add platformdirs + fix client imports

pyproject.toml

@@ -42,6 +42,7 @@ dependencies = [
     "opencv-python-headless>=4.0.0",
     "pandas",
     "pillow",
+    "platformdirs",
     "scikit-image>=0.20.0",
     "shapely",
     # https://github.com/Bayer-Group/tiffslide/issues/72#issuecomment-1631015274

wsinfer_mil/cli.py

@@ -16,14 +16,15 @@
 import click
 from PIL import Image
 
-from wsinfer_mil.hfclient import load_torchscript_model_from_hf
+from wsinfer_mil.client.hfmodel import load_torchscript_model_from_hf
+from wsinfer_mil.client.localmodel import load_torchscript_model_from_filesystem
 from wsinfer_mil.inference import infer_one_slide
-from wsinfer_mil.localclient import load_torchscript_model_from_filesystem
 
 logger = logging.getLogger(__name__)
 
 
 def _load_tissue_mask(path: str | Path) -> Image.Image:
+    logger.info(f"Loading tissue mask: {path}")
     with Image.open(path) as tissue_mask:
         tissue_mask.load()
     if tissue_mask.mode != "1":
@@ -36,7 +37,7 @@ def _load_tissue_mask(path: str | Path) -> Image.Image:
 
 @click.group()
 def cli() -> None:
-    pass
+    """Run specimen-level inference using pre-trained models."""
 
 
 @cli.command()
@@ -48,15 +49,15 @@ def cli() -> None:
     "--wsi-path",
     required=True,
     help="Path to the whole slide image",
-    type=click.Path(exists=True, path_type=Path),  # type:ignore
+    type=click.Path(exists=True, path_type=Path),
 )
 @click.option(
     "--hf-repo-revision", help="Revision of the HuggingFace Hub repo", default=None
 )
 @click.option(
     "--tissue-mask-path",
     help="Path to the tissue mask for this image",
-    type=click.Path(exists=True, path_type=Path),  # type:ignore
+    type=click.Path(exists=True, path_type=Path),
     default=None,
 )
 @click.option(
@@ -97,12 +98,12 @@ def run(
     "-i",
     "--wsi-path",
     help="Path to the whole slide image",
-    type=click.Path(exists=True, path_type=Path),  # type:ignore
+    type=click.Path(exists=True, path_type=Path),
 )
 @click.option(
     "--tissue-mask-path",
     help="Path to the tissue mask for this image",
-    type=click.Path(exists=True, path_type=Path),  # type:ignore
+    type=click.Path(exists=True, path_type=Path),
     default=None,
 )
 @click.option(

wsinfer_mil/defaults.py

@@ -1,7 +1,9 @@
 from pathlib import Path
 
+from platformdirs import user_cache_dir
+
 # Where we keep all files related to WSInfer MIL.
-WSINFER_MIL_DIR = Path.home() / ".wsinfer-mil"
+WSINFER_MIL_DIR = Path(user_cache_dir(appname="wsinfer-mil"))
 
 # Cache for tissue masks, patch coordinates, and feature embeddings.
 WSINFER_MIL_CACHE_DIR = WSINFER_MIL_DIR / "cache"

wsinfer_mil/inference.py

@@ -22,21 +22,14 @@
 from torch.utils.data import DataLoader
 
 from wsinfer_mil.cache import Cache
+from wsinfer_mil.client.localmodel import Model
 from wsinfer_mil.data import WSIPatches
 from wsinfer_mil.extractors import get_extractor_by_name
-from wsinfer_mil.localclient import Model
 from wsinfer_mil.patchlib.patch import patch_tissue
 from wsinfer_mil.patchlib.segment import segment_tissue
 from wsinfer_mil.quickhash import quickhash
 
-# Configure logging
-logger = logging.getLogger()
-logger.setLevel(logging.DEBUG)
-stream_handler = logging.StreamHandler()
-stream_handler.setLevel(logging.DEBUG)
-formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
-stream_handler.setFormatter(formatter)
-logger.addHandler(stream_handler)
+logger = logging.getLogger(__name__)
 
 
 @dataclasses.dataclass