# CellClass -- ML Cell Classifier

**cellclass** is the machine-learning training pipeline for the OmeroScreen ecosystem. It trains lightweight convolutional neural networks to classify single-cell crops generated by the [Training Widget](../../napari/user-guide/training_widget.md) and deploys the resulting [TorchScript](https://pytorch.org/docs/stable/jit.html) models back into the [omero-screen pipeline](../../) for automated inference.

The package follows a four-step workflow:

1.  **Create dataset** -- normalise and package `.npy` crop files into a single `.npz` archive.
2.  **Write a training batch file** -- one run per line with model and hyperparameter flags.
3.  **Train** -- run all jobs locally or on a SLURM cluster; results log to Weights & Biases.
4.  **Extract model** -- export the best checkpoint to a TorchScript `.pt` + `.json` sidecar for inference.

> **Note: Note**
>
> Every command is documented, option by option, in the generated [CLI reference](../reference/cli/index.md). The pages in this guide explain *why* and *when* to use them.