trans | R Documentation |
Transform a base image in shape, color, and/or texture by the differences between two images.
trans( trans_img = NULL, from_img = NULL, to_img = NULL, shape = 0, color = 0, texture = 0, outname = NULL, norm = c("none", "twopoint", "rigid"), normpoint = 0:1, sample_contours = TRUE, warp = c("multiscale", "linear", "multiscalerb") )
trans_img |
list of stimuli to transform |
from_img |
negative transform dimension endpoint (0% image) |
to_img |
positive transform dimension endpoint (100% image) |
shape, color, texture |
amount to change along the vector defined by from_img and to_img (can range from -3 to +3) |
outname |
name to save each image as |
norm |
how to normalise the images; see Details |
normpoint |
points for twopoint normalisation |
sample_contours |
whether to sample contours or just points |
warp |
warp type |
none: averages will have all coordinates as the mathematical average of the coordinates in the component templates
twopoint: all images are first aligned to the 2 alignment points designated in normpoint
. Their position is set to their position in the first image in stimuli
rigid: procrustes aligns all images to the position of the first image in stimuli
This interpolates more control points along the lines. This can improve the accuracy of averages and transforms. If you see a “feathery” appearance along lines that have many, close-together points, try turning this off.
multiscale: Implements multi-scale affine interpolation for image warping. This is the default, with a good balance between speed and accuracy
linear: Implements triangulated linear interpolation for image warping. Linear warping is least accurate, often resulting in image artifacts, but is very fast.
multiscalerb: Implements multi-scale rigid body interpolation for image warping. This decreases image artifacts in some circumstances, but is much slower.
list of stimuli with transformed images and templates
WebMorph.org functions
avg()
,
continuum()
,
loop()
,
symmetrize()
,
webmorph_up()
if (webmorph_up()) { stimuli <- demo_stim() sexdim <- trans(stimuli, stimuli$f_multi, stimuli$m_multi, shape = c(fem = -0.5, masc = 0.5)) sexdim |> draw_tem() |> label() }
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.