Semi-automatic segmentation workflow for Volume SEM datasets
Paintera:
conda env create -f paintera-env.yml
Main environment:
conda env create -f paintera-mc-workflow-env.yml
Paintera
TODO
Main environment:
conda create -n paintera-mc-workflow-env -c cpape -c conda-forge elf python=3.7
conda activate paintera-mc-workflow-env
conda install -c conda-forge napari
conda install -c cpape z5py
from paintera_multicut_workflow import pm_workflow
pm_workflow(
results_folder='path/to/results/folder/',
raw_filepath='path/to/raw_data.h5,
mem_pred_filepath='path/to/mem_pred.h5',
supervoxel_filepath='path/to/supervoxels.h5',
mem_pred_channel=2, # Required if mem_pred.ndim == 4 to select channel
auto_crop_center=True, # Crops to the center if raw, mem or sv shapes are > annotation_shape
annotation_shape=(256, 256, 256),
paintera_env_name='paintera_env_new', # Name of the paintera environment
activation_command='source /home/hennies/miniconda3/bin/activate',
export_binary=True,
conncomp_on_paintera_export=True,
verbose=True
)
Download pm_workflow.tar.gz
Unpack with
mkdir pm_workflow
tar -xzf pm_workflow.tar.gz -C pm_workflow
Run the pipeline
cd pm_workflow
./run_workflow.sh input_folder result_folder [arguments]
Use help for description of arguments
./run_workflow.sh -h
Download pm_workflow_win.zip
Unpack to the the disired location (workflow directory)
Run the pipeline using the command prompt:
Open command prompt and navigate to the workflow directory, e.g.
cd path\to\pm_workflow_win
Run the pipeline with
run_workflow.bat input_folder result_folder [arguments]
Use help for description of arguments
run_workflow.bat -h