This page describes all basic operations on videos and images.

3.1 - Object properties

Video Stream Image VideoWriter
Testing for isVideo(x) isStream(x) isImage(x) isVideoWriter(x)
Dimensions dim(x) dim(x) dim(x) -
Number of rows nrow(x) nrow(x) nrow(x) -
Number of columns ncol(x) ncol(x) ncol(x) -
Number of channels - - nchan(x) -
Number of frames nframes(x) - - -
Framerate fps(x) - - -
Codec codec(x) - - -
Bit depth - - bitdepth(x) -
Color space - - colorspace(x) -

3.2 - Displaying images

There are two methods for displaying images. The first method offers full compatibility with base R plotting methods, which allows for drawing non-destructively over an image using graphics::lines(), garaphics::points(), etc. This method is however is however rather slow and therefore not suitable for applications requiring quick refresh rates between successive images (e.g. when playing a video).

The second method uses OpenCV’s capabilities to display images at high frame rates, making it suitable to play videos for instance. It is however incompatible with base R plotting functions. However you can use the drawing functions provided with Rvision to draw over images - destructively this time - before displaying them.

3.2.1 - Method compatible with base R

path_to_image <- system.file("sample_img", "bunny.png", package = "Rvision")
my_image <- image(filename = path_to_image)

abline(h = 400, col = "red", lwd = 5)
abline(h = 550, col = "red", lwd = 5)
abline(v = 430, col = "red", lwd = 5)
abline(v = 570, col = "red", lwd = 5)

3.2.2 - Method incompatible with base R

path_to_video <- system.file("sample_vid", "Balloon.mp4", package = "Rvision")
my_video <- video(filename = path_to_video)

# Create an empty display window (note: it can hide behind other windows)
newDisplay("My display", nrow(my_video) / 2, ncol(my_video) / 2)

# Display images (note: it creates the display window if it doesn't exist yet)
# The 3rd argument ('delay') is the minimum time in ms during which the image 
# should be displayed before it can be replaced
for (i in 1:25) {
  display(readNext(my_video), "My display", 25, nrow(my_video) / 2, ncol(my_video) / 2)

# Close display
destroyDisplay("My display")

# Close all opened displays

3.3 - Accessing/replacing parts of an image

You can access parts of an image in the same way you would do it with matrices and arrays in base R.

my_image[]          # Entire image
my_image[1, 1]      # Bottom-right pixel
my_image[1, ]       # Bottom row of pixels
my_image[, 1]       # Leftmost column of pixels
my_image[1:5, 1:5]  # All pixels between the 1st and 5th row and column
my_image[c(TRUE, FALSE), c(TRUE, FALSE)]  # Every other row and column of pixels

Note that images are not exactly like traditional matrices. Color images have multiple layers, each corresponsing to a dimension in the BGR or BGRA space (Blue, Green, Red, Alpha transparency). Therefore, when accessing a pixel of a color image, you will obtain 3 or 4 values in return. Grayscale images, on the other hand, function similarly to regular monolayer matrices in base R.

To replace parts of an image, you can use the <- assignment operator. With grayscale images, it works exactly like in base R with matrices.

my_gray_image <- changeColorSpace(my_image, "GRAY")
my_gray_image[1:250, 1:250] <- 0  # Turn the corresponding pixels to black

With color images however, you will need to supply 3 (for BGR images) or 4 (for BGRA images) values (or any multiple of 3 or 4 respectively).

my_image[1:250, 1:250] <- c(0, 0, 255, 255) # Turn the corresponding pixels to red

The utility function col2bgr provided by Rvision (not to be confused with col2rgb provided by the grDevices package and on which col2bgr is based) will conveniently convert any of the R-compatible color specifications to color codes compatible with Rvision images.

my_image[1:250, 1:250] <- col2bgr("blue", alpha = TRUE) # Turn the corresponding pixels to blue