Plantcv

[](https://doi.org/10.5281/zenodo.3483049)

* Add a new template for opening an issue for discussions, requesting a new feature, and for reporting an issue/requesting help.
* Give more detail in documentation (how to change version of documentation, types of images compatible with workflow parallelization, example batch script for windows).
* Updates to `plantcv.analyze_color`. Users are given the option to create histograms from data about all available colorspaces or just a subset but data was getting stored out for all channels regardless of the selected colorspace. Update so that only data requested gets saved out (since color frequency data is verbose).
* Update method for `plantcv.apply_mask` to make it more robust to the types of data that can get masked.
* Bugfix with `plantcv.cluster_contours` to allow number of row and/or columns to exceed 9.
* Update method for `plantcv.roi_objects` since the old algorithm fails when a ROI is small enough to be fully enclosed by a contour.
* Bugfix for the sorting algorithm within `plantcv.morphology.segment_insertion_angle` since it was overly sensitive.
* Update docker.

[](https://doi.org/10.5281/zenodo.3375003)

PlantCV v3.6.0 adds new functionality and fixes several bugs.

Summary of changes
* Updated `pcv.visualize.pseudocolor` to stop scaling the background values
* Add image dataset random sampling tool `plantcv-utils.py sample_images`
* Added custom ROI polygon tool `pcv.roi.custom`
* Added grayscale image value rescaling function `pcv.transform.rescale`
* Fixed bug in `pcv.roi_objects` for evaluating the largest contour
* Fixed bugs in documentation
* Added function for correcting for non-uniform illumination `pcv.nonuniform_illumination`
* Restricted scikit-image dependency to v0.14.2 to bypass an issue with v0.14.3 in Windows
* Added function to generate kernel structuring elements
* Added pip to conda environment dependencies in `environment.yml`
* Added improvements to `pcv.morphology` functions
* Make it optional for the first segment to be classified as stem regardless in the segment_sort function
* Update method for sorting through segments in the segment_insertion_angle function, makes it quicker and more robust to measuring every leaf.
* Update plotting method for segment_id since the previous method can give a weird artifact when plotting segments that have been combined.
* Update pruning function
* Removing old warnings that aren't really relevant anymore

[](https://doi.org/10.5281/zenodo.3338666)

PlantCV v3.5.0 adds new functionality and fixes several bugs and usability issues.

Summary of changes:

- Added `pcv.analyze_thermal_values` to handle thermal data analysis.
- Update Dockerfile
- Added a thermal tutorial
- Added functionality to `pcv.readimage` to allow it to handle .csv format files for thermal imaging.
- Add ` pcv.visualize.clustered_contours` which creates an image that assists with debugging parameters upstream of using `pcv.cluster_contours`
- Bug fix regarding listing observations while running PlantCV parallel workflows.
- Removed legacy format where `pcv.analyze_*` functions returned lists. When a function returns a single image it will no longer store that image inside a list object.
- Various documentation updates and improvements
- The function `pcv.within_frame` now stores an observation in addition to returning a boolean to the user

[](https://doi.org/10.5281/zenodo.3249350)

PlantCV v3.4.1 is an intermediate release to address a few issues, particularly with the new JSON output data format.

**Summary of changes**:

* Updated format of JSON output files
* Added `plantcv-utils.py` script with a `json2csv` conversion tool for exporting CSV files from the JSON output data
* `plantcv-workflow.py`, `plantcv-train.py`, and `plantcv-utils.py` are now installed in the environment `bin` directory
* `pcv.visualize.pseudocolor ` now has the ability to apply custom padding when cropping
* Updated skeleton pruning algorithm
* Combined pruning and skeleton segmentation
* Put the iterative pruning method into an internal function
* set roi_type='partial' default for the roi_objects function
* Add fill_holes function that does a flood fill on black holes inside a binary mask
* Various documentation updates and improvements
* Updated the `analyze_nir_intensity` function to use `cv2.calcHist` instead of `np.histogram`

[](https://doi.org/10.5281/zenodo.3236323)

[](https://doi.org/10.5281/zenodo.3122076)

PlantCV v3.3.0 adds new functionality and fixes several bugs and usability issues. Big thanks to HaleySchuhl, dschneiderch, JLJ90, huberma, and karnoldbio for work and guidance on the updates below.

**Summary of changes**:

* Added `plantcv.visualize` sub-package
* Moved `pseudocolor` and `histogram` into sub-package
* Added `colorize_masks` function to sub-package to make false-colored images from a set of binary masks (e.g. output masks from the naive Bayes classifier)
* Added `plantcv.opening` and `plantcv.closing` functions (removes salt and pepper noise)
* Added `plantcv.threshold.custom_range` function (threshold based on upper and lower values)
* Added `plantcv.within_frame` function (tests if object, in a binary image, is within the field of view)
* Added `plantcv.morphology` sub-package
* Added `skeletonize` function to sub-package (skeletonizes a binary image)
* Added `prune` function to sub-package (removes spurs from skeleton)
* Added `check_cycles` function to sub-package (checks for connected cycles in skeleton)
* Added `find_branch_pts` function to sub-package (finds branch points in skeleton)
* Added `find_tips` function to sub-package (finds tips in skeleton)
* Added `segment_skeleton` function to sub-package (segments a skeleton into component paths)
* Added `segment_sort` function to sub-package (sorts segments into primary and secondary groups)
* Added `segment_id` function to sub-package (plots/labels segment IDs)
* Added `segment_path_length` function to sub-package (calculates segment lengths)
* Added `segment_euclidean_length` function to sub-package (calculates segment Euclidean lengths)
* Added `segment_curvature` function to sub-package (calculates the ratio of path length to Euclidean length)
* Added `segment_angle` function to sub-package (calculates the overall angle of the segment)
* Added `segment_insertion_angle` function to sub-package (calculates the angle that a segment intersects another segment)
* Added `segment_tangent_angle` function to sub-package (calculates the angle between the tangents of the ends of each segment)
* Added `parallel` sub-package.
* The sub-package contains functions that were originally from the `plantcv-pipeline.py` script file
* Renamed `plantcv-pipeline.py` to `plantcv-workflow.py`
* Removed SQLite database and requirements. Data are now output in a JSON-formatted text file
* `plantcv.print_results` now outputs data in JSON format
* The `Outputs` class now stores data in a single dictionary
* Added `add_observation` method to the `Outputs` class. Allows user to add custom observations to the output
* Output observations are stored by a unique variable name along with a trait name, method, scale (units), data type, value, and label(s)
* Keep 1st generation sub contours when using 'largest' in `roi_objects`
* In `analyze_color`, color and color property scales now use the conventional scale for each type (e.g. hue is a value from 0-359 degrees while green is a value from 0-255)
* Added summary statistics for hue in `analyze_color`: median hue value, circular mean hue value, and the circular mean standard deviation of hue
* Removed the `bins` argument from `analyze_color`