Plantcv

* Refactored plantcv.fluor_fvfm which is now plantcv.photosynthesis.analyze_fvfm to be consistent with the naming of other analysis functions. Input parameters are unchanged.

[](https://doi.org/10.5281/zenodo.4024970)

* 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).

[](https://doi.org/10.5281/zenodo.3956488)

[](https://doi.org/10.5281/zenodo.3700183)

* Fixed a few missing pages and broken links within the documentation.
* Add `plantcv.hyperspectral.analyze_index`
* This function now accepts min/maximum bin labels, or can auto-calculate bins based on image data range.
* Collects frequency data for all integrated indices (mean, median, std, frequency).
* Optionally plots a histogram of frequency values.
* Add links to source code throughout documentation pages. This allows users to more easily find the raw, source code for those interested in learning more of the mechanics of a function than the documentation page provides.
* Adds a `border_width` parameter to `plantcv.within_frame`.
* Allows the user to specify how many pixels from the image edge they want to consider for detecting out-of-frame objects.
* The default is 1 px, which maintains the previous default behavior.
* Made some updates to the documentation based on usage on Windows.
* Update dependencies in `requirements.txt`
* Add `plantcv.roi.roi2mask` which allows user to create a binary mask from any contour.
* Added `plantcv.plantcv.visualize.colorspaces` which
* Used to quickly view all potential colorspaces, that are often used for thresholding/object segmentation steps.
* Plots out an image will all potential colorspaces, labeled with which colorspace each is, next to the original image.
* Add indices to the `plantcv.hyperspectral.extract_index` function
* Add PRI (Photochemical reflectance index)
* Add ARI (anthocyanin reflectance index)
* Add ACI (anthocyanin content index)
* Add and update `plantcv.hyperspectral.analyze_spectral` function
* Was storing out information, mainly about the global statistics like the maximum reflectance value for the entire datacube.
* Average reflectance per band was the only per-band measurement that we had been doing but really most of the stats could be per-band rather than global.
* Modify various .npz test data files in code tests (avoid using Numpy object arrays and the pickle module)
* In plantcv.transform.create_color_card_mask() the exclude input option required users to input excluded color chip IDs in descending numerical order.
* Adds `plantcv.threshold.saturation` function for masking saturated pixels.
* Any channel at or above a certain threshold
* All channels at or above a certain threshold.
* The user can also pick this threshold (default = 255).

[](https://doi.org/10.5281/zenodo.3561216)

* Dropped Python v2.7 support (https://python3statement.org/).
* Added a Hyperspectral tool sub-package:
* Read in ENVI hyperspectral data with new option for the existing `plantcv.readimage` function. While reading in hyperspectral data a pseudo-rgb image is also created.
* Calibrate raw hyperspectral image data with white and dark reference images with `plantcv.hyperspectral.calibrate`.
* Calculate indices (e.g. NDVI) from a hyperspectral datacube with `plantcv.hyperspectral.extract_index`.
* Extract bands from a hyperspectral datacube that are the closest to user defined wavelengths with `plantcv.hyperspectral.extract_wavelength`.
* Add functionality to the existing function `plantcv.apply_mask` that allows users to mask hyperspectral images.
* Add documentation pages and edit existing documentation pages to reflect all additions.
* Add a hyperspectral workflow tutorial.
* Add documentation
* Underlying functions used in `plantcv-workflow`.
* Information about updating PlantCV.
* Minor update to `plantcv.morphology.segment_sort` to ensure the function is robust.
* Enhance various region of interest `plantcv.roi.*` functions to draw the debug image before hitting the fatal error when an ROI extends beyond the image boundaries and start printing a warning if a user defined grid causes ROI's to overlap