Blog Archives

Superpixels in imager

March 24, 2017
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Superpixels in imager

Superpixels are used in image segmentation as a pre-processing step. Instead of segmenting pixels directly, we first group similar pixels into “super-pixels”, which can then be processed further (and more cheaply). (image from Wikimedia) The current version of imager doesn’t implement them, but it turns out that SLIC superpixels are particularly easy to implement. SLIC […]

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New version of imager package for image processing

March 15, 2017
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New version of imager package for image processing

A new version of imager is now available on CRAN. This release brings a lot of new features, including a whole new set of functions dealing with pixel sets, better support for videos, new and faster reduction functions. The most significant change is the introduction of a “pixset” class, which deals with sets of pixels […]

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vecpack: an R package for packing stuff into vectors

September 18, 2016
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vecpack: an R package for packing stuff into vectors

Here’s a problem I’ve had again and again: let’s say you’ve defined a statistical model with several parameters. One of them is a scalar. Another is a matrix. The third one is a vector, and so on. When fitting the model the natural thing to do is to write a likelihood function that takes as […]

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New features in imager 0.30

September 13, 2016
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New features in imager 0.30

imager is an R package for image processing, based on CImg. This new release brings many new features, including: Support for automatic parallel processing using OpenMP. A new S3 class, imlist, which makes it easy to work with image lists New functions for interactively selecting image regions (grabRect,grabPoint,grabLine) Experimental support for CImg’s byte-compiled DSL via […]

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New features in imager 0.20

May 2, 2016
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New features in imager 0.20

imager, an R package for image processing, has been updated to v0.20 on CRAN. It’s a major upgrade with a lot of new features, better documentation and a more consistent API. imager now has 130 functions, and I myself keep forgetting all that’s in there. I’ve added a tutorial vignette that should help you get […]

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New R package for Eyelink eye-trackers

February 23, 2016
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New R package for Eyelink eye-trackers

Eyelink eye-trackers output an avalanche of disorganised crap. I’ve written an R package that will hopefully filter that crap for you. It’s called eyelinker and it’s on Github. It outputs a set of dataframes containing raw traces, saccades, fixations and blinks, meaning it’s easy to produce plots like this one: There’s a vignette explaining everything, […]

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imager now on CRAN, and a non-linear filtering example

September 17, 2015
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imager now on CRAN, and a non-linear filtering example

imager is an R package for image processing that’s fairly fast and now quite powerful (if I may say so myself). It wraps a neat C++ library called CImg, by David Tschumperlé (CNRS). It took quite a bit of work, but imager is now on CRAN, so that installing it is as easy as: Here’s […]

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New package for image processing in R

June 5, 2015
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New package for image processing in R

[update: imager is now on CRAN. install via install.packages(“imager”)] I’ve written a package for image processing in R, with the goal of providing a fast API in R that lets you do things in C++ if you need to. The package is called imager, and it’ on Github. The whole thing is based on CImg, […]

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Neurostats 2014 Highlights

September 10, 2014
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Neurostats 2014 Highlights

Last week the Neurostats 2014 workshop took place at the University of Warwick (co-organised by Adam Johansen, Nicolas Chopin, and myself). The goal was to put some neuroscientists and statisticians together to talk about neural data and what to do with it. General impressions: The type of Bayesian hierarchical modelling that Andrew Gelman has been […]

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Poisson transform – update

July 14, 2014
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Poisson transform – update

Michael Gutmann (University of Helsinki) recently wrote me with some comments on the Poisson transform paper (here). It turns out that the Poisson likelihood we define in the paper is a special case of more general frameworks he has worked on, the most recent being: M.U. Gutmann and J.Hirayama (2011). Bregman Divergence as General Framework […]

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