Analyze Color

Extract color data of objects and produce pseudocolored images, can extract data for RGB (Red, Green, Blue), HSV (Hue, Saturation, Value) and LAB (Lightness, Green-Magenta, Blue Yellow) channels.

plantcv.analyze_color(rgb_img, mask, hist_plot_type=None)

returns data analysis images

  • Parameters:
    • rgb_img - RGB image data
    • mask - binary mask of selected contours
    • hist_plot_type - None (default), 'all', 'rgb','lab' or 'hsv', this is the data to be printed to an SVG histogram file, however all (every channel) data is still stored to the database.
  • Context:
    • Used to extract color data from RGB, LAB, and HSV color channels.
    • Generates histogram of color channel data. Data automatically gets stored into the Outputs class. Users can look at the data collected at any point during the workflow by using pcv.print_results which prints all stored data to a .json file.
  • Example use:
  • Output data stored: Summary of Output Observations

Original image


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 = "print"

# Analyze Color

analysis_images = pcv.analyze_color(rgb_img, mask, 'all')

Histograms of (R, G, B), (H, S, V), and (L, A, B) color channels


Pseudocolored value-channel image

Note: The grayscale input image (e.g. value-channel) and object mask can be used with the pcv.visualize.pseudocolor function which allows the user to pick a colormap for plotting.