Package: deforestable 3.1.1
deforestable: Classify RGB Images into Forest or Non-Forest
Implements two out-of box classifiers presented in <doi:10.48550/arXiv.2112.01063> for distinguishing forest and non-forest terrain images. Under these algorithms, there are frequentist approaches: one parametric, using stable distributions, and another one- non-parametric, using the squared Mahalanobis distance. The package also contains functions for data handling and building of new classifiers as well as some test data set.
Authors:
deforestable_3.1.1.tar.gz
deforestable_3.1.1.tar.gz(r-4.5-noble)deforestable_3.1.1.tar.gz(r-4.4-noble)
deforestable_3.1.1.tgz(r-4.4-emscripten)deforestable_3.1.1.tgz(r-4.3-emscripten)
deforestable.pdf |deforestable.html✨
deforestable/json (API)
# Install 'deforestable' in R: |
install.packages('deforestable', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:a17cede3ac. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 15 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 15 2024 |
Exports:classifycreateDataPartitioncreateFoldsKoutparamsread_dataread_data_matrixread_data_rastertrain
Dependencies:briocallrclicrayondescdiffobjdigestevaluatefBasicsfsgluegssjpegjsonlitelatticelifecyclemagrittrMASSMatrixnumDerivpkgbuildpkgloadplyrpraiseprocessxpsR6rbibutilsRcppRcppArmadilloRdpackrlangrprojrootspatialstabledistStableEstimterratestthattimeDatetimeSerieswaldowithrxtable
Readme and manuals
Help Manual
Help page | Topics |
---|---|
S3 class ForestTrain | Class_ForestTrain |
Classify parts of images as forest / non-forest | classify classify.ForestTrainNonParam classify.ForestTrainParam |
Data Partitioning | createDataPartition createFolds |
Koutrouvelis parameter estimation of image data | Koutparams |
Import a jpeg image | read_data read_data_matrix read_data_raster |
Train models for forest detection | train |