This script takes paths to raw/label n5 datasets as an input, and outputs .zarr container with the correct cellmap schema:
n5 / zarr container
- recon_{number}
- em
- fibsem-uint8
- fibsem-uint16
- labels
- inference (predictions and segmentations)
- groundtruth (training crops)
- mask
- em
Installation:
- cd PATH_TO_POETRY_PROJECT_DIRECTORY/
- poetry install
Example(for lsf cluster):
bsub -n 15 -J n5convert -o path_to_output_log_file 'poetry run python src/to_cellmap_zarr.py --num_workers=300 --cluster=lsf --src=path_to_raw_data_n5_group(array) --inf=path_to_inference --dest=path_to_the_output_zarr_container';