Datasets:
license: cc-by-4.0
task_categories:
- image-classification
language:
- en
tags:
- microscopy
- biomedical-imaging
- image-classification
pretty_name: Lurcher 10x Microscopy
configs:
- config_name: viewer
data_files:
- split: folds
path: viewer/lurcher_folds.parquet
Lurcher 10x Microscopy Dataset
This dataset contains 10x microscopy images for the Lurcher classification experiments used by Active Prompt Tuning (APT). Images are organized once by class and case id, while the experiment folds are provided as JSONL manifests plus fold-specific seed prompts.
Image layout
images/microscopy_lurcher/
lurcher/<case_id>/<image_name>.jpg
wild/<case_id>/<image_name>.jpg
Fold manifests
Predefined folds are included under:
folds/microscopy_lurcher/fold-<fold>/
train.jsonl
val.jsonl
test.jsonl
seed.json
Each row has a path relative to the dataset repository root and a normalized class label:
{"image_path":"images/microscopy_lurcher/lurcher/5917/example.jpg","class":"lurcher"}
train.jsonl is the active-learning candidate pool. val.jsonl is the validation split used by the APT code. test.jsonl is the held-out evaluation split. seed.json contains the initial seed prompt examples used before active selection starts.
Dataset Viewer
The Hub dataset viewer uses:
viewer/lurcher_folds.parquet
This table mirrors the released fold manifests and includes both image_path and an image column so the viewer can render thumbnails directly.
Metadata
metadata/images.csv: one row per image with class and case id.metadata/folds.csv: per-fold split counts and manifest file paths.
Prompt bank
The Lurcher prompt bank used by the APT oracle is included at:
prompt_banks/microscopy_lurcher.json
Download it into the APT code repository with:
hf download USF-CS-Microscopy-Image-Analysis/Lurcher_10x \
prompt_banks/microscopy_lurcher.json \
--repo-type dataset \
--local-dir .
The APT repository also includes setup_lurcher_data.py, which downloads the images, fold manifests, seed prompts, metadata, and prompt bank into the expected local layout automatically.
Intended use
Use these fixed folds when comparing against the APT paper or repository results. Do not regenerate splits for direct comparison to reported fold-level numbers.