Squash history: zarr-only, current metadata

Co-authored-by: Donglai Wei <Donglai Wei@users.noreply.huggingface.co>
Co-authored-by: donglaiw <donglaiw@users.noreply.huggingface.co>

.gitattributes

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+# MitoVerse data repo (HuggingFace pytc/MitoVerse)
+# Zarr stores live under data/. Track the binary chunk files via LFS, but keep the small zarr
+# metadata (.zarray/.zattrs/.zgroup/.zmetadata) and JSON as readable text.
+data/** filter=lfs diff=lfs merge=lfs -text
+data/**/.zarray   -filter -diff -merge text
+data/**/.zattrs   -filter -diff -merge text
+data/**/.zgroup   -filter -diff -merge text
+data/**/.zmetadata -filter -diff -merge text
+
+# legacy single-file artifacts, if any are ever added
+*.h5  filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text

CLAUDE.md

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+# CLAUDE.md — MitoVerse **data** repo (HuggingFace `pytc/MitoVerse`)
+
+This directory is the **data** half of MitoVerse: zarr volumes + benchmark splits + the dataset card.
+It is a HuggingFace dataset repo. The **code** (ingestion, loader, PyTC adapter) lives separately at
+`/projects/weilab/weidf/lib/pytorch_connectomics/lib/mitoverse` (GitHub `PytorchConnectomics/mitoverse`).
+**Do not put Python/scripts here** — only data, splits, catalog, and docs.
+
+## What's here
+
+```
+data/<dataset>/<vol>.zarr/   original-chunk volumes: img (uint8) + mito (instance) + .zattrs metadata
+splits/*.json                benchmark definitions (overlays; whole-volume now, regions later)
+catalog.json                 generated index (shape, voxel, strata, instance count) — by ingest.py
+README.md                    HuggingFace dataset card
+plan.md                      benchmark design rationale (research)
+```
+
+## Rules
+
+- **Minimal + original chunk.** One zarr per source volume. No tiling, no physical train/val/test
+  split, no stored semantic/boundary (consumers derive `mito>0` themselves).
+- **Instance labels only** in `mito`; background = 0; `img` is uint8 ZYX.
+- **Splits are overlays**, not data copies. Add a benchmark by writing `splits/<name>.json`
+  (see `splits/README.md`), never by duplicating volumes.
+- **Add a volume** by running the code repo's ingester (writes here via `--out-root`):
+  `python <pytc>/lib/mitoverse/scripts/ingest.py --dataset <d> --volume <v> --im ... --mito ... --voxel x,y,z ...`
+- Labels are reused from their source datasets as-is — never re-annotate.
+
+## Publishing
+
+HuggingFace remote: `https://huggingface.co/datasets/pytc/MitoVerse`. Zarr chunks are LFS-tracked
+(`.gitattributes`); zarr metadata stays text. Push requires `huggingface-cli login` (human-run).
+
+## Reference
+
+- Code, format decision, architecture: https://github.com/PytorchConnectomics/mitoverse (`DESIGN.md`).

