resmush

resmush is a R package that allow users to optimize and compress images using reSmush.it. reSmush.it is a free API that provides image optimization, and it has been implemented on WordPress, Drupal and many more.

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.
• 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.

Installation

Install resmush from CRAN with:

install.packages("resmush")

You can install the development version of resmush from GitHub with:

remotes::install_github("dieghernan/resmush")

Alternatively, you can install resmush using the r-universe:

# Install resmush in R:
install.packages("resmush", repos = c(
  "https://dieghernan.r-universe.dev",
  "https://cloud.r-project.org"
))

Example

Compressing an online jpg image:

library(resmush)

url <- paste0(
  "https://raw.githubusercontent.com/dieghernan/",
  "resmush/main/img/jpg_example_original.jpg"
)

resmush_url(url, outfile = "man/figures/jpg_example_compress.jpg", overwrite = TRUE)
#> ══ resmush summary ═════════════════════════════════════════════════════════════
#> ℹ Input: 1 url with size 178.7 Kb
#> ✔ Success for 1 url: Size now is 45 Kb (was 178.7 Kb). Saved 133.7 Kb (74.82%).
#> See result in directory 'man/figures'.

Original picture (top) 178.7 Kb and optimized picture (bottom) 45 Kb (Compression 74.8%). Click to enlarge.

The quality of the compression can be adjusted in the case of jpg files using the parameter qlty. However, it is recommended to keep this value above 90 to get a good image quality.

# Extreme case
resmush_url(url,
  outfile = "man/figures/jpg_example_compress_low.jpg", overwrite = TRUE,
  qlty = 3
)
#> ══ resmush summary ═════════════════════════════════════════════════════════════
#> ℹ Input: 1 url with size 178.7 Kb
#> ✔ Success for 1 url: Size now is 2.2 Kb (was 178.7 Kb). Saved 176.4 Kb (98.74%).
#> See result in directory 'man/figures'.

Low quality image due to a high compression rate.

All the functions return invisibly a data set with a summary of the process. The next example shows how when compressing a local file.

png_file <- system.file("extimg/example.png", package = "resmush")

# For the example, copy to a temporary file
tmp_png <- tempfile(fileext = ".png")
file.copy(png_file, tmp_png, overwrite = TRUE)
#> [1] TRUE


summary <- resmush_file(tmp_png, overwrite = TRUE)

tibble::as_tibble(summary[, -c(1, 2)])
#> # A tibble: 1 × 6
#>   src_size dest_size compress_ratio notes src_bytes dest_bytes
#>   <chr>    <chr>     <chr>          <chr>     <dbl>      <dbl>
#> 1 239.9 Kb 70.7 Kb   70.54%         OK       245618      72356

Other alternatives

There are other alternatives for optimizing images with R:

• xfun (Xie 2024), which includes the following functions for optimizing image files:
  • xfun::tinify() is similar to resmush_file() but uses TinyPNG. An API key is required.
  • xfun::optipng() compresses local files with OptiPNG (which needs to be installed locally).
• tinieR package by jmablog. An R package that provides a full interface with TinyPNG.
• optout package by @coolbutuseless. Similar to xfun::optipng() with more options. Requires additional software to be installed locally.

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

Table 2: R packages: Formats admitted.

Citation

A BibTeX entry for LaTeX users is

@Manual{R-resmush,
  title = {{resmush}: Optimize and Compress Image Files with {reSmush.it}},
  doi = {10.32614/CRAN.package.resmush},
  author = {Diego Hernangómez},
  year = {2024},
  version = {0.2.1},
  url = {https://dieghernan.github.io/resmush/},
  abstract = {Compress local and online images using the reSmush.it API service <https://resmush.it/>.},
}

References

Xie, Yihui. 2024. xfun: Supporting Functions for Packages Maintained by Yihui Xie. https://github.com/yihui/xfun.