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Optimize your images with R and reSmush.it
Introducing the resmush package
r_bloggers
r_package
resmush
md_document html_document
variant preserve_yaml
gfm
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resmush package has recently hit CRAN! This is one tiny utility package that allows to optimize (i.e. compress the size) of local and online images using reSmush.it.

What is reSmush.it?

reSmush.it is a free online API that provides image optimization, and it has been implemented on Wordpress, Drupal or Magento. Some of the features of reSmush.it are:

  • Free optimization services, no API key required.
  • Optimize local and online images.
  • Image files supported: png, jpg/jpeg, gif, bmp, tiff, webp.
  • Max image size: 5 Mb.
  • Compression via several algorithms:
    • PNGQuant: Strip unneeded chunks from pngs, preserving a full alpha transparency.
    • JPEGOptim: Lossless optimization based on optimizing the Huffman tables.
    • OptiPNG: png reducer that is used by several online optimizers.

Why resmush package?

One of the main reasons I developed resmush is because I used to ship precomputed vignettes with my packages (see tidyterra as an example). I found that the plots created on CRAN with the standard configuration (i.e., not precomputed vignettes but built on CRAN itself) are not very satisfying, and in some of the packages I developed (especially those related to mapping), they don’t do justice to the actual results when a useR runs them.

This approach has the drawback that it produces images of higher quality at a expense of size. So, to avoid reaching CRAN’s 5Mb max size policy, I developed resmush, which enables me to reduce the size of the images without a significant loss in quality

Another use case for resmush is optimizing images in the context of web page development and SEO optimization. For example, I optimized all the images on this blog using resmush_dir(), which is a shorthand for optimizing all files in a specific folder.

There are other alternatives that I would discuss at the end of this post, but in one line, reSmush.it API performs fast with minimal configuration for a wide range of formats without an API key.

Using resmush package

With local files

Let’s present an example of how a local file can be optimized. First we create a large plot with ggplot2

library(tidyterra)
library(ggplot2)
library(terra)
library(maptiles)

cyl <- vect(system.file("extdata/cyl.gpkg", package = "tidyterra")) %>%
  project("EPSG:3857")
cyl_img <- get_tiles(cyl, "Esri.WorldImagery", zoom = 8, crop = TRUE)
cyl_gg <- autoplot(cyl_img, maxcell = Inf) +
  geom_spatvector(data = cyl, alpha = 0.3)

cyl_gg
Original file

Original file 

# And we save it for resmushing
ggsave("cyl.png", width = 5, height = 0.7 * 5)

Cool, but the file has a size of 1.7 Mb. So we can use resmush_file() to reduce it, see:

library(resmush)
resmush_file("cyl.png")
#> ══ resmush summary ═════════════════════════════════════════════════════════════
#> ℹ Input: 1 file with size 1.7 Mb
#> ✔ Success for 1 file: Size now is 762.2 Kb (was 1.7 Mb). Saved 948.9 Kb (55.46%).
#> See result in directory '.'.

png::readPNG("cyl_resmush.png") %>%
  grid::grid.raster()
Optimized file

Optimized file

By default resmush_file()/resmush_dir() do not overwrite the original file, altough this may be modified with the parameter overwrite = TRUE Now the resmushed file (“cyl_resmush.png”) has a size of 762.2 Kb.

Let’s compare them size-by-side:

Original online figure Optimized figure

Original picture (top) 1.7 Mb and optimized picture (bottom) 762.2 Kb (Compression 55.46%)

We can chech the reduction of size without reducing the dimensions of the image.

size_src <- file.size("cyl.png") %>%
  `class<-`("object_size") %>%
  format(units = "auto")
size_dest <- file.size("cyl_resmush.png") %>%
  `class<-`("object_size") %>%
  format(units = "auto")

dim_src <- dim(png::readPNG("cyl.png"))[1:2] %>% paste0(collapse = "x")
dim_dest <- dim(png::readPNG("cyl_resmush.png"))[1:2] %>% paste0(collapse = "x")

data.frame(
  source = c("original file", "compressed file"),
  size = c(size_src, size_dest),
  dimensions = c(dim_src, dim_dest)
) %>%
  knitr::kable()
source size dimensions
original file 1.7 Mb 1050x1500
compressed file 762.2 Kb 1050x1500

With online files

We can also optimize online files with resmush_url() and download them on disk. In this example I present a feature of all the functions of resmush, that is that they return an invisible data frame with a summary of the process.

url <- "https://dieghernan.github.io/assets/img/samples/sample_1.3mb.jpg"

# Invisible data frame
dm <- resmush_url(url, "sample_optimized.jpg", report = FALSE)
knitr::kable(dm)
src_img dest_img src_size dest_size compress_ratio notes src_bytes dest_bytes
https://dieghernan.github.io/assets/img/samples/sample_1.3mb.jpg sample_optimized_01.jpg 1.3 Mb 985 Kb 26.63% OK 1374693 1008593

Original online figure Optimized online figure

Original picture (top) 1.3 Mb and optimized picture (bottom) 985 Kb (Compression 26.63%)

Other alternatives

There are other alternatives for optimizing images for R, but first…

Yihui Xie, one of the most prominent figures in the R community, has recently been laid off from his position at Posit PBC (formerly RStudio) (more info).

Yihui is the developer of knitr, markdown, blogdown, and bookdown, among others, and he has been one of the key contributors (if not the most) to reproducible research space with R through his libraries.

If you have ever used and enjoyed his packages consider sponsor him. 

  <a class="btn btn-light border border-dark" role="button" aria-label="Sponsor @yihui" target="_top" href="https://github.com/sponsors/yihui?o=esb">
  <i class="fa-regular fa-heart fa-lg mr-2" aria-hidden="true" style="color: #bf3989;"></i><span class="font-weight-bold">Sponsor Yihui Xie</span>
  </a>

  • One of the many packages developed by Yihui Xie is xfun , that includes following functions that optimize image files:

    • xfun::tinify() is similar to resmush_file() but uses TinyPNG. API key required.
    • xfun::optipng() compress local files with OptiPNG (that needs to be installed locally).

  • tinieR package by jmablog. R package that provides a full interface with TinyPNG.

  • optout package by @coolbutuseless. Similar to xfun::optipng() with additional options. Needs additional software installed locally.

tool CRAN Additional software? Need online? API Key? Limits?
xfu n::tinify() Yes No Yes Yes 500 files/month (Free tier)
xfun ::optipng() Yes Yes No No No
tinieR No No Yes Yes 500 files/month (Free tier)
optout No Yes No No No
resmush Yes No Yes No Max size 5Mb

Table 1: R packages: Comparison of alternatives for optimizing images.

tool png jpg gif bmp tiff webp pdf
xfun::tinify() Yes Yes Yes
xfun::optipng() Yes
tinieR Yes Yes Yes
optout Yes Yes Yes
resmush Yes Yes Yes Yes Yes Yes

Table 2: R packages: Formats admitted.

Additionally, if you host your projects in GitHub, you can try Imgbot that is free for open-source projects. Imgbot provides automatic optimization for files in your repos and the optimized files would be included in specific PR before merging in your work.