conradry

"""Minimal ``AsyncZarrDataset`` pattern: async zarr crop reads + kornia collate.

Shows a :class:`torch.utils.data.Dataset` that fans out bounding-box crop reads
via ``zarr.AsyncArray.getitem`` + ``asyncio.gather``, decoded by the ``zarrs``
Rust codec pipeline. A kornia ``AugmentationSequential`` is wired as the
DataLoader ``collate_fn`` so stacking, device upload, and augmentation happen
in one batched call.

The zarr handle is opened lazily in ``_ensure_initialized`` rather than
``__init__`` so the dataset stays picklable across spawn-based workers (the

conradry

import zarr
import argparse
import numpy as np
from empanada.inference.tracker import InstanceTracker
from empanada.inference import filters
from empanada.inference.patterns import fill_volume
from empanada.consensus import merge_objects_from_trackers

if __name__ == '__main__':
    parser = argparse.ArgumentParser()

conradry

import os
import zarr
import argparse
import numpy as np
from empanada.inference.tracker import InstanceTracker
from empanada.inference.rle import pan_seg_to_rle_seg, rle_seg_to_pan_seg
from tqdm import tqdm

if __name__ == '__main__':
    parser = argparse.ArgumentParser()

conradry

import os
import numpy as np
from fibsem_tools import io
from skimage.io import imsave
from scipy.ndimage import zoom

datasets = [
	'jrc_hela-2',
	'jrc_hela-3',
	'jrc_jurkat-1',