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Compare screenshots given threshold value

Source: R/compare-screenshot-threshold.R
compare_screenshot_threshold.Rd

chromote can sometimes produce screenshot images with non-deterministic (yet close) color values. This can happen in locations such as rounded corners of divs or textareas.

Usage

compare_screenshot_threshold(
  old,
  new,
  ...,
  threshold = getOption("shinytest2.compare_screenshot.threshold", NULL),
  kernel_size = getOption("shinytest2.compare_screenshot.kernel_size", 5),
  quiet = FALSE
)

screenshot_max_difference(
  old,
  new = missing_arg(),
  ...,
  kernel_size = getOption("shinytest2.compare_screenshot.kernel_size", 5)
)

Arguments

old

Current screenshot file path

new

New screenshot file path

...

Must be empty. Allows for parameter expansion.

threshold

The threshold for maximum allowed image difference (see below for details). The default is NULL or can be set globally via the shinytest2.compare_screenshot.threshold option.

If the value of threshold is NULL, compare_screenshot_threshold() will act like testthat::compare_file_binary. However, if threshold is a positive number, it will be compared against the largest convolution value found if the two images fail a testthat::compare_file_binary comparison. The max value that can be found is 4 * kernel_size ^ 2.

Threshold values values below 5 help deter false-positive screenshot comparisons (such as inconsistent rounded corners). Larger values in the 10s and 100s will help find real changes. However, not all values are one size fits all and you will need to play with a threshold that fits your needs.

To find the current difference between two images, use screenshot_max_difference().

kernel_size

The kernel_size represents the height and width of the convolution kernel applied to the matrix of pixel differences. This integer-like value should be relatively small, such as 5. The default value can be set via the shinytest2.compare_screenshot.kernel_size option.

quiet

If FALSE and the value is larger than threshold, then a message is printed to the console. This is helpful when getting a failing image and being informed about how different the new image is from the old image.

Details

These differences make comparing screenshots impractical using traditional expectation methods as false-positives are produced often over time. To mitigate this, we can use a fuzzy matching algorithm that can tolerate small regional differences throughout the image. If the local changes found are larger than the threshold, then the images are determined to be different. Both the screenshot difference threshold and the size of the kernel (kernel_size) can be set to tune the false positive rate.

Functions

  • compare_screenshot_threshold(): Compares two images and allows for a threshold difference of so many units in each RGBA color channel.

    It is suggested to use this method with AppDriver$expect_screenshot(threshold=, kernel_size=) to make expectations on screenshots given particular threshold and kernel_size values.

  • screenshot_max_difference(): Finds the difference between two screenshots.

    This value can be used in compare_screenshot_threshold(threshold=). It is recommended that the value used for compare_screenshot_threshold(threshold=) is larger than the immediate max difference found. This allows for random fluctuations when rounding sub pixels.

    If new is missing, it will use the file value of old (FILE.png) and default to FILE.new.png

Algorithm for the difference between two screenshots

  1. First the two images are compared using testthat::compare_file_binary(). If the files are identical, return TRUE that the screenshot images are the same.

  2. If threshold is NULL, return FALSE as the convolution will not occur.

  3. Prepare the screenshot difference matrix by reading the RGBA channels of each image and find their respective absolute differences

  4. Sum the screenshot difference matrix channels at each pixel location

  5. Perform a convolution using a small square kernel matrix that is kernel_size big and filled with 1s.

  6. Find the largest value in the resulting convolution matrix.

  7. If this max convolution value is larger than threshold, return FALSE, images are different.

  8. Otherwise, return TRUE, images are the same.

Examples

img_folder <- system.file("example/imgs/", package = "shinytest2")
slider_old <- fs::path(img_folder, "slider-old.png")
slider_new <- fs::path(img_folder, "slider-new.png")

# Can you see the differences between these two images?
showimage::show_image(slider_old)

showimage::show_image(slider_new)


# You might have caught the difference between the two images!
slider_diff <- fs::path(img_folder, "slider-diff.png")
showimage::show_image(slider_diff)


# Let's find the difference between the two images
screenshot_max_difference(slider_old, slider_new)
#> [1] 28.11765
# ~ 28

# Using different threshold values...
compare_screenshot_threshold(slider_old, slider_new, threshold = NULL)
#> [1] FALSE
#> FALSE # Images are not identical
compare_screenshot_threshold(slider_old, slider_new, threshold = 25)
#> ! Maximum screenshot convolution value `28.1176470588235` > `25` (threshold).
#> • `old`:/home/runner/work/_temp/Library/shinytest2/example/imgs/slider-old.png
#> • `new`:/home/runner/work/_temp/Library/shinytest2/example/imgs/slider-new.png
#> ℹ (To remove this message, increase `threshold`, or set `quiet = TRUE`)
#> [1] FALSE
#> FALSE # Images are more different than 25 units
compare_screenshot_threshold(slider_old, slider_new, threshold = 30)
#> [1] TRUE
#> TRUE # Images are not as different as 30 units

#########################

# Now let's look at two fairly similar images
bookmark_old <- fs::path(img_folder, "bookmark-old.png")
bookmark_new <- fs::path(img_folder, "bookmark-new.png")

# Can you see the difference between these two images?
# (Hint: Focused corners)
showimage::show_image(bookmark_old)

showimage::show_image(bookmark_new)


# Can you find the red pixels showing the differences?
# Hint: Look in the corners of the focused text
bookmark_diff <- fs::path(img_folder, "bookmark-diff.png")
showimage::show_image(bookmark_diff)


# Let's find the difference between the two images
screenshot_max_difference(bookmark_old, bookmark_new)
#> [1] 0.2705882
# ~ 0.25

# Using different threshold values...
compare_screenshot_threshold(bookmark_old, bookmark_new, threshold = NULL)
#> [1] FALSE
#> FALSE # Images are not identical
compare_screenshot_threshold(bookmark_old, bookmark_new, threshold = 5)
#> [1] TRUE
#> TRUE # Images are not as different than 5 units