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Using resmush

Source: vignettes/resmush.qmd

resmush is an R package for optimizing local image files, directories and online images with the reSmush.it API. The API is free for personal use and does not require an API key. reSmush.it is also available through WordPress and other tools.

The reSmush.it API provides:

  • Optimization without an API key.
  • Support for PNG, JPEG, GIF, BMP and TIFF files.
  • A file size limit of less than 5 MB.
  • Compression powered by several algorithms:
    • pngquant: Removes unnecessary data from PNG files while preserving full alpha transparency.
    • JPEGOptim: Lossless optimization based on Huffman table optimization.
    • OptiPNG: A PNG optimizer used by several online compression tools.

Examples

Optimize and download an online JPEG image with resmush_url():

library(resmush)

url <- "https://dieghernan.github.io/resmush/img/jpg_example_original.jpg"

resmush_url(url, outfile = "jpg_example_compress.jpg", overwrite = TRUE)

#> ══ resmush summary ══════════════════════════════════════════════════════════
#> ℹ Input: 1 URL, 178.7 Kb total.
#> ✔ Optimized 1 URL: size is now 45 Kb (was 178.7 Kb). Saved 133.7 Kb (74.82%).
#> Saved result in directory 'C:/user/john_doe/AppData/Local/Temp/'.
Original uncompressed JPEG image
(a)
Optimized JPEG image
(b)
Figure 1: Original image Figure 1 (a): 178.7 KB, optimized image Figure 1 (b): 45 KB (compression: 74.8%). Click to enlarge.

Use the qlty argument to adjust the optimization level for JPEG files. For best results, use values above 90.

# Use a low optimization level.
resmush_url(
  url,
  outfile = tempfile(fileext = ".jpg"),
  overwrite = TRUE,
  qlty = 3
)

#> ══ resmush summary ══════════════════════════════════════════════════════════
#> ℹ Input: 1 URL, 178.7 Kb total.
#> ✔ Optimized 1 URL: size is now 2.2 Kb (was 178.7 Kb). Saved 176.4 Kb (98.74%).
#> Saved result in directory 'C:/user/john_doe/AppData/Local/Temp/'.

JPEG image with visible compression artifacts

Figure 2: Image with visible compression artifacts caused by high compression (qlty = 3), compared with Figure 1 (b).

All optimization functions return, invisibly, a data frame summarizing the optimization. Successful API calls also write the optimized files to disk. The following example shows the returned data frame for a local image file:

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

# Copy to a temporary file for this example.
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

Alternatives

Several other R packages provide image optimization tools:

  • The xfun package (Xie 2024), which includes:
  • The tinieR package by jmablog: an R interface to TinyPNG.
  • The tinyimg package (Xie 2026): Optimizes local PNG and JPEG files using Rust libraries. It supports lossless PNG optimization via oxipng, optional lossy PNG palette reduction, and JPEG re-encoding via mozjpeg.
  • The optout package by @coolbutuseless: Similar to xfun::optipng() but with more options. Requires additional local software.
Tool CRAN Additional software Online images API key required Limits
xfun::tinify() Yes No Yes Yes 500 compressions/month (free tier)
xfun::optipng() Yes Yes No No No
tinieR No No Yes Yes 500 compressions/month (free tier)
tinyimg Yes Yes (Rust toolchain) No No No
optout No Yes No No No
resmush Yes No Yes No Personal use, files under 5 MB
Table 1: R packages: comparison of image optimization alternatives.
Tool PNG JPEG GIF BMP TIFF WebP PDF
xfun::tinify() ✅ ✅ ❌ ❌ ❌ ✅ ❌
xfun::optipng() ✅ ❌ ❌ ❌ ❌ ❌ ❌
tinieR ✅ ✅ ❌ ❌ ❌ ✅ ❌
tinyimg ✅ ✅ ❌ ❌ ❌ ❌ ❌
optout ✅ ✅ ❌ ❌ ❌ ❌ ✅
resmush ✅ ✅ ✅ ✅ ✅ ❌ ❌
Table 2: R packages: supported formats.

In practice, resmush is designed for quick image optimization with minimal setup, including support for online images and formats such as GIF, BMP and TIFF. Packages such as tinyimg may be a better fit for fully local workflows focused on PNG / JPEG optimization and fine-grained control over compression settings.

References

Xie, Yihui. 2024. xfun: Supporting Functions for Packages Maintained by Yihui Xie. https://github.com/yihui/xfun.
Xie, Yihui. 2026. tinyimg: Optimize and Compress Images. https://doi.org/10.32614/CRAN.package.tinyimg.