pyopia.process

Module containing tools for processing particle image data

Functions

clean_bw(imbw, minimum_area)	Cleans up particles which are too small and particles touching the border
concentration_check(imbw[, max_coverage])	Check saturation level of the sample volume by comparing area of particles with settings.Process.max_coverage
expand_bbox(bbox, image_shape, fraction)	Expand a bounding box by a fraction of its width and height, clamped to image bounds.
extract_particles(imc, timestamp, ...[, ...])	Extracts the particles to build stats and export particle rois to HDF5 files
extract_roi(input_image, bbox)	Given a full image and bounding box, this will return the roi image from within the bounding box
get_spine_length(imbw_roi)	Extracts the spine length of particles from a binary particle image (imbw is a binary roi)
image2blackwhite_accurate(input_image, ...)	Converts corrected image (im_corrected) to a binary image using greythresh as the threshold value (some auto-scaling of greythresh is done)
image2blackwhite_fast(input_image, greythresh)	Converts an image (input_image) to a binary image using greythresh as the threshold value (fixed scaling of greythresh is done)
measure_particles(imbw[, max_particles])	Measures properties of particles
put_roi_in_h5(export_outputpath, HDF5File, ...)	Adds rois to an open hdf file if export_outputpath is not None.
segment(img[, threshold, minimum_area, ...])	Create a binary image from a background-corrected image.
statextract(imbw, timestamp, imc[, ...])	Extracts statistics of particles in a binary images (imbw)

Classes

CalculateImageStats()	PyOpia pipline-compatible class for collecting whole-image statistics
CalculateStats([max_coverage, ...])	PyOpia pipline-compatible class for calling statextract
Segment([minimum_area, threshold, ...])	PyOpia pipline-compatible class for calling segment