util

Author: Chris Dijkstra Date: 11/10/2023

Utility functions for image analysis

lettuceSee.util.crop_region(image, centre, shape)

Crops an image area of specified width and height around a central point

Parameters:

image (ndarray) – matrix representing the image
centre (tuple[int, int]) – x and y coordinate of the centre as integers
shape (tuple[int, int]) – contains the height and width of the subregion in pixels as integers

Return type:

ndarray

Returns:

The cropped region of the original image

lettuceSee.util.read_fimg(filename)

Reads a fimg image from a file and outputs the corresponding np.ndarray

Parameters:: filename (str) – name of the file that is to be opened
Return type:: ndarray
Returns:: 2D array representing the fimg image

lettuceSee.util.scale_zero_to_one(im_channel)

Takes a 2d array and makes its values range from 0 to 1

Parameters:: im_channel (ndarray) – numpy array with 2 dimensions
Return type:: ndarray
Returns:: input channel scaled from 0 to 1.

lettuceSee.util.multichannel_mask(image, mask)

Takes an image and applies a mask to every channel

Parameters:

image (ndarray) – 3 dimensional array representing an image
mask (ndarray) – 2d binary mask

Return type:

ndarray

Returns:

masked input image

lettuceSee.util.paint_col(image, mask, color_tuple)

Makes masked area the specified color

Parameters:

image (ndarray) – 3d array representing an RGB image
mask (ndarray) – 2d binary mask
color_tuple (tuple[int, int, int]) – contains the values in integer of the R, G and B channel that you want to paint

Return type:

ndarray

Returns:

same as input image but with the masked area painted in the specified color

lettuceSee.util.threshold_between(image, x_low=None, x_high=None, y_low=None, y_high=None, z_low=None, z_high=None, and_mask=True)

Thresholds an image array for being between two values for each channels

Parameters:

image (ndarray) – 3d matrix representing the image
x_low (float | int) – low boundary for channel 1. Defaults to minimum of channel 1.
x_high (float | int) – high boundary for channel 1. Defaults to maximum of channel 1.
y_low (float | int) – low boundary for channel 2. Defaults to minimum of channel 2.
y_high (float | int) – high boundary for channel 2. Defaults to maximum of channel 2.
z_low (float | int) – low boundary for channel 3. Defaults to minimum of channel 3.
z_high (float | int) – high boundary for channel 3. Defaults to maximum of channel 3.
and_mask (bool) – if true returned mask is only true when all thresholds apply. If false returned mask is true if at least one of the thresholds apply.

Return type:

ndarray

Returns:

binary mask

lettuceSee.util.label_horizontally(mask, left_right=True)

Labels images from left to right

Parameters:

mask (ndarray) – Binary mask of objects that need to be labelled
left_right (bool) – If true labels left to right, if false right to left

Return type:

ndarray

Returns:

Mask of labelled objects

lettuceSee.util.parse_coord_file(filename)

Parser for ImageJ xy.txt output files

Parameters:: filename (str) – The input file
Return type:: list[tuple[int, int]]
Returns:: List where each element is a tuple of ints in form (x, y)