Add dataset categories to data modules (#1105)

* Fix metadata path

* Add categories to data modules

src/anomalib/data/btech.py

@@ -40,6 +40,8 @@
     name="btech", url="https://avires.dimi.uniud.it/papers/btad/btad.zip", hash="c1fa4d56ac50dd50908ce04e81037a8e"
 )
 
+CATEGORIES = ("01", "02", "03")
+
 
 def make_btech_dataset(path: Path, split: str | Split | None = None) -> DataFrame:
     """Create BTech samples by parsing the BTech data file structure.
@@ -134,7 +136,7 @@ class BTechDataset(AnomalibDataset):
         >>> transform = get_transforms(image_size=256)
         >>> dataset = BTechDataset(
         ...     root='./datasets/BTech',
-        ...     category='leather',
+        ...     category='01',
         ...     transform=transform,
         ...     task="classification",
         ...     is_train=True,
@@ -215,13 +217,13 @@ class BTech(AnomalibDataModule):
         >>> from anomalib.data import BTech
         >>> datamodule = BTech(
         ...     root="./datasets/BTech",
-        ...     category="leather",
+        ...     category="01",
         ...     image_size=256,
         ...     train_batch_size=32,
-        ...     test_batch_size=32,
+        ...     eval_batch_size=32,
         ...     num_workers=8,
         ...     transform_config_train=None,
-        ...     transform_config_val=None,
+        ...     transform_config_eval=None,
         ... )
         >>> datamodule.setup()
 

src/anomalib/data/mvtec.py

@@ -48,7 +48,7 @@
 logger = logging.getLogger(__name__)
 
 
-IMG_EXTENSIONS = [".png", ".PNG"]
+IMG_EXTENSIONS = (".png", ".PNG")
 
 DOWNLOAD_INFO = DownloadInfo(
     name="mvtec",
@@ -57,6 +57,24 @@
     hash="eefca59f2cede9c3fc5b6befbfec275e",
 )
 
+CATEGORIES = (
+    "bottle",
+    "cable",
+    "capsule",
+    "carpet",
+    "grid",
+    "hazelnut",
+    "leather",
+    "metal_nut",
+    "pill",
+    "screw",
+    "tile",
+    "toothbrush",
+    "transistor",
+    "wood",
+    "zipper",
+)
+
 
 def make_mvtec_dataset(
     root: str | Path, split: str | Split | None = None, extensions: Sequence[str] | None = None

src/anomalib/data/mvtec_3d.py

@@ -54,6 +54,8 @@
     hash="d8bb2800fbf3ac88e798da6ae10dc819",
 )
 
+CATEGORIES = ("bagel", "cable_gland", "carrot", "cookie", "dowel", "foam", "peach", "potato", "rope", "tire")
+
 
 def make_mvtec_3d_dataset(
     root: str | Path, split: str | Split | None = None, extensions: Sequence[str] | None = None

src/anomalib/data/ucsd_ped.py

@@ -39,6 +39,8 @@
     hash="5006421b89885f45a6f93b041145f2eb",
 )
 
+CATEGORIES = ("UCSDped1", "UCSDped2")
+
 
 def make_ucsd_dataset(path: Path, split: str | Split | None = None) -> DataFrame:
     """Create UCSD Pedestrian dataset by parsing the file structure.
@@ -151,7 +153,7 @@ class UCSDpedDataset(AnomalibVideoDataset):
     Args:
         task (TaskType): Task type, 'classification', 'detection' or 'segmentation'
         root (Path | str): Path to the root of the dataset
-        category (str): Sub-category of the dataset, e.g. 'bottle'
+        category (str): Sub-category of the dataset, e.g. "UCSDped1" or "UCSDped2"
         transform (A.Compose): Albumentations Compose object describing the transforms that are applied to the inputs.
         split (str | Split | None): Split of the dataset, usually Split.TRAIN or Split.TEST
         clip_length_in_frames (int, optional): Number of video frames in each clip.
@@ -186,7 +188,7 @@ class UCSDped(AnomalibVideoDataModule):
 
     Args:
         root (Path | str): Path to the root of the dataset
-        category (str): Sub-category of the dataset, e.g. 'bottle'
+        category (str): Sub-category of the dataset, e.g. "UCSDped1" or "UCSDped2"
         clip_length_in_frames (int, optional): Number of video frames in each clip.
         frames_between_clips (int, optional): Number of frames between each consecutive video clip.
         target_frame (VideoTargetFrame): Specifies the target frame in the video clip, used for ground truth retrieval

src/anomalib/data/visa.py

@@ -55,6 +55,21 @@
     hash="ef908989b6dc701fc218f643c127a4de",
 )
 
+CATEGORIES = (
+    "candle",
+    "capsules",
+    "cashew",
+    "chewinggum",
+    "fryum",
+    "macaroni1",
+    "macaroni2",
+    "pcb1",
+    "pcb2",
+    "pcb3",
+    "pcb4",
+    "pipe_fryum",
+)
+
 
 class VisaDataset(AnomalibDataset):
     """VisA dataset class.