opencv: OpenCV Computer Vision

In opencv: Bindings to 'OpenCV' Computer Vision Library

OpenCV Computer Vision

Description

Tools to experiment with computer vision algorithms. Use ocv_read and ocv_write to load/save images on disk, or use ocv_picture / ocv_video to use your webcam. In RSudio IDE the image objects will automatically be displayed in the viewer pane.

Usage

ocv_face(image)

ocv_facemask(image)

ocv_read(path)

ocv_write(image, path)

ocv_destroy(image)

ocv_bitmap(image)

ocv_edges(image)

ocv_picture()

ocv_resize(image, width = 0, height = 0)

ocv_mog2(image)

ocv_knn(image)

ocv_hog(image)

ocv_blur(image, ksize = 5)

ocv_sketch(image, color = TRUE)

ocv_stylize(image)

ocv_markers(image)

ocv_info(image)

ocv_copyto(image, target, mask)

ocv_display(image)

ocv_video(filter, stop_on_result = FALSE)

ocv_grayscale(image)

ocv_version()

Arguments

image	an ocv image object created from e.g. ocv_read()
path	image file such as png or jpeg
width	output width in pixels
height	output height in pixels
ksize	size of blurring matrix
color	true or false
target	the output image
mask	only copy pixels from the mask
filter	an R function that takes and returns an opecv image
stop_on_result	stop if an object is detected

Examples

# Silly example
mona <- ocv_read('https://jeroen.github.io/images/monalisa.jpg')

# Edge detection
ocv_edges(mona)
ocv_markers(mona)

# Find face
faces <- ocv_face(mona)

# To show locations of faces
facemask <- ocv_facemask(mona)
attr(facemask, 'faces')

# This is not strictly needed
ocv_destroy(mona)

opencv documentation built on Oct. 4, 2024, 9:06 a.m.