Added docstring, and load_metadata function.

src/facebias/__init__.py

@@ -1,5 +1,6 @@
 # -*- coding: utf-8 -*-
 
+import csv
 import logging
 from collections import OrderedDict
 from dataclasses import dataclass
@@ -11,7 +12,6 @@ import numpy as np
 
 logging.basicConfig(
     level=logging.DEBUG,  # Set the minimum logging level
-    # format="%(asctime)s - [%(levelname)s] - %(filename)s:%(lineno)s - %(message)s",
 )
 
 logger = logging.getLogger(__name__)
@@ -25,11 +25,50 @@ class FaceBox:
     y2: int
 
 
+def load_metadata(p: Path, key_id="image", key_proc_fn=None) -> dict[str, dict[str, str]]:
+    lines = []
+    with open(p, newline="") as csvfile:
+        dialect = csv.Sniffer().sniff(csvfile.read(1024))
+        csvfile.seek(0)
+        reader = csv.DictReader(csvfile, dialect=dialect)
+        for row in reader:
+            lines.append(row)
+
+    metadata = dict()
+    for l in lines:
+        new_key_id = key_proc_fn(l[key_id]) if key_proc_fn is not None else l[key_id]
+        metadata[new_key_id] = dict((k, v) for k, v in l.items() if k != key_id)
+
+    return metadata
+
+
 def load_dataset(
         root: Path,
         meta_path: Optional[Path] = None,
         imname_proc_fn: Optional[Callable]=None
-) -> tuple[dict[Path, np.ndarray], dict[str, dict[str, Any]]]:
+) -> tuple[dict[Path, np.ndarray], Optional[dict[str, dict[str, Any]]]]:
+    """
+    if `meta_path` is `None`, we won't attempt to read it.
+
+    Parameters
+    ----------
+    root: Path
+        Root path to the images. We assume that the images are positioned in a
+        flat directory under `root`.
+
+    meta_path: Optional[Path]
+        Path to the metadata file on the dataset. Default is `None`.
+
+    imname_proc_fn: Optional[Callable]
+        Function to apply to the image filenames when building the output
+        dictionary. Use it to uniformize it with the metadata file. Default
+        is `None`.
+
+    Returns
+    -------
+    data: dict[Path, np.ndarray]
+    metadata, Optional[dict[str, dict[str, Any]]]
+    """
     metadata = dict()
     paths = set([p for p in root.iterdir() if not p.is_dir()])
     if meta_path is not None and meta_path in paths:
@@ -43,16 +82,16 @@ def load_dataset(
         try:
             im = cv2.cvtColor(cv2.imread(p), cv2.COLOR_BGR2RGB)
         except cv2.error:
-            logger.info(f'File "{p}" is not an image.')
-            if meta_path is None:
-                logger.info(f'Trying to read "{p}" as metadata.')
-                if p.suffix == ".csv":
-                    metadata = load_metadata(p)
-                    logger.info("Metadata read successfully.")
-                else:
-                    logger.error(f'Failed to read "{p}" as metadata. Skipping.')
-            elif not metadata:
-                logger.critical("Logic error: Metadata should have been read already.")
+            logger.info(f'File "{p}" is not an image. Skipping.')
+            # if meta_path is None:
+            #     logger.info(f'Trying to read "{p}" as metadata.')
+            #     if p.suffix == ".csv":
+            #         metadata = load_metadata(p)
+            #         logger.info("Metadata read successfully.")
+            #     else:
+            #         logger.error(f'Failed to read "{p}" as metadata. Skipping.')
+            # elif not metadata:
+            #     logger.critical("Logic error: Metadata should have been read already.")
         else:
             proc_imname = imname_proc_fn(p.name) if imname_proc_fn is not None else p.name
             ims[proc_imname] = im