Description Usage Arguments Value Author(s) Examples
Apply trained artificial neural network to particleStat object.
1 2 |
object |
Object of class 'nnTrackdemObject'. |
neuralnet |
Trained neural net obtained from |
pca |
Logical. By default |
colorimages |
An array with the original full color images, in order
to plot on the original images, obtained by |
sbg |
Images subtracted from background, as obtained by
|
... |
further arguments passed to or from other methods. |
Data frame class 'particles', containing updated particle statistics (excluding particles that have been filtered out by the neural net).
Marjolein Bruijning, Caspar A. Hallmann & Marco D. Visser
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ## Not run:
dir.create("images")
## Create image sequence
traj <- simulTrajec(path="images",
nframes=30,nIndividuals=20,domain='square',
h=0.01,rho=0.9,movingNoise=TRUE,
parsMoving = list(density=20, duration=10, size=1,
speed = 10, colRange = c(0,1)),
sizes=runif(20,0.004,0.006))
## Load images
dir <- "images"
allFullImages <- loadImages (dirPictures=dir,nImages=1:30)
stillBack <- createBackground(allFullImages,method="mean")
allImages <- subtractBackground(stillBack)
partIden <- identifyParticles(allImages,threshold=-0.1,
pixelRange=c(3,400))
nframes <- 3
frames <- order(tapply(partIden$patchID,partIden$frame,length),
decreasing=TRUE)[1:nframes]
mId <- manuallySelect(particles=partIden,frame=frames)
finalNN <- testNN(dat=mId,repetitions=10,maxH=4,prop=c(6,2,2))
partIdenNN <- update(particles=partIden,neuralnet=finalNN)
## End(Not run)
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