PlantCV v3.9.0

Version 3.9 updates:

• plantcv.morphology.find_tips and plantcv.morphology.find_branch_pts now saves observations (a list of coordinates of the relevant points identified from a skeleton image) to the Outputs class.
• Reworked the plantcv.color_palette function to use matplotlib colormaps instead, so users now have a wide range of coloring options.
  • Added three new parameters to pcv.params to control color_palette (and functions that use it). The parameters are color_scale: the name of the colormap, color_sequence: "sequential" or "random", and saved_color_scale: stores the last color scale. The latter is important for the morphology functions to plot results correctly as the colors of the segments need to get reused to match up from function to function.
• Add plantcv.morphology.analyze_stem
  • This function measures stem height, length, and angle from sorted segments of a skeletonized plant.
  • Plots debug image that shows detected height and angle
• Internal updates to the plantcv.transform.find_color_card function
  • Updates to the contour sorting algorithm to compensate for changes in the outputs of the OpenCV function cv2.minAreaRect in version 3.4.10. Their updates were having implications in the sensitivity of the PlantCV algorithm and causing colorcards to stop being identified in example images.
  • This function now also stores observations to the Outputs class for the mean/median (user defined) color chip area, height, and width. This functionality should remove the need to to include a size marker for scaling measurements in images that already have a color card.
• Updates the documentation and README file to fix a few typos/formatting issues and update some content for relevance to the current version of PlantCV.
• Update/bugfix to plantcv.hyperspectral.calibrate
  • There was a mistake in the calibration code that resulted in the actual algorithm differing slightly from the proposed (raw-dark)/(white-dark).
  • Now also truncate any negative values to 0
• PEP8 and other miscellaneous code cleanup to clear the way for GitHub Actions
• Replace prior continuous integration platform with GitHub Actions
• Add plantcv.spatial_clustering
  • New function that segments features of images based on their distance from each other.
  • Takes a binary mask, minimum number of clusters, which algorithm to use (either “DBSCAN” or “OPTICS”), the maximum distance between two pixels before they can be considered part of the same cluster, and outputs a clustered image as well as the masks of each cluster.
• Update Dockerfile recipe to fix missing libGL dependency, which was causing an ImportError
• Update plantcv.hyperspectral.read_data, which is used if mode=”ENVI” during plantcv.readimage so that we now set a default wavelength units to “nm” to enable more flexibility in the image files that we can read in.
• Bugfix to the data getting saved out to the hue_circular_std observation while running plantcv.analyze_color.
• Add summary statistics to the observations recorded while running plantcv.analyze_nir so they now include mean, median, and stdev observations in the Outputs class while running NIR workflows.
• Update the order of debug images plotted to match the order of outputs in plantcv.rectangle_mask and plantcv.threshold.*.
• Updated and improved documentation for the machine learning tutorial.
• Update plantcv.threshold.custom_range to be R,G,B instead of B,G,R
• Added many new indices and completely restructured the spectral index family of options into their own functions beneath the spectral_index sub-package.
  • See here for the latest list of supported spectral indices.
• Add plantcv.visualize.auto_threshold_methods which aims to assist in streamlining workflow development.
• Update input parameter in the function plantcv.threshold.custom_range from rgb_img to img since the function also works on grayscale images.
• Internal enhancements to the plantcv.hyperspectral.extract_index to significantly increase speed and decrease memory needed for hyperspectral workflows.
• Add plantcv.stdev_filter
  • Creates a grayscale image of pixel-wise standard deviation from a grayscale input image
• Made two small updates to plantcv.utils.sample_images
  • Removes newline characters from each row of SnapshotInfo.csv
  • Only appends rows of SnapshotInfor.csv to a list for random sampling if the row has image data records
• Removed a Non-ascii character causing an error.

Version 3.9 breaking changes:

• Update input parameter in the function plantcv.threshold.custom_range from rgb_img to img since the function also works on grayscale images.
• Removed plantcv.hyperspectral.extract_index and replaced it with the plantcv.spectral_index subpackage (see above).