tl;dr

Now you can use a function to deep fry memes in R.

Extra crispy

You can make memes in R with packages like Guangchang Yu’s {meme}. You could even post them to Twitter with #RStatsMemes for @rstatsmemes to find.

However, it’s no longer enough to present memes as-is. They must be deep-fried to become modern and ironic. It will help people think that your meme is so edgy that it’s been re-saved thousands of times.

Get to temperature

You’ll need image-manipulation wizardry from the {magick} package, along with {extrafont} to let you use fonts from your system.

At time of writing there is an issue with importing fonts, which requires an earlier version of {Rttf2pt1} to be installed.

install.packages(c("magick", "extrafont", "remotes"))
remotes::install_version("Rttf2pt1", version = "1.3.8")

You can then import fonts from your system.

extrafont::font_import()

Now we can use important joke fonts—like Impact, Papyrus or Calibri—in our memes.

Small fry

I’ve cooked up a single, low-quality function, fry(), that:

1. Reads a meme template image (or any image) from a path
2. Adds top/bottom text in Impact font
3. Reads from a URL a specific (cursed) cry/laugh emoji that’s popular in deep-frying and places it in a random location (corners or left/right sides)
4. Adjusts the image contrast, saturation, etc,¹, tints it orange and bulges it from the centre
5. Writes the image to a temporary jpeg file—compressing it horribly—and then reads it back in
6. Outputs a magick-image object that you can save with magick::image_write() and send to all your friend (sic)

It does what I want it to do; adjust it as you please.

suppressPackageStartupMessages(library(magick))

fry <- function(
  img_path, emoji_path,
  text_top, text_bottom,
  depth = c("shallow", "deep")) {
  
  depth <- match.arg(depth)
  
  cat("Heating oil... ")
  
  emoji <- magick::image_read(emoji_path)
  
  emoji_where <-  sample(c(  
    paste0("north", c("east", "west")),
    paste0("south", c("east", "west")),
    "east", "west"  # e.g. 'east' is right
  ), 1)
  
  img <- image_read(img_path) |> 
    image_annotate(
      text_top, "north", size = 80, font = "Impact",
      color = "white", strokecolor = "black"
    ) |>
    image_annotate(
      text_bottom, "south", size = 80, font = "Impact",
      color = "white", strokecolor = "black"
    ) |>
    image_scale("1000") |> 
    image_composite(emoji, gravity = emoji_where) |> 
    image_colorize(30, "orange") |>  # tint
    image_modulate(brightness = 80, saturation = 120, hue = 90) |>
    image_contrast(sharpen = 100) |> 
    image_noise()
  
  cat("dunking meme... ")
  
  if (depth == "shallow") {
    img <- img %>% image_implode(-0.5)  # bulge
    compress <- 8
  } else if (depth == "deep") {
    img <- img %>% image_implode(-1)  # more bulge
    compress <- 1  # maximum compression
  } 
  
  path_out <- tempfile("meme", fileext = ".jpeg")
  image_write(img, path_out, "jpeg", compress)
  
  cat("crisp.")
  image_read(path_out)
  
}

Get cooking

What spicy meme shall I make? Well, the = versus <- assignment-operator flamewar has been cold for a few days, so time to heat it up again.² And why not incorporate the world’s most famous fry cook (in sarcastic form)?

sponge_path <- paste0(  # URL to meme image
  "https://raw.githubusercontent.com/matt-dray/rostrum-blog/",
  "master/static/post/2021-11-07-deepfry_files/spongebob.jpg"
)

emoji_path <- paste0(  # URL to cry/laugh emoji
  "https://raw.githubusercontent.com/matt-dray/rostrum-blog/",
  "master/static/post/2021-11-07-deepfry_files/deepfry-emoji.jpg"
)

bot_txt <- "= sAvEs KeYsTrOkEs Vs <-"  # sarcastic text
top_txt <- tolower(bot_txt)

First, a nice shallow fry.

fry(sponge_path, emoji_path, top_txt, bot_txt, "shallow")

## Heating oil... dunking meme... crisp.

And now we deep fry.

fry(sponge_path, emoji_path, top_txt, bot_txt, "deep")

## Heating oil... dunking meme... crisp.

*Fry-cook’s kiss*

## ─ Session info ───────────────────────────────────────────────────────────────
##  setting  value                       
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##  os       macOS Mojave 10.14.6        
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##  language (EN)                        
##  collate  en_GB.UTF-8                 
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##  date     2021-12-01                  
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## 
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## [2] /Library/Frameworks/R.framework/Versions/4.1/Resources/library