Fix Classify train from arbitrary CWD (#3692)

ultralytics/yolo/data/utils.py

@@ -268,28 +268,33 @@ def check_det_dataset(dataset, autodownload=True):
 
 def check_cls_dataset(dataset: str, split=''):
     """
-    Check a classification dataset such as Imagenet.
+    Checks a classification dataset such as Imagenet.
 
-    This function takes a `dataset` name as input and returns a dictionary containing information about the dataset.
-    If the dataset is not found, it attempts to download the dataset from the internet and save it locally.
+    This function accepts a `dataset` name and attempts to retrieve the corresponding dataset information.
+    If the dataset is not found locally, it attempts to download the dataset from the internet and save it locally.
 
     Args:
-        dataset (str): Name of the dataset.
-        split (str, optional): Dataset split, either 'val', 'test', or ''. Defaults to ''.
+        dataset (str): The name of the dataset.
+        split (str, optional): The split of the dataset. Either 'val', 'test', or ''. Defaults to ''.
 
     Returns:
-        data (dict): A dictionary containing the following keys and values:
-            'train': Path object for the directory containing the training set of the dataset
-            'val': Path object for the directory containing the validation set of the dataset
-            'test': Path object for the directory containing the test set of the dataset
-            'nc': Number of classes in the dataset
-            'names': List of class names in the dataset
+        dict: A dictionary containing the following keys:
+            - 'train' (Path): The directory path containing the training set of the dataset.
+            - 'val' (Path): The directory path containing the validation set of the dataset.
+            - 'test' (Path): The directory path containing the test set of the dataset.
+            - 'nc' (int): The number of classes in the dataset.
+            - 'names' (dict): A dictionary of class names in the dataset.
+
+    Raises:
+        FileNotFoundError: If the specified dataset is not found and cannot be downloaded.
     """
-    data_dir = (DATASETS_DIR / dataset).resolve()
+
+    dataset = Path(dataset)
+    data_dir = (dataset if dataset.is_dir() else (DATASETS_DIR / dataset)).resolve()
     if not data_dir.is_dir():
         LOGGER.info(f'\nDataset not found ⚠️, missing path {data_dir}, attempting download...')
         t = time.time()
-        if dataset == 'imagenet':
+        if str(dataset) == 'imagenet':
             subprocess.run(f"bash {ROOT / 'yolo/data/scripts/get_imagenet.sh'}", shell=True, check=True)
         else:
             url = f'https://github.com/ultralytics/yolov5/releases/download/v1.0/{dataset}.zip'
@@ -312,12 +317,12 @@ def check_cls_dataset(dataset: str, split=''):
 
 class HUBDatasetStats():
     """
-    Class for generating HUB dataset JSON and `-hub` dataset directory
+    A class for generating HUB dataset JSON and `-hub` dataset directory.
 
-    Arguments
-        path:           Path to data.yaml or data.zip (with data.yaml inside data.zip)
-        task:           Dataset task. Options are 'detect', 'segment', 'pose', 'classify'.
-        autodownload:   Attempt to download dataset if not found locally
+    Args:
+        path (str): Path to data.yaml or data.zip (with data.yaml inside data.zip). Default is 'coco128.yaml'.
+        task (str): Dataset task. Options are 'detect', 'segment', 'pose', 'classify'. Default is 'detect'.
+        autodownload (bool): Attempt to download dataset if not found locally. Default is False.
 
     Usage
         from ultralytics.yolo.data.utils import HUBDatasetStats