Visualize All Auto-Thresholding Methods

This is a plotting method used to represent various auto-thresholding methods available in PlantCV. These include Gaussian, triangle, mean, and Otsu.

plantcv.visualize.auto_threshold_methods(gray_img, grid_img=True, object_type="light")

returns labeled_imgs

  • Parameters:
    • gray_img - Grayscale image data
    • grid_img - Whether or not to compile masks into a single plot
    • object_type - "light" or "dark" (default: "light"). If object is lighter than the background then standard thresholding is done. If object is darker than the background then inverse thresholding is done.
  • Context:
    • This function returns a list of the labeled binary masks that get created. The list needs to be subset in order to further manipulate the labeled images.
    • All auto threshold functions operate under default parameters (e.g. xstep=1 in pcv.threshold.triangle()) apart from the user defined object_type.
  • Example use:
    • Below

Original image


from plantcv import plantcv as pcv
pcv.params.debug = "plot"

# Our input image was relatively large so increase global parameters 
pcv.params.text_size = 2.2       # Default = .55
pcv.params.text_thickness = 4    # Default = 2

# Visualize all auto threshold methods  
labeled_imgs = pcv.visualize.auto_threshold_methods(gray_img=gray_img, grid_img=True, object_type="light")

Grid Image:


Source Code: Here