Detect Circles in a Maze Image

Description

The function first applies the Canny edge detection algorithm to the input image. It then detects circles corresponding to the board and holes using the detectCircles function. The function filters the detected hole circles based on their distance from the board circle, ensuring they fall within acceptable ranges relative to the specified radii. Finally, it calculates the median radius and angle differences of the remaining circles and constructs a circular representation for the holes based on these parameters.

Usage

detectBarnes(im, boardRadius, holeRadius, sigma = 25, plot = TRUE)

Arguments

Details

Detects circles representing boards and holes in a given image of a maze. It utilizes edge detection to identify potential circle patterns based on specified radius parameters. The function returns the detected circles' coordinates, along with additional information about the board and hole radii.

Value

A list containing:

Examples

path <- system.file('extdata/data.tiff', package='BioTrajectory')
im <- tiff::readTIFF(path)
im <- imager::as.cimg(t(im[,,1]))
Barnes <- detectBarnes(im, boardRadius=207, holeRadius=13, sigma=25)

Calculates distances to a target point

Description

Given a dataset of points, it computes the Euclidean distances from each point to a specified target point. The function also identifies contiguous segments of points that fall within a specified radius around the target.

Usage

distanceToTarget(data, target, targetRadious = 0)

Arguments

Value

A list containing:

Examples

# Create an example data matrix
data <- matrix(c(1, 1, 2, 2, 3, 3), ncol = 2, byrow = TRUE)
target <- c(2, 2)
result <- distanceToTarget(data, target, targetRadious = 0)
print(result)

Calculates the total distance traveled through a series of points.

Description

Computes the cumulative distance between consecutive points in a given set of coordinates. It sums the Euclidean distances between each pair of adjacent points, providing the total distance traveled along the path defined by the points.

Usage

distanceTraveled(points)

Arguments

Value

A numeric value representing the total distance traveled through the points.

Examples

# Define a set of points
points <- matrix(c(0, 0, 1, 1, 2, 0), ncol = 2, byrow = TRUE)
# Calculate the distance traveled
total_distance <- distanceTraveled(points)
# Print the total distance
print(total_distance)

Estimate the Radius of a Circle Fitting Four Points

Description

This function estimates the center and radius of a circle that best fits four points provided by the user. The user interacts with the plot to select four points, and the function optimizes the parameters (center and radius) using a least squares approach.

Usage

getRadius(frame)

Arguments

Details

The function plots the provided 'frame' and then uses the 'locator()' function to allow the user to click on four points. The function then performs optimization using the 'optim()' function to minimize the difference between the selected points and the circle's equation.

The objective function ('ftemp') calculates the sum of squared differences between the points and the expected distance from the circle's center.

Value

A vector of length 3, where: - The first element is the x-coordinate of the circle center (cx). - The second element is the y-coordinate of the circle center (cy). - The third element is the radius of the circle (r).

Examples

if(interactive()){ 
path <- system.file('extdata/data.tiff', package='BioTrajectory')
im <- tiff::readTIFF(path)
im <- imager::as.cimg(t(im[,,1]))
frame <- plot(im)
circle_params <- getRadius(frame)
print(circle_params)
}

Get Object Trajectory from Image Sequence

Description

This function calculates the trajectory of an object in a sequence of images. It compares each frame to a background image to detect movement. The function identifies the largest object in each frame and calculates its centroid coordinates across the sequence.

Usage

getTrajectory(listImages, Barnes, iBackground, iBegin, iEnd)

Arguments

Details

The function reads the images from 'listImages' and compares each frame to the background image specified by 'iBackground'. Background subtraction is performed using the 'removeBackground()' function, followed by thresholding to identify significant changes between the background and the current frame. The largest connected component in the thresholded image is assumed to be the object of interest, and its centroid is calculated. The trajectory is tracked across frames, and the centroid coordinates are returned for each frame.

Value

A data frame with two columns: the x and y coordinates of the object centroid in each frame. If no object is detected in a frame, the coordinates are set to 'NA'.

Examples

 
 # Not run:
 path <- system.file('extdata/frames', package='BioTrajectory')
 images <- list.files(path, full.names = TRUE)
 B <- list(c1 = structure(list(x = 342L, y = 263L), row.names = 1L, class = "data.frame"),
    r1 = 207, c2 = structure(list(x = c(157L, 172L, 202L, 245L,
    297L, 352L, 408L, 455L, 494L, 517L, 522L, 507L, 476L, 430L,
    375L, 318L, 262L, 215L, 180L, 160L), y = c(242L, 188L, 141L,
    105L, 85L, 80L, 93L, 124L, 166L, 219L, 277L, 334L, 383L,
    420L, 440L, 442L, 426L, 394L, 350L, 298L), class = "data.frame"), r2 = 13))
 trajectory <- getTrajectory(images, B, 1, 1, 1)
 print(trajectory) 
 

Creates a heatmap from a set of points.

Description

Generates a heatmap based on the density of points in a given dataset. It utilizes kernel density estimation to visualize the concentration of points, allowing for adjustments in color palette and plotting limits.

Usage

heatmapFromPoints(data, plim = NULL, plot.pal = TRUE, ...)

Arguments

Value

A matrix of density values corresponding to the heatmap.

Examples

# Generate example data
set.seed(123)
data <- data.frame(x = rnorm(1000), y = rnorm(1000))

# Create a heatmap from the points
heatmap_result <- heatmapFromPoints(data)

Interpolates a trajectory

Description

Given a dataset of points, it interpolates to generate intermediate points between them.

