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:

14 exports 9 stars 1.70 score 39 dependencies 1 mentions 15 scripts 1.1k downloads

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

TargetResultDate
Doc / VignettesOKSep 07 2024
R-4.5-win-x86_64NOTESep 07 2024
R-4.5-linux-x86_64NOTESep 07 2024
R-4.4-win-x86_64NOTESep 07 2024
R-4.4-mac-x86_64NOTESep 07 2024
R-4.4-mac-aarch64NOTESep 07 2024
R-4.3-win-x86_64NOTESep 07 2024
R-4.3-mac-x86_64NOTESep 07 2024
R-4.3-mac-aarch64NOTESep 07 2024

Exports:createBackgroundcreateImageSeqfindMaxCostfindPixelRangefindThresholdidentifyParticlesloadImagesmanuallySelectmergeTracksrunBatchsimulTrajecsubtractBackgroundtestNNtrackParticles

Dependencies:base64encbslibcachemclicommonmarkcrayonDerivdigestfastmapfontawesomefsgluehtmltoolshttpuvjquerylibjsonlitelaterlatticelifecyclemagrittrMASSmemoisemimeneuralnetpngpromisesR6rappdirsrasterRcppRcppArmadillorlangsassshinysourcetoolsspterrawithrxtable

Tutorial

Rendered fromtutorial.Rnwusingutils::Sweaveon Sep 07 2024.

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