Filter a Mask using a Region of Interest¶

Filter objects (connected regions of non-zero pixels) within a region of interest, either cut those objects to the region of interest or include objects that overlap with the region of interest.

plantcv.roi.filter(mask, roi, roi_type='partial')

returns filtered_mask

Important Note: If your ROI object detection does not perform first check that the ROI is completely within the image.

• Parameters:

  • mask = binary image data to be filtered
  • roi = region of interest, an instance of the Objects class, output from one of the pcv.roi subpackage functions
  • roi_type = 'partial' (for partially inside, default), 'cutto' (cut objects to the inside of the ROI), 'within' (keep only objects fully inside ROI) or 'largest' (keep only the largest contour)

• Context:

  • Used to filter objects within a region of interest and decide which ones to keep.

• Warning:

  • Using roi_type='largest' will only keep the largest outer connected region of non-zero pixels.

• Example use:

  • Use In VIS Tutorial
  • Use In PSII Tutorial

RGB image

Thresholded image (mask)

ROI visualization

from plantcv import plantcv as pcv

# Set global debug behavior to None (default), "print" (to file),
# or "plot" (Jupyter Notebooks or X11)
pcv.params.debug = "plot"

# ROI filter allows the user to define if objects partially inside ROI are included or if objects are cut to ROI.
filtered_mask = pcv.roi.filter(mask=mask, roi=roi, roi_type='partial')

Filtered mask with roi_type='partial'

from plantcv import plantcv as pcv

# Set global debug behavior to None (default), "print" (to file), or "plot" (Jupyter Notebooks or X11)
pcv.params.debug = "plot"

# ROI filter allows the user to define if objects partially inside ROI are included or if objects are cut to ROI.
filtered_mask = pcv.roi.filter(mask=mask, roi=roi, roi_type='cutto')

Filtered mask with roi_type='cutto'

Source Code: Here