Usage

interpolateTrajectory(data, n = 4)

Arguments

Value

A data frame containing the 'x' and 'y' coordinates, which includes both the original points and the interpolated points.

Examples

# Create an example data frame
data <- data.frame(x = c(1, 2, 3), y = c(1, 4, 9))
# Interpolate the trajectory
interpolated <- interpolateTrajectory(data, n = 4)
print(interpolated)

Finds the nearest targets to a set of points within a specified radius.

Description

Calculates the distances between a set of points and target locations. It identifies the nearest target for each point and checks if the distance is within a specified radius. If a target is found within the radius, its index and distance are returned; otherwise, -1 is returned for both.

Usage

nearestTarget(points, targets, r)

Arguments

Value

A data frame with two columns:

Examples

# Define a set of points and targets
points <- matrix(c(1, 2, 3, 4), ncol = 2)
targets <- matrix(c(2, 3, 5, 6), ncol = 2)
radius <- 2

# Find the nearest targets
nearest_results <- nearestTarget(points, targets, radius)

# Print the results
print(nearest_results)

Read and Resize an Image

Description

This function reads an image from a file path and resizes it to a specified number of rows. It supports several image formats, including JPG, JPEG, PNG, TIFF, and TIF. The function also converts the image into a suitable format for further processing.

Usage

readImage(path, resizeRows)

Arguments

Details

The function detects the image format based on the file extension. It currently supports the following formats: JPG, JPEG, PNG, TIFF, and TIF. If the image has more than 3 dimensions (such as an RGBA image with an alpha channel), the alpha channel is discarded. The image is resized only if its height exceeds the specified 'resizeRows'.

Value

A cimg object containing the resized image.

Examples

# Example usage
img_path <- system.file('extdata/data.tiff', package='BioTrajectory')
img <- readImage(img_path, resizeRows = 500)
plot(img)  # Visualizes the resized image

Reads tracking data from a specified file.

Description

Reads a text file containing tracking data, where each line represents coordinates. If a line contains "null", it adds NA values for that entry. Optionally, it can remove rows with NA values.

Usage

readtrackData(file, na.rm = FALSE)

Arguments

Value

A data frame with two columns ('x' and 'y') containing the coordinates read from the file. If 'na.rm' is TRUE, rows with NA values are omitted.

Examples

# Read tracking data from a file
path <- system.file('extdata/track.txt', package='BioTrajectory')
tracking_data <- readtrackData(path, na.rm = TRUE)
# Print the resulting data frame
print(tracking_data)

Image Frame Selector and Viewer

Description

This function provides an interactive image frame viewer where the user can navigate through a sequence of images and select a specific one. The viewer uses buttons for navigation (previous and next) and an option to select an image. The function uses the 'rp.control' to create a window for the interface, and 'grid' for displaying images.

Usage

selFrame(image_files)

Arguments

Details

The function displays a sequence of images from the provided file paths, allowing the user to navigate between them using "Previous" and "Next" buttons. The images are displayed using 'grid.raster' from the 'grid' package. A "Select" button allows the user to select the current image, and the function returns the index of the selected image.

Value

The index of the selected image.

Examples

# Not run:
path <- system.file('extdata/frames/', package='BioTrajectory')
image_files <- list.files(path, pattern = "\\.png$", full.names = TRUE)
selFrame(image_files)

Visualizes the distance to the target in a plot.

Description

This function generates a plot of the distance to a target over time or some other associated parameter in the object. It also draws a horizontal line to indicate the target radius and a red segment that shows the start and length of a parameter associated with the 'obj'.

Usage

showDistanceToTarget(obj, ...)

Arguments

Details

This function generates a line plot of the distance to a target (stored in 'obj$distance'). It also draws a red horizontal line at the value of 'obj$targetRadious' to indicate the target's radius. Additionally, a red vertical segment is drawn to show the start of the range defined by 'obj$r$start' and the length defined by 'obj$r$length'.

Value

A plot showing the relationship between the object's position and the target's position.

Examples

# Create a fictional object with example data
obj <- list(
  distance = rep(c(5, 10, 15, 20, 15, 10, 5),5),
  targetRadious = 12,
  r = list(start = 2, length = 10)
)
# Visualize the distance to the target using the function
showDistanceToTarget(obj)

Displays a trajectory plot from a set of coordinates.

Description

Visualizes the trajectory represented by a series of points. The function can display the full trajectory or a subset based on a specified step size. It supports customizable color palettes for enhanced visualization.

Usage

showTrajectory(data, stepSize = 0, pal)

Arguments

Value

A plot displaying the trajectory based on the provided coordinates and settings.

Examples

# Generate example trajectory data
path <- system.file('extdata/track.txt', package='BioTrajectory')
data <- BioTrajectory::readtrackData(path)
data <- na.omit(data)
palette <- grDevices::colorRampPalette(c("purple","blue","cyan","yellow","orange","red"))
# Show the full trajectory
showTrajectory(data, stepSize = 0, pal = palette)
# Show the trajectory with a step size of 36
showTrajectory(data, stepSize = 36, pal = palette)

Extract Frames from a Video and Save as Images

Description

This function is a wrapper that simplifies extracting frames from a video. It processes the video file and saves the frames as PNG images in the specified directory. By default, it extracts 15 frames per second.

Usage

videoToFrames(videoPath, outputDir, fps=15)

Arguments

Value

A list of file paths to the generated images.

Examples

# Not run:
videoPath <- system.file('extdata/video.mp4', package='BioTrajectory')
outputDir <- system.file('extdata/frames/', package='BioTrajectory')
images <- videoToFrames(videoPath, outputDir, fps=15)
print(images)  # Displays the paths to the generated images