🚀 feat(dataset): add 3D-ADAM dataset to Anomalib

docs/source/examples

@@ -0,0 +1 @@
+../../examples

examples/configs/data/adam_3d.yaml

@@ -0,0 +1,10 @@
+class_path: anomalib.data.ADA3D
+init_args:
+  root: ./datasets/ADAM3D
+  category: "1m1"
+  train_batch_size: 32
+  eval_batch_size: 32
+  num_workers: 8
+  test_split_mode: from_dir
+  val_split_mode: from_dir
+  seed: null

src/anomalib/data/__init__.py

@@ -48,7 +48,7 @@
 
 # Datamodules
 from .datamodules.base import AnomalibDataModule
-from .datamodules.depth import DepthDataFormat, Folder3D, MVTec3D
+from .datamodules.depth import ADAM3D, DepthDataFormat, Folder3D, MVTec3D
 from .datamodules.image import (
     MPDD,
     VAD,
@@ -69,7 +69,7 @@
 
 # Datasets
 from .datasets import AnomalibDataset
-from .datasets.depth import Folder3DDataset, MVTec3DDataset
+from .datasets.depth import ADAM3DDataset, Folder3DDataset, MVTec3DDataset
 from .datasets.image import (
     BTechDataset,
     DatumaroDataset,
@@ -175,6 +175,7 @@ def get_datamodule(config: DictConfig | ListConfig | dict) -> AnomalibDataModule
     # Depth Data Modules
     "Folder3D",
     "MVTec3D",
+    "ADAM3D",
     # Image Data Modules
     "BTech",
     "Datumaro",
@@ -201,6 +202,7 @@ def get_datamodule(config: DictConfig | ListConfig | dict) -> AnomalibDataModule
     "FolderDataset",
     "KolektorDataset",
     "MPDDDataset",
+    "ADAM3DDataset",
     "MVTecADDataset",
     "MVTecLOCODataset",
     "TabularDataset",

src/anomalib/data/datamodules/depth/__init__.py

@@ -5,6 +5,7 @@
 
 from enum import Enum
 
+from .adam_3d import ADAM3D
 from .folder_3d import Folder3D
 from .mvtec_3d import MVTec3D
 
@@ -14,6 +15,7 @@ class DepthDataFormat(str, Enum):
 
     MVTEC_3D = "mvtec_3d"
     FOLDER_3D = "folder_3d"
+    ADAM_3D = "adam_3d"
 
 
-__all__ = ["Folder3D", "MVTec3D"]
+__all__ = ["Folder3D", "MVTec3D", "ADAM3D"]

src/anomalib/data/datamodules/depth/adam_3d.py

@@ -0,0 +1,139 @@
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+"""3D-ADAM Datamodule.
+
+This module provides a PyTorch Lightning DataModule for the 3D-ADAM dataset.
+The dataset contains RGB and depth image pairs for anomaly detection tasks.
+
+Example:
+    Create a ADAM3D datamodule::
+
+        >>> from anomalib.data import ADAM3D
+        >>> datamodule = ADAM3D(
+        ...     root="./datasets/ADAM3D",
+        ...     category="1m1"
+        ... )
+
+License:
+    3D-ADAM dataset is released under the Creative Commons
+    Attribution-NonCommercial-ShareAlike 4.0 International License
+    (CC BY-NC-SA 4.0).
+    https://creativecommons.org/licenses/by-nc-sa/4.0/
+
+Reference: https://arxiv.org/abs/2507.07838
+
+"""
+
+import logging
+from pathlib import Path
+
+from torchvision.transforms.v2 import Transform
+
+from anomalib.data.datamodules.base.image import AnomalibDataModule
+from anomalib.data.datasets.depth.adam_3d import ADAM3DDataset
+from anomalib.data.utils import DownloