cp-bg-bench-anon/jump-sample
cp-bg-bench preview — jump Compact preview of the jump dataset from the cp-bg-bench benchmark. Stratified subset of the full release; designed so that the held-out-batch perturbation-recall and cp_measure-prediction evals can be reproduced end-to-end against this small slice alone. Cells 913 Wells 69 Perturbations 33 Held-out batch source_4 Views crops, crops_density, seg, seg_density What's in this repo crops/ # HF dataset… See the full description on the dataset page: https://huggingface.co/datasets/cp-bg-bench-anon/jump-sample.
cp-bg-bench preview — jump
Compact preview of the jump dataset from the cp-bg-bench benchmark. Stratified subset of the full release; designed so that the held-out-batch perturbation-recall and cp_measure-prediction evals can be reproduced end-to-end against this small slice alone.
What's in this repo
crops/ # HF dataset, 224×224×C uint8 cell crops + masks
crops_density/ # crops + 4 corner density patches
seg/ # mask-applied cell crops
seg_density/ # mask + density patches
metadata/ # perturbations parquet + quality filter report
build_info.json # full provenance (seed, source pipeline commit, selection stats)Schema (per cell row)
row_key, source, plate, well, tile, id_local # identity
nuc_area, cyto_area, nuc_cyto_ratio, n_cells_in_fov, n_cells_scaled # per-cell QC
mask: large_binary # (2, 224, 224) uint8 -> NucMask, CellMask
cell: large_binary # (C, 224, 224) uint8 fluorescence channels
Metadata_JCP2022, Metadata_InChIKey, Metadata_PlateType # source metadata
perturbation, batch, treatment, Metadata_Perturbation # benchmark axesSelection recipe
- All control wells, capped to a small budget.
- Treated wells whose perturbation appears in both the held-out batch and at least one non-held-out batch (so cross-batch retrieval is reproducible). Per chosen perturbation: one held-out well + one non-held-out well.
- Per-well cell cap to keep total budget near 1,000 cells.
Seed = 42. See build_info.json for exact stats.
Quick start
from datasets import load_dataset
ds = load_dataset("cp-bg-bench-anon/jump-sample", name="crops", split="train")
print(ds)
print(ds[0]["row_key"], ds[0]["perturbation"])Full dataset
The corresponding full-size release is hosted separately.
License
CC0 1.0. Anonymous NeurIPS 2026 Datasets and Benchmarks submission; citation on acceptance.