README.md

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+---
+license: other
+task_categories:
+  - image-segmentation
+tags:
+  - electron-microscopy
+  - connectomics
+  - mitochondria
+  - 3d-segmentation
+  - instance-segmentation
+pretty_name: MitoVerse
+size_categories:
+  - 10B<n<100B
+---
+
+# MitoVerse
+
+A generalist **3D-EM mitochondria segmentation** benchmark: many domains (modality, species, tissue,
+resolution) in one consistent format, with **instance** labels.
+
+**Code, loaders, ingestion, and PyTorchConnectomics usage:**
+👉 https://github.com/PytorchConnectomics/mitoverse
+
+Each volume is one zarr store `data/<dataset>/<volume>.zarr` with arrays `img` (uint8, ZYX) and
+`mito` (instance, 0=background); per-volume metadata (voxel size, modality, species, tissue) lives in
+its `.zattrs` and in `catalog.json`. Semantic masks are `mito > 0` — derive as needed.
+
+## 3D EM Datasets with Mitochondria Annotation
+
+`*` = instance labels we converted from binary segmentation. `†` = redistribution caveat.
+Shape is the average `(x,y,z)` per volume, `×N` = number of volumes.
+
+| Microscope | Dataset | Species | Region | Avg Shape (xyz) | Resolution (nm) | # Mitos |
+|---|---|---|---|---|---|---|
+| FIB-SEM | [OpenOrganelle](https://openorganelle.janelia.org/) (Xu'21), [CellMap](https://cellmapchallenge.janelia.org/) annot. | mixed | various cells/tissues | (213,204,203)×147 | 8×8×8 | 1580 |
+| FIB-SEM | └ + MitoEM2.0 chunks (Liu et al. '26) | mixed | jurkat/macro/kidney/liver/cardiac | (1024,1024,256)×10 | 8×8×8 | 2910 |
+| FIB-SEM | [Müller'21 (BetaSeg)](https://betaseg.github.io/)* | Mouse | Pancreas (β-cells) | (874,669,979)×7 | 16×16×16 | 1852 |
+| FIB-SEM | [Mekuč'20 (UroCell)](https://github.com/MancaZerovnikMekuc/UroCell) | Mouse | Urinary bladder | (256,256,256)×5 | 16×16×15 | 287 |
+| FIB-SEM | Kunduri'22 | Drosophila | Gonad (spermatocyte) | (1024,1024,341)×3 | 16×16×16 | 621 |
+| FIB-SEM | [Conrad'23 (MitoNet)](https://volume-em.github.io/empanada.html) | mixed | fly brain / C. elegans / HeLa / muscle / salivary | (546,446,466)×5 | 12–24 (iso) | 635 |
+| ssSEM | [Wei'20 (MitoEM)](https://mitoem.grand-challenge.org/) | Human | Temporal lobe (L2) | (4096,4096,500) | 8×8×30 | 10552 |
+| ssSEM | [Wei'20 (MitoEM)](https://mitoem.grand-challenge.org/) | Rat | V1 (L2/3) | (4096,4096,500) | 8×8×30 | 5446 |
+| ssSEM | [Casser'20 (Kasthuri++)](https://sites.google.com/view/connectomics/)* | Mouse | Somatosensory (L4/5) | (700,791,80)×2 | 12×12×30 | 265 |
+| FIB-SEM | └ Lucchi++ ([Lucchi'13](https://www.epfl.ch/labs/cvlab/data/data-em/))* | Mouse | Hippocampus | (512,768,82) | 10×10×10 | 70 |
+| ssSEM | [Xiao'18](https://www.frontiersin.org/articles/10.3389/fnana.2018.00092/full) | Mouse | Auditory cortex | (2156,2104,31) | 8×8×50 | 468 |
+| ssSEM | Han'24 | Mouse | Cerebellum (mossy fiber) | (1357,1411,331)×5 | 8×8×30 | 1144 |
