Plot Image With Clustering Information¶

This is a plotting method used to represent the way in which contours get clustered together into objects from pcv.cluster_contours.

plantcv.visualize.clustered_contours(img, grouped_contour_indices, roi_objects, roi_obj_hierarchy, nrow=1, ncol=1, bounding=True)

returns clustered_image

• Parameters:
  • img - RGB or grayscale image data for plotting.
  • grouped_contour_indices - Contour indices for which groups contours belong to. Output from pcv.cluster_contour
  • roi_objects - object contours in an image that are needed to be clustered.
  • roi_obj_hierarchy - object hierarchy
  • nrow - Optional row grid lines to get drawn (default nrow=1). If nrow is unchanged, grid lines don't get drawn.
  • ncol - Optional column grid lines to get drawn (default ncol=1). If ncol is unchanged, grid lines don't get drawn.
  • bounding - Optional circles to bound the individual clusters (default bounding=True)
• Context:
  • This function was written to allow users to debug pcv.cluster_contours and make sure that contours from the same plant are getting grouped together.
• Example use:
  • Below

Original image

from plantcv import plantcv as pcv

# Our input image was relatively large so increase global parameters 
pcv.params.text_size = 3 # Default = .55
pcv.params.text_thickness = 10 # Default = 2
pcv.params.line_thickness = 10 # Default = 5

# Create a figure using output from pcv.cluster_contours 
clustered_image = pcv.visualize.clustered_contours(img=img, grouped_contour_indices=cnt_i, 
                                                   roi_objects=roi_obj,
                                                   roi_obj_hierarchy=hier, bounding=True)

# Create a figure using output from pcv.cluster_contours with a grid
clustered_image = pcv.visualize.clustered_contours(img=img, grouped_contour_indices=cnt_i, 
                                                   roi_objects=roi_obj,
                                                   roi_obj_hierarchy=hier,
                                                   nrow=4, ncol=6, bounding=True)

Clustered Image:

Clustered Image with Grid:

Source Code: Here