:py:mod:`wsinfer.modellib.run_inference`
========================================

.. py:module:: wsinfer.modellib.run_inference

.. autoapi-nested-parse::

   Run inference.

   From the original paper (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369575/):
   > In the prediction (test) phase, no data augmentation was applied except for the
   > normalization of the color channels.



Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   wsinfer.modellib.run_inference.run_inference



.. py:function:: run_inference(wsi_dir: str | pathlib.Path, results_dir: str | pathlib.Path, model_info: wsinfer_zoo.client.HFModelTorchScript | wsinfer.modellib.models.LocalModelTorchScript, batch_size: int = 32, num_workers: int = 0, speedup: bool = False) -> tuple[list[str], list[str]]

   Run model inference on a directory of whole slide images and save results to CSV.

   This assumes the patching has already been done and the results are stored in
   `results_dir`. An error will be raised otherwise.

   Output CSV files are written to `{results_dir}/model-outputs/`.

   :param wsi_dir: Directory containing whole slide images. This directory can *only* contain
                   whole slide images. Otherwise, an error will be raised during model inference.
   :type wsi_dir: str or Path
   :param results_dir: Directory containing results of patching.
   :type results_dir: str or Path
   :param model_info: Instance of Weights including the model object and information about how to
                      apply the model to new data.
   :param batch_size: The batch size during the forward pass (default is 32).
   :type batch_size: int
   :param num_workers: Number of workers for data loading (default is 0, meaning use a single thread).
   :type num_workers: int
   :param speedup: If True, JIT-compile the model. This has a startup cost but model inference
                   should be faster (default False).
   :type speedup: bool

   :returns: * *A tuple of two lists of strings. The first list contains the slide IDs for which*
             * *patching failed, and the second list contains the slide IDs for which model*
             * *inference failed.*