MUPAD
Collection
Multimodal Pathology Diffusion Model • 5 items • Updated
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
slide: string
organ: string
subject: string
oncotree: string
is_cancer: bool
pixel_size_um: double
pixel_size_source: string
median_cell_diam_um: double
tile_um: double
he_px: int64
tile_px: double
n_tiles: int64
n_cells: int64
genes: list<item: string>
child 0, item: string
source: string
registration_qc: struct<heldout_median_um: double, heldout_rmse_um: double, n_landmarks: int64, nucleus_enrichment_0u (... 70 chars omitted)
child 0, heldout_median_um: double
child 1, heldout_rmse_um: double
child 2, n_landmarks: int64
child 3, nucleus_enrichment_0um: double
child 4, nucleus_enrichment_20um: double
child 5, cell_level_verified: bool
spot_diameter: double
pixel_size_um_embedded: double
spots_under_tissue: int64
fullres_px_width: int64
pixel_size: double
region_name: string
inter_spot_dist: double
panel_name: string
cells_under_tissue: int64
fullres_px_height: int64
instrument_type: string
pixel_size_um_estimated: double
adata_nb_col: int64
to
{'pixel_size_um_embedded': Value('float64'), 'pixel_size': Value('float64'), 'region_name': Value('string'), 'panel_name': Value('string'), 'instrument_type': Value('string'), 'source': Value('string'), 'pixel_size_um_estimated': Value('float64'), 'spot_diameter': Value('float64'), 'inter_spot_dist': Value('float64'), 'spots_under_tissue': Value('int64'), 'cells_under_tissue': Value('int64'), 'adata_nb_col': Value('int64'), 'fullres_px_width': Value('int64'), 'fullres_px_height': Value('int64'), 'registration_qc': {'heldout_median_um': Value('float64'), 'heldout_rmse_um': Value('float64'), 'n_landmarks': Value('int64'), 'nucleus_enrichment_0um': Value('float64'), 'nucleus_enrichment_20um': Value('float64'), 'cell_level_verified': Value('bool')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
slide: string
organ: string
subject: string
oncotree: string
is_cancer: bool
pixel_size_um: double
pixel_size_source: string
median_cell_diam_um: double
tile_um: double
he_px: int64
tile_px: double
n_tiles: int64
n_cells: int64
genes: list<item: string>
child 0, item: string
source: string
registration_qc: struct<heldout_median_um: double, heldout_rmse_um: double, n_landmarks: int64, nucleus_enrichment_0u (... 70 chars omitted)
child 0, heldout_median_um: double
child 1, heldout_rmse_um: double
child 2, n_landmarks: int64
child 3, nucleus_enrichment_0um: double
child 4, nucleus_enrichment_20um: double
child 5, cell_level_verified: bool
spot_diameter: double
pixel_size_um_embedded: double
spots_under_tissue: int64
fullres_px_width: int64
pixel_size: double
region_name: string
inter_spot_dist: double
panel_name: string
cells_under_tissue: int64
fullres_px_height: int64
instrument_type: string
pixel_size_um_estimated: double
adata_nb_col: int64
to
{'pixel_size_um_embedded': Value('float64'), 'pixel_size': Value('float64'), 'region_name': Value('string'), 'panel_name': Value('string'), 'instrument_type': Value('string'), 'source': Value('string'), 'pixel_size_um_estimated': Value('float64'), 'spot_diameter': Value('float64'), 'inter_spot_dist': Value('float64'), 'spots_under_tissue': Value('int64'), 'cells_under_tissue': Value('int64'), 'adata_nb_col': Value('int64'), 'fullres_px_width': Value('int64'), 'fullres_px_height': Value('int64'), 'registration_qc': {'heldout_median_um': Value('float64'), 'heldout_rmse_um': Value('float64'), 'n_landmarks': Value('int64'), 'nucleus_enrichment_0um': Value('float64'), 'nucleus_enrichment_20um': Value('float64'), 'cell_level_verified': Value('bool')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MuPaD examples
Example data for MuPaD (paper code) and the MuPaD SDK (whole-slide inference).
| folder | contents | size | licence |
|---|---|---|---|
he2mif/ |
ORION-CRC tiles for 5-HE2mIF: 840 H&E / 17-channel mIF / nuclei tiles in the Zenodo 15340874 layout, as one tar |
0.4 GB | MIT |
he2st/ |
two HEST-1k Xenium breast slides for 6-HE2ST (NCBI917 train, NCBI920 val): raw HEST files, the 100 µm tile cache and per-cell MUSK features |
12.4 GB | CC BY-NC-SA 4.0 |
sdk/ |
the two held-out H&E whole-slide images the SDK's end-to-end checks run on: ORION-CRC CRC11 (0.325 µm/px) and HEST-1k NCBI920 (0.087 µm/px); H&E only, see sdk/README.md |
6.9 GB | original terms |
huggingface-cli download xiangjx/MuPaD-examples --repo-type dataset --include "he2mif/*" --local-dir examples
tar xf examples/he2mif/ORIONCRC_dataset_tile_20x.tar -C examples/he2mif # tiles ship as one tar
huggingface-cli download xiangjx/MuPaD-examples --repo-type dataset --include "he2st/*" --local-dir examples
he2mif. Tiles with tissue were sampled uniformly per slide: 600 train, 120 val, 120 test, plus the two demo tiles of 5-HE2mIF/demo.ipynb (a best case, not typical). Point the code at it with ORION_DATA_ROOT=$PWD/examples/he2mif/ORIONCRC_dataset_tile_20x.
he2st. cache/<slide>/ is the tile cache, features/musk/<slide>/emb_cell.npy the per-cell MUSK features, HEST1k/ the raw inputs they were built from (wsis/ st/ xenium_seg/ cells/ metadata/). Rows of expr.npy, emb_cell.npy and every prediction are the same cells in the same order. Set HEST_ROOT=$PWD/examples/he2st/HEST1k HE2ST_CACHE=$PWD/examples/he2st/cache HE2ST_MUSK_FEATURES=$PWD/examples/he2st/features/musk; splits_example.json makes a one-slide smoke run.
sdk. python scripts/e2e_mif_orion.py and python scripts/e2e_expression_ncbi920.py in the SDK download these slides themselves; the ground truth (Orion mIF, Xenium counts) comes from the original ORION-CRC and HEST-1k releases.
Sources: ORION-CRC tiles from the MIPHEI-ViT release (Balezo et al., 2025; MIT); HEST-1k (Jaume et al., NeurIPS 2024; CC BY-NC-SA 4.0, non-commercial, attribution, share-alike).
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