PlantCV v3.0.2

PlantCV v3.0.2 only changes PyPI authentication information.

PlantCV v3.0.1

PlantCV v3.0.1 adds a new Travis CI build method on git tags that should also trigger auto-deployment to PyPI.

PlantCV v3.0

With PlantCV v3.0 PlantCV should be available on PyPI (if all goes well). Big thanks to @HaleySchuhl and @dschneiderch for all the pull requests and all the other contributors.

PlantCV v3.0 contains the following new features/changes:

• plantcv.fill is now significantly faster using a scikit-image backend
• plantcv.median_blur now allows the kernel size to be asymmetric (a two-element tuple)
• Fixed issues with Read the Docs rendering
• Documentation was updated to fix typos, command examples, etc.
• Some test data was reduced in size to shrink the memory footprint during build tests
• Fixed some package usage syntax to avoid future method deprecation issues
• Added color card mask helper function
• Added color card checker analysis function
• Added color card auto detection method (thanks to @bhive01 for the method inspiration)
• Improved code testing coverage to 98%
• Added method to read raw Bayer images
• Updated plantcv.fluor_fvfm to accept 8-bit images in addition to 16-bit images
• Added conda environment YAML configuration files for quick conda installation

PlantCV v3.0.dev2

PlantCV v3.0.dev2 is an early release in the v3 release cycle. A full v3 will be released at a later date. While this is an early release, it should be considered essentially production-ready. Note that this release breaks previous syntax/functionality with the goal of making things easier. Updating existing code to the new styles should be fairly straightforward.

Overview of changes:

• The input and output device has been eliminated for all functions. The step counter still exists in the background.
• The input debug has been eliminated for all functions. It can now be set globally with the class Params: https://plantcv.readthedocs.io/en/latest/params/.
• The output location of images printed in debug mode can now be set using the plantcv.params.debug_outdir global setting: https://plantcv.readthedocs.io/en/latest/params/
• Some function arguments were refactored. Many were changed to make it more explicit what type of input image is required. The new vocabulary is generally: img = all image types, rgb_img = RGB images only, gray_img = Grayscale images only, bin_img or mask = Binary images only. Some other inputs were renamed for consistency and/or PEP8 formatting guidelines. All function call changes are summarized here: https://plantcv.readthedocs.io/en/latest/updating/#updating-to-v3.
• Several functions were removed and replaced with updated versions.
  • define_roi: replaced with the functions in the subpackage roi.
  • analyze_bound: replaced with the functions analyze_bound_horizontal and analyze_bound_vertical.
  • rotate_img: replaced with the function rotate.
  • The threshold functions binary_threshold, adaptive_threshold, otsu_auto_threshold, and triangle_auto_threshold were moved to a new subpackage and are now: plantcv.threshold.binary, plantcv.threshold.gaussian, plantcv.threshold.mean, plantcv.threshold.otsu, plantcv.threshold.triangle.
  • These changes are also summarized here: https://plantcv.readthedocs.io/en/latest/updating/#updating-to-v3.
• Testing coverage was increased to 94%.
• Some additional general documentation and docstring reformatting for consistency.
• The FAQ was updated.

PlantCV v3.0.dev1

PlantCV v3.0.dev1 is an early release in the v3 release cycle. A full v3 will be released at a later date. While this is an early release, it should be considered essentially production-ready.

Some features already included in the v3 release:

• Distance transformation
• Release of PlantCV through Docker containerization
• Full and tested Python2/3 and OpenCV2/3 compatibility
• Global settings and simplified API framework
• New boundary line tools
• Simplified region of interest (ROI) tools
• Color correction/standardization
• Package namespace reorganization
• Documentation improvements and bug fixes

PlantCV v2.1

The PlantCV release v2.1 is an update to the v2.0 release. The release contains some minor bug fixes and updated documentation based on feedback we received for the PlantCV v2.0 preprint.

PlantCV v2.0

The PlantCV release v2.0 marks the final commit used in our upcoming manuscript describing improvements to PlantCV since v1.0. If you are updating from v1, please see our instructions here.

A brief description of changes since the v1.0 release:

• Changed license from GPLv2 to MIT
• Reformatted code for PEP8 compliance
• General improvements for Python2.7 and 3 compatibility
• Updated documentation (installation methods, tutorials, contribution guide, function documentation)
• Added issue and pull request templates
• Added continuous integration (Travis CI)
• Added unit test coverage (Coveralls)
• Added continuous documentation (Read the Docs)
• Added Jupyter notebook integration
• Improved metadata parsing
• Rewrote the parallelization and data management tool in Python (plantcv-pipeline.py)
• New functions
  • White balance (white_balance)
  • Triangle auto-threshold (triangle_auto_threshold)
  • Otsu auto-threshold (otsu_auto_threshold)
  • Adaptive threshold (adaptive_threshold)
  • Gaussian blur (gaussian_blur)
  • Size marker normalization (report_size_marker_area)
  • Multi-plant detection (cluster_contours, cluster_contours_split_img, rotate_img, shift_img)
  • Combined image processing (get_nir, resize, crop_position_mask)
  • Watershed segmentation (watershed_segmentation)
  • Landmarking functions for morphometrics (acute, acute_vertex, x_axis_pseudolandmarks, y_axis_pseudolandmarks, scale_features)
• Added machine learning training (plantcv.learn submodule) and classifier tools
  • Training program (plantcv-train.py) with two methods:
    • Naive Bayes (naive_bayes)
    • Naive Bayes multiclass (naive_bayes_multiclass)
  • Classifier (naive_bayes_classifier)

Citation

Gehan MA., Fahlgren N., Abbasi A., Berry JC., Callen ST., Chavez L., Doust AN., Feldman MJ., Gilbert KB., Hodge JG., Steen Hoyer J., Lin A., Liu S., Lizárraga C., Lorence A., Miller M., Platon E., Tessman M., Sax T. 2017. PlantCV v2.0: Image analysis software for high-throughput plant phenotyping. PeerJ Preprints 5:e3225v1. DOI: 10.7287/peerj.preprints.3225v1.

PlantCV v1.1

This is a minor release that adds mkdocs build files to the v1.0 release so that documentation can be built automatically with readthedocs.

PlantCV v1.0

PlantCV release v1.0 marks the final commit used in our manuscript [1]. If you want to repeat an analysis from the paper, checkout tag v1.0 after cloning the repository.

1. Fahlgren N, Feldman M, Gehan MA, Wilson MS, Shyu C, Bryant DW, Hill ST, McEntee CJ, Warnasooriya SN, Kumar I, Ficor T, Turnipseed S, Gilbert KB, Brutnell TP, Carrington JC, Mockler TC, Baxter I (2015) A versatile phenotyping system and analytics platform reveals diverse temporal responses to water availability in Setaria. Molecular Plant, in press.