Repackage: per-split parquets + YAML configs (name=real/companion/per-tissue)
Browse files- README.md +109 -6
- companion-lung-test.parquet +3 -0
- companion-lung-train.parquet +3 -0
- companion-lung-val.parquet +3 -0
- companion-prostate-test.parquet +3 -0
- companion-prostate-train.parquet +3 -0
- companion-prostate-val.parquet +3 -0
- companion-skin-test.parquet +3 -0
- companion-skin-train.parquet +3 -0
- companion-skin-val.parquet +3 -0
- real-lung-test.parquet +3 -0
- real-lung-train.parquet +3 -0
- real-lung-val.parquet +3 -0
- real-prostate-test.parquet +3 -0
- real-prostate-train.parquet +3 -0
- real-prostate-val.parquet +3 -0
- real-skin-test.parquet +3 -0
- real-skin-train.parquet +3 -0
- real-skin-val.parquet +3 -0
README.md
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- benchmark
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size_categories:
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- 100K<n<1M
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---
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# SenoMorph
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| Companion (skin) | 16,844 | 168,440 (×10) |
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| **Companion total** | **87,391** | **873,910** |
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-
Each instance carries five attributes
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`senescence_score`, `nuclear_area` (mask
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and `dapi_intensity` (mean intensity
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`64×64` grayscale uint8 DAPI crop.
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## Splits
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## Loading
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```python
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from datasets import load_dataset
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-
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-
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```
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## License
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- benchmark
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size_categories:
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- 100K<n<1M
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configs:
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- config_name: real
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data_files:
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- split: train
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path: real-*-train.parquet
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- split: validation
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path: real-*-val.parquet
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- split: test
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path: real-*-test.parquet
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- config_name: companion
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data_files:
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- split: train
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path: companion-*-train.parquet
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- split: validation
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path: companion-*-val.parquet
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- split: test
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path: companion-*-test.parquet
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- config_name: real_lung
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data_files:
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- split: train
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path: real-lung-train.parquet
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- split: validation
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path: real-lung-val.parquet
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- split: test
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path: real-lung-test.parquet
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- config_name: real_prostate
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data_files:
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- split: train
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path: real-prostate-train.parquet
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- split: validation
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path: real-prostate-val.parquet
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- split: test
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path: real-prostate-test.parquet
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- config_name: real_skin
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data_files:
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- split: train
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path: real-skin-train.parquet
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- split: validation
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path: real-skin-val.parquet
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- split: test
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path: real-skin-test.parquet
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- config_name: companion_lung
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data_files:
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- split: train
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path: companion-lung-train.parquet
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- split: validation
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path: companion-lung-val.parquet
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- split: test
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path: companion-lung-test.parquet
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- config_name: companion_prostate
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data_files:
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- split: train
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path: companion-prostate-train.parquet
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- split: validation
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path: companion-prostate-val.parquet
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- split: test
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path: companion-prostate-test.parquet
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- config_name: companion_skin
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data_files:
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- split: train
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path: companion-skin-train.parquet
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- split: validation
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path: companion-skin-val.parquet
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- split: test
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path: companion-skin-test.parquet
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---
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# SenoMorph
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| Companion (skin) | 16,844 | 168,440 (×10) |
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| **Companion total** | **87,391** | **873,910** |
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Each instance carries five attributes (paper §2 attribute card):
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`tissue`, `cell_type_name`, `senescence_score`, `nuclear_area` (mask
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pixel count, threshold > 10), and `dapi_intensity` (mean intensity
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within the mask). The image is a `64×64` grayscale uint8 DAPI crop.
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## Splits
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## Loading
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Available configs:
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| `name=` | Description |
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|---|---|
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| `real` | All three tissues, real DAPI cells |
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| `companion` | All three tissues, generated companion cells |
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| `real_lung` / `real_prostate` / `real_skin` | Real cells, single tissue |
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| `companion_lung` / `companion_prostate` / `companion_skin` | Companion cells, single tissue |
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Each config has `train`, `validation`, and `test` splits.
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```python
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from datasets import load_dataset
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# Full real benchmark, training split (3 tissues combined)
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real_train = load_dataset('anon-neuripsdb26/SenoMorph', name='real', split='train')
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# Real lung test split only
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lung_test = load_dataset('anon-neuripsdb26/SenoMorph', name='real_lung', split='test')
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# Companion data (873,910 generated cells), train split
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comp_train = load_dataset('anon-neuripsdb26/SenoMorph', name='companion', split='train')
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# Companion skin only, validation split
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skin_val_comp = load_dataset('anon-neuripsdb26/SenoMorph', name='companion_skin', split='validation')
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```
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## Schema
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```
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image PIL.Image (grayscale 64×64, PNG-encoded)
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tissue str ('lung' | 'prostate' | 'skin')
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cell_type_id int32 (raw CellTypist integer)
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cell_type_name str ('Epithelial cells' | 'T cells' | 'Fibroblasts' | ...)
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senescence_score float32 in [0, 1]
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real: DeepScence min-max norm within tissue
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companion: target conditioning score from linspace(0,1,10)
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nuclear_area int32 (mask pixel count, threshold > 10)
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dapi_intensity float32 (mean intensity within mask)
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split str ('train' | 'val' | 'test')
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cell_id int64
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real: row index in source set
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companion: source real cell id (10 companion rows share a cell_id)
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```
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## License
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companion-lung-test.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:e3ddff071cd2cfc660d70042fee20b76f72e7a8b7f6250f27124ec6fe0708598
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companion-lung-train.parquet
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companion-lung-val.parquet
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companion-prostate-test.parquet
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companion-prostate-train.parquet
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companion-prostate-val.parquet
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companion-skin-test.parquet
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companion-skin-train.parquet
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companion-skin-val.parquet
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size 8001840
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real-lung-test.parquet
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real-lung-train.parquet
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real-lung-val.parquet
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size 2653100
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real-prostate-test.parquet
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real-prostate-train.parquet
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real-prostate-val.parquet
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real-skin-test.parquet
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real-skin-train.parquet
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real-skin-val.parquet
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