparing labels for training and testing data. If not set, only the tiles for the image bands and nDSM are exported, but no segmentation and labeling is performed.
--overwrite: Allow output files to overwrite existing files
--help: Print usage summary
--verbose: Verbose module output
--quiet: Quiet module output
--ui: Force launching GUI dialog

Parameters:

tindex=name [required]: tindex file for tiling.; must be created with m.neural_network.tindex
image_bands=name[,name,...] [required]: The names of imagery raster bands, e.g. for DOPs RGBI raster bands; The first raster defines the output resolution
ndsm=name: Name of the nDSM raster; Name of input raster map
dsm=name: Name of the DSM raster; Name of input raster map
dtm=name: Name of the DTM raster; Name of input raster map
ndsm_out=name: Name for the computed nDSM raster; Name for output raster map
reference=name: Name of the reference vector map; Or data source for direct OGR access
segmentation_minsize=integer: Minimum number of cells in a segment; Default: 80
segmentation_threshold=float: Difference threshold between 0 and 1 for the segments; Threshold = 0 merges only identical segments; threshold = 1 merges all; Default: 0.3
imagery_scale_min=integer: minimum scaling value for imagery; Default: 1
imagery_scale_max=integer: maximum scaling value for imagery; Default: 255
output_dir=name [required]: Directory where the prepared data should be stored; The directory will be split into train and apply
nprocs=integer: Number of threads for parallel computing; 0: use OpenMP default; >0: use nprocs; <0: use MAX-nprocs; Default: 0

DESCRIPTION
EXAMPLES
- Prepare the labeling of training data for a neural network with a tile_size of 512
- Prepare training data and computing ndsm on the fly (Note: will be kept within mapset, where Addon is executed)
SEE ALSO
AUTHORS

DESCRIPTION

m.neural_network.preparedata_part1 prepares tiles for the labeling process as part of the training data preparation of a neural network using DOPs and nDSM as input data. Additionally, a tile index containing information about the labeled status is created.

The suffix option may be used to add a suffix to each output tile/file in order to create unique tile IDs that can later be combined with results from other runs.

EXAMPLES

Prepare the labeling of training data for a neural network with a tile_size of 512

m.neural_network.preparedata_part1 image_bands=top_red_02,top_green_02,top_blue_02,top_nir_02 ndsm=ndsm tile_size=512 output_dir=/mnt/data/ nprocs=7

Prepare training data and computing ndsm on the fly (Note: will be kept within mapset, where Addon is executed)

m.neural_network.preparedata_part1 image_bands=top_red_02,top_green_02,top_blue_02,top_nir_02 dsm=dsm dtm=dtm ndsm_out=ndsm tile_size=512 output_dir=/mnt/data/ nprocs=7