Package: deforestable 3.1.2
Dmitry Otryakhin
deforestable: Classify RGB Images into Forest or Non-Forest
Implements two out-of box classifiers presented in <doi:10.1002/env.2848> 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_3.1.2.tar.gz
deforestable_3.1.2.tar.gz(r-4.7-arm64)deforestable_3.1.2.tar.gz(r-4.7-x86_64)deforestable_3.1.2.tar.gz(r-4.6-arm64)deforestable_3.1.2.tar.gz(r-4.6-x86_64)
deforestable_3.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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 from:e92d8f9dc1. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 298 | ||
| linux-devel-x86_64 | OK | 229 | ||
| source / vignettes | OK | 254 | ||
| linux-release-arm64 | OK | 294 | ||
| linux-release-x86_64 | OK | 231 | ||
| wasm-release | OK | 143 |
Exports:classifycreateDataPartitioncreateFoldsKoutparamsread_dataread_data_matrixread_data_rastertrain
Dependencies:fBasicsgssjpegMASSnumDerivplyrrbibutilsRcppRcppArmadilloRdpackspatialstabledistStableEstimterratimeDatetimeSeries
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 |