+| ssTEM | [Turner'22 (MICrONS, Pinky)](https://www.sciencedirect.com/science/article/pii/S0092867422001349)† | Mouse | V1 (Pinky + MICrONS1) | (1203,1282,83)×16 | 8×8×40 | 1420 |
+| SBF-SEM | [Jiang'25](https://www.sciencedirect.com/science/article/pii/S2667237525000256) | Mouse | Brainstem | (1000,1000,100)×3 | 15×15×40 | 2057 |
+| SBF-SEM | [Guay'21](https://leapmanlab.github.io/dense-cell/)* | Human | Platelet | (667,736,65)×3 | 10×10×50 | 279 |
+| SBF-SEM | [Haberl'18 (CDeep3M)](https://doi.org/10.1038/s41592-018-0106-z)* | Mouse | Cerebellum (brain) | (256,256,15)×2 | 10×10×24 | 247 |
+
+**Total: 212 volumes, 29,833 mitochondria.** Volumes are organized by imaging source; benchmarks are
+split overlays in [`splits/`](splits/): `cellmap.json` (CellMap challenge over OpenOrganelle crops) and
+`mitoem2.0.json` (MitoEM2.0 generalization suite). The OpenOrganelle `*_test0/_test1` volumes are
+lab-annotated and belong to `mitoem2.0`.
+
+## MitoEM2.0 benchmark
+
+MitoEM2.0 (Liu et al., 2026) is a multi-domain generalization benchmark of 8 sub-datasets. Official
+nnU-Net release: **[Zenodo 10.5281/zenodo.20417683](https://zenodo.org/records/20417683)**. Within
+MitoVerse it is **not duplicated** — it is the split overlay [`splits/mitoem2.0.json`](splits/mitoem2.0.json)
+over the source volumes below (muller21, openorganelle, han24, wei20, jiang25, kunduri22). EFI/DCI are
+per-dataset difficulty metrics from the MitoEM2.0 paper; `†` redistribution caveat, `*` converted to instances.
+
+| Name | Organism | Tissue | Cell type | Modality | Avg Shape (xyz) | Voxels | Split (tr/val/te) | # Mito | EFI/DCI | Source |
+|---|---|---|---|---|---|---|---|---|---|---|
+| ME2-Beta   | Mouse      | Pancreas   | β-cell       | FIB-SEM | (874,669,979)   | 3961M | 3/1/3  | 1935 | 0.02/2.68 | Müller'21 † |
+| ME2-Jurkat | Human      | Cell line  | Jurkat       | FIB-SEM | (1024,1024,256) | 805M  | 1/1/1  | 372  | 0.00/1.62 | Xu'21 * |
+| ME2-Macro  | Human      | Cell line  | Macrophages  | FIB-SEM | (1024,1024,256) | 805M  | 1/1/1  | 497  | 0.01/1.38 | Xu'21 * |
+| ME2-Mossy  | Mouse      | Cerebellum | Mossy Fiber  | ssSEM   | (1024,1024,500) | 3333M | 3/1/3  | 1099 | 0.10/4.13 | Han'24 |
+| ME2-Pyra   | Human      | Cerebrum   | Pyramidal    | ssSEM   | (4096,4096,500) | 8388M | 3/1/11 | 45   | 0.96/0.53 | Wei'20 |
+| ME2-Podo   | Mouse      | Kidney     | Podocyte     | FIB-SEM | (1024,1024,256) | 805M  | 1/1/1  | 1333 | 0.00/2.43 | CellMap'24 † |
+| ME2-Sperm  | Drosophila | Gonad      | Spermatocyte | FIB-SEM | (1024,1024,341) | 1073M | 3/1/4  | 775  | 0.01/0.96 | Kunduri'22 † |
+| ME2-Stem   | Mouse      | Brainstem  | Mix          | SBF-SEM | (1024,1024,100) | 300M  | 1/1/1  | 2058 | 0.09/0.80 | Jiang'25 |
+
+## License
+
+Per-volume; see each volume's `source` in `catalog.json`. Some sources (MICrONS †, CellMap) carry
+attribution or redistribution caveats — check before reuse.
+
+## Acknowledgement
+
+- [Aswath et al. 2023. Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey](https://arxiv.org/abs/2206.07171)

