Update how functions use contours and hierarchies

Update how functions use contours and hierarchies

Description

• Many functions in PlantCV output and require the user to input contours and hierarchies. Often the functions that need contours and hierarchies as input also take a mask. It might be easier to hide contours and hierarchies from users all together since these can be found from the masks that get input. It is more or less repetitive info.
• Functions that deal with multiple plants, i.e. pcv.roi.multi() and pcv.cluster_contours(), could instead return a list of masks and we could handle multiple objects within the pcv.analyze_* functions.
• Under this restructuring we could change the way we think of entities (in regards to data stored to the Outputs class and printed out when a workflow is run in parallel over a set of images). Right now, individual images are usually an entity but in the case where images contain more than one plant it might make more sense to treat individual plants as separate entities. We can differentiate between these by naming the entities with information about it’s position in addition to the image filename. pcv.roi.multi() allows for irregular plant layout so the entity can be named after the filename of the original image plus the center of the ROI used to identify the plant.

Details

• If these updates seem beneficial they will impact all functions outputting contours, all functions requiring a contour input, enhancing all analyze_* functions to allow for multiple entities per image, and the Outputs data storage/json data output/json2csv function.

Completion Criteria

For a discussion:

• Discuss and develop requirements docs
• Create issues for next steps

[dschneiderch]

I don’t really understand how a contour class vs contour list would differ so I can’t comment on that, but avoiding user-triggered for loops for multiple roi would really help readability and intuitiveness.

[HaleySchuhl]

This is kind of in progress now. Once plantcv-workflow.py is updated we plan to start transitioning each PlantCV function over to accept data object class instances to simplify parameters for many functions. This is in progress since the new functions getting added to the hyperspectral sub-package (since it’s relatively separate from other pcv functions) have been written to utilize a class system to attach all sorts of metadata to a hyperspectral datacube or spectral index.