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Running on Zero
Running on Zero
RootScope v4: manuscript model (LightGBM per round, 3 seeds, layer + soft-neighbor context, radial prior)
47c4bf8 verified | """ | |
| Rootscope: cell-type prediction for confocal root-tip cross-section images. | |
| Give it a TIFF, it segments the cells (Cellpose-SAM), extracts shape / size / | |
| intensity / layer features plus fine-tuned DINOv2 embeddings, and predicts the | |
| cell type of every cell with an iterative ensemble (RandomForest / XGBoost / | |
| LightGBM). | |
| Typical use (command line): | |
| rootscope --tif my_image.tif --out results/ | |
| Typical use (Python): | |
| from rootscope import predict_tif | |
| df = predict_tif("my_image.tif", out_dir="results/", gpu=True) | |
| """ | |
| __version__ = "4.0.0" | |
| from .api import predict_tif, predict_folder # noqa: E402,F401 | |
| __all__ = ["predict_tif", "predict_folder", "__version__"] | |