TODO.md

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+# MitoVerse — Open Questions / TODO
+
+Unsolved items as of the current build (212 volumes, 13 datasets). Grouped by theme.
+
+## Data integrity
+
+- **kunduri22 gt not connected.** `train01`/`train02` are separate stores; an instance crossing that
+  z-cut gets a different id in each. Ingested count is 621 (218+172+231) vs the paper's **775** — likely
+  this split + double/under-count. Connect the gt across train01/train02 (and decide whether to then
+  merge into one 512z volume).
+- **ME2-Pyra # Mito = 45?** The MitoEM2.0 table lists ME2-Pyra at 45 mitochondria, but `wei20/mitoEM-H`
+  has 10,552. Confirm the ME2-Pyra figure (is it per held-out crop, or an error?).
+- **wei20 test withheld.** Only train+val (500z) ingested for MitoEM-H/R, to keep the grand-challenge
+  test hidden. Confirm this stays the policy for any public release.
+
+## Missing metadata
+
+- **turner22 voxel** = 8×8×40 (MICrONS default) — verify the Pinky-specific resolution; the 5
+  `microns1_vol*` crops may differ.
+- ~~conrad23 voxel/species~~ — DONE (filled per-volume from the MitoNet paper; FIB-SEM isotropic 12–24 nm).
+- **Per-volume license / redistribution rights** — especially unpublished OpenOrganelle crops, MICrONS
+  (†), and internal kunduri22. Clear before any HuggingFace push.
+
+## Not-yet-ingested data
+
+- **MICrONS1 full volume** (`mito/lichtman/microns1_*`): 16 tiles of (750,1024,1024). Decide: stitch the
+  4×4 grid into one volume and add to `turner22`, or skip. (Only the 5 small `microns1_vol*` crops are in.)
+- **Peng's other 3D sets**: `cerebellum` (4 quadrant vols, instance), `wilson19`, `zhu22` — voxel/metadata
+  TBD. `Boston3Mouse` is image-only (no labels) → skip unless labels appear.
+- **OME-Zarr refined labels**: only ME2-Sperm was taken from `MitoEM2.0_OMEZarr`. The other 7 ME2 OME-Zarr
+  sub-datasets may carry refined labels vs the MitoLE-sourced volumes — decide whether to re-ingest from
+  the OME-Zarr (needs the zarr-v3 path).
+
+## Candidate external datasets to acquire (mito · 3D)
+
+Sourced from the torch-em EM dataset tracker (full sheet cached at
+`<pytc>/lib/mitoverse/tmp/em_datasets.csv`). Filtered to mitochondria + volumetric + usable labels.
+
+### Ready — instance mito, 3D, not yet in MitoVerse
+- **VNC** (Gerhard'13) — ssTEM, Drosophila larval ventral nerve cord; instance mito. Small, easy add.
+  Loader: https://github.com/constantinpape/torch-em/blob/main/torch_em/data/datasets/electron_microscopy/vnc.py
+  (NB: different from our COSEM `jrc_fly-vnc-1`.)
+- **MBLiver** (Nat Commun 2024) — FIB-SEM, mouse liver; instance mito. ~2.1 TB native → take a 16 nm
+  ROI / downsample. https://doi.org/10.6019/EMPIAR-12017 · paper https://www.nature.com/articles/s41467-024-48272-7
+- **MICrONS minnie (cortical mm³)** — ssTEM, mouse cortex; instance mito (+ neurites). Complements our
+  Pinky (`turner22`). https://www.microns-explorer.org/cortical-mm3#voxel-segmentation · https://zenodo.org/records/5760218
+- **MitoNet_OpenOrganelle_Mouse_Kidney** — auto MitoNet instance mito, **not proofread** → low priority.
+  https://figshare.com/articles/dataset/MitoNet_automatic_instance_segmentation_of_mitochondria_in_the_OpenOrganelle_Mouse_Kidney_dataset/20749729/2
+
+### Needs binary→instance conversion (semantic mito source)
+- **ASEM** — FIB-SEM whole-cell; semantic mito + golgi/ER/nucleus → cc3d to instances.
+  https://doi.org/10.1083/jcb.202208005 · loader https://github.com/constantinpape/torch-em/blob/main/torch_em/data/datasets/electron_microscopy/asem.py
+- **DeepContact** — semantic mito/ER/lipid (figshare server was flaky).
+  https://figshare.com/articles/dataset/DeepContact_Training_Data/19898404/1
+- **Human Organoids** — FIB-SEM, semantic organelles incl. mito; EMPIAR-11380.
+  https://www.ebi.ac.uk/empiar/EMPIAR-11380/
+- **ProbTEM** — semantic mito but **2D TEM** → skip for the 3D benchmark.
+  https://yoonlab.unist.ac.kr/index.php/research/mitochondria-tem-dataset/
+
+### Extend what we already have
+- **CellMap** — more annotated `jrc_*` crops (being extended upstream).
+  https://doi.org/10.25378/janelia.c.7456966 · loader https://github.com/constantinpape/torch-em/blob/main/torch_em/data/datasets/electron_microscopy/cellmap.py
+- **OpenOrganelle** — additional `jrc_*` volumes with mito (e.g. mb-liver, more `mus-liver-zon`/`kidney`).
+  https://openorganelle.janelia.org/datasets
+
+### Already in MitoVerse (no download)
+Kasthuri & Lucchi (`casser20`) · MitoEM (`wei20`) · UroCell (`mekuc20`) · BetaSeg (`muller21`) ·
+DenseCell/Guay (`guay21`) · Haberl (`haberl18`) · Xiao'18 · Jiang'25 · CEM/MitoNet-3D-benchmark
+(`conrad23`) · OpenOrganelle/CellMap subset (`openorganelle`) · Pinky/MICrONS (`turner22`).
+
+## Benchmark splits
+
+- **cellmap.json**: all 147 crops currently marked `train`. Apply the official CellMap challenge
+  train/val/test split.
+- **mitoem.json**: not written yet — classic MitoEM (wei20) split (region-based).
+- **Within-volume regions (PyTC feature).** ME2-Pyra (wei20 crops) and classic MitoEM splits need PyTC to
+  support coordinate regions as train/val/test within one volume. Until then they reference whole volumes.
+- **Self-annotated OpenOrganelle volumes not in any split** (e.g. some cardiac/mus-liver `test` crops) have
+  ambiguous annotation provenance — decide where they belong.
+
+## Tooling / publishing
+
+- **zarr v3 env.** OME-Zarr ingestion currently uses a throwaway pip venv. Stand up a persistent conda env
+  (`conda create -n zarrv3 -c conda-forge "zarr>=3" ...`) for repeatable v3 reads.
+- **HuggingFace push (pending, human auth):** (a) MitoVerse data + splits + card; (b) deprecation banners
+  on `pytc/MitoEM` and `pytc/MitoEM2.0` (committed locally at `weidf/lib/hf_legacy_cards/`). Also fix the
+  malformed YAML frontmatter on the `pytc/MitoEM` card (line 1 sits above the opening `---`).
+
+## Definitions
+
+- **EFI / DCI** difficulty metrics in the MitoEM2.0 table are quoted but not defined here — add their
+  definitions (or a paper reference) so the numbers are interpretable.

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