Package: trackdem 0.6

Marjolein Bruijning

trackdem: Particle Tracking and Demography

Obtain population density and body size structure, using video material or image sequences as input. Functions assist in the creation of image sequences from videos, background detection and subtraction, particle identification and tracking. An artificial neural network can be trained for noise filtering. The goal is to supply accurate estimates of population size, structure and/or individual behavior, for use in evolutionary and ecological studies.

Authors:Marjolein Bruijning, Marco D. Visser, Caspar A. Hallmann, Eelke Jongejans

trackdem_0.6.tar.gz
trackdem_0.6.zip(r-4.5)trackdem_0.6.zip(r-4.4)trackdem_0.6.zip(r-4.3)
trackdem_0.6.tgz(r-4.4-x86_64)trackdem_0.6.tgz(r-4.4-arm64)trackdem_0.6.tgz(r-4.3-x86_64)trackdem_0.6.tgz(r-4.3-arm64)
trackdem_0.6.tar.gz(r-4.5-noble)trackdem_0.6.tar.gz(r-4.4-noble)
trackdem_0.6.tgz(r-4.4-emscripten)trackdem_0.6.tgz(r-4.3-emscripten)
trackdem.pdf |trackdem.html
trackdem/json (API)

# Install 'trackdem' in R:
install.packages('trackdem', repos = c('https://marjoleinbruijning.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/marjoleinbruijning/trackdem/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

4.83 score 9 stars 15 scripts 607 downloads 1 mentions 14 exports 39 dependencies

Last updated 3 years agofrom:c74c15724a. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-win-x86_64NOTENov 06 2024
R-4.5-linux-x86_64NOTENov 06 2024
R-4.4-win-x86_64NOTENov 06 2024
R-4.4-mac-x86_64NOTENov 06 2024
R-4.4-mac-aarch64NOTENov 06 2024
R-4.3-win-x86_64NOTENov 06 2024
R-4.3-mac-x86_64NOTENov 06 2024
R-4.3-mac-aarch64NOTENov 06 2024

Exports:createBackgroundcreateImageSeqfindMaxCostfindPixelRangefindThresholdidentifyParticlesloadImagesmanuallySelectmergeTracksrunBatchsimulTrajecsubtractBackgroundtestNNtrackParticles

Dependencies:base64encbslibcachemclicommonmarkcrayonDerivdigestfastmapfontawesomefsgluehtmltoolshttpuvjquerylibjsonlitelaterlatticelifecyclemagrittrMASSmemoisemimeneuralnetpngpromisesR6rappdirsrasterRcppRcppArmadillorlangsassshinysourcetoolsspterrawithrxtable

Tutorial

Rendered fromtutorial.Rnwusingutils::Sweaveon Nov 06 2024.

Last update: 2021-09-24
Started: 2018-01-09