plant-seg-tools

Simple python tools for plant-seg https://github.com/hci-unihd/plant-seg

Index

• Install PlantSeg Tools
• Segmentation to Meshes
• Proofreading tool
• Automated Segmentation Proofread from seeds
• Evaluation

Install PlantSeg Tools

• Install plant-seg from https://github.com/hci-unihd/plant-seg
• activate plant-seg environment using:

conda activate plant-seg

• clone this repository locally on our machine, in the terminal navigate to the desired install location and execute:

git clone https://github.com/hci-unihd/plant-seg-tools.git

• install plant-seg-tools:

cd plant-seg-tools
pip install .

Additional dependencies

While having your conda environment activated:

• In oder to use seg2mesh

conda activate plant-seg
pip install -U "ray[default]"
conda install conda-forge::vtk

• In order to use the trimesh backend of plantsegtools/meshes, you will need to install trimesh using:

conda install -c conda-forge trimesh

• In order to use the training configurator wizard you need to install PyInquirer

pip install PyInquirer

Install proofreading tool

• create a new conda environment (at the moment plant-seg and the proofreading tools are not compatible). On a fresh terminal execute:

conda create -n plant-seg-proofreading -c conda-forge python numpy numba scipy matplotlib scikit-image pyaml h5py tqdm napari pyqt=5.12.3
conda activate plant-seg-proofreading

• clone this repository locally on our machine, in the terminal navigate to the desired install location and execute:

git clone https://github.com/hci-unihd/plant-seg-tools.git

• install plant-seg-tools:

cd plant-seg-tools
pip install .

Segmentation to Meshes

Basic usage

From the project root (plant-seg-tools) run the seg2mesh script using:

python useful-scripts/seg2mesh.py --path 'PATHTOSEGMENTATIONSTACK'

Optional arguments guide

• --new-base: optional custom saving directory. If not given the ply will be saved in the same dir as the source.
• --h5-dataset: h5 internal dataset name. Default: segmentation.
• --labels: List of labels to process. By default, the script will process all labels.
• --step-size: Step size for the marching cube algorithm, larger steps yield a coarser but faster result. Default 2.
• --crop: Crop the dataset, takes as input a bounding box. eg --crop 10, 0, 0 15, -1, -1.
• --voxel-size: Voxel size [Z, Y, X] of the segmentation stack. By default, voxel size is read from the source file, if this is not possible voxel-size is set to [1, 1, 1].
• --min-size: Minimum cell size. Default 50.
• --max-size: Maximum cell size. Default inf.
• --relabel: If this argument is passed the pipeline will relabel the segmentation. This will ensure the contiguity of each segment but will change the labels.
• --check-cc: If this argument is passed the pipeline will check if each label is has a single connected component (cc). If multiple cc are present only the largest will be processed.
• --ignore-labels: List of labels to ignore. By default, only background (label 0) is ignored.
• --reduction: If reduction > 0 a decimation filter is applied.MaxValue: 1.0 (100%reduction).
• --smoothing: To apply a Laplacian smoothing filter.
• --use-ray: If you use ray flag is used the multiprocessing flag is managed by ray.
• --multiprocessing: Define the number of cores to use for parallel processing. Default value (-1) will try to parallelize over all available processors.

Proofreading tool

Basic usage

From the project root (plant-seg-tools) run the proofreading tool using:

• if the stack is coming from PlantSeg

python useful-scripts/proofreading.py --path-raw 'PATHTORAWSTACK' --path-seg 'PATHTOSEGMENTATIONSTACK' --dataset-seg segmentation

or in short

python useful-scripts/proofreading.py --r 'PATHTORAWSTACK' -s 'PATHTOSEGMENTATIONSTACK' -ds segmentation

• if you want to continue working on a stack exported with the proofreading tool (or if segmentation and raw images are together in the same h5 file):

python useful-scripts/proofreading.py -r 'PATHTORAWSTACK (convetional name *_proofreading.h5')'

add to bashrc

alias  proofreading="[user-dir-location]/miniconda3/envs/plant-seg-proofreading/bin/python [plant-seg-tools-location]/plant-seg-tools/useful-scripts/proofreading.py"

Keybinding Guide:

• s: Save stack
• n: Merge or split from seeds
• ctrl+n: Undo merge or split from seeds
• c: Clean seeds
• o: Mark/un-mark correct segmentation
• b: show/un-show correct segmentation layer
• j: Update boundaries from segmentation
• k: Update segmentation from boundaries

Navigation

• ctrl + arrows: to move the field of view
• alt + down/up arrows: to increase or decrease the field of view

Optional arguments guide

• -dr or --dataset-raw: name of the dataset containing the raw boundary image. Only used if raw boundary image is in h5 format. default raw.
• -ds or --dataset-seg: name of the dataset containing the cell segmentation. Only used if segmentation is in h5 format. default label.
• -xy or --xy-size: field of view size along the xy-plane. Larger field of view might slow down the tool.
• -z or --z-size: field of view size along z. Only for 3D. Larger field of view might slow down the tool.

Automated Segmentation Proofread from seeds

Basic usage

python useful-scripts/fix_over_under_from_nuclei.py --seg-path 'PATHTOSEGMENTATIONSTACK' --nuclei-seg-path 'PATHTONUCLEISEGMENTATIONSTACK' 

Optional arguments guide

• --t-merge: Overlap merging threshold, between 0-1.
• --t-split: Overlap split threshold, between 0-1.
• --quantiles: Nuclei size below and above the defined quantiles will be ignored.
• --scaling: Scaling factor for the segmentation.
• --export-h5: In order to export the segmentation as h5.
• --boundaries-path: path to boundaries predictions file.

Evaluation

Basic usage

python useful-scripts/evaluation_segmentation.py -s PATHTOSEG -g PATHTOGT 

Optional arguments guide

• -ds or --dataset-seg: if h5 contains dataset name to segmentation
• • -dg or --dataset-gt: if h5 contains dataset name to ground-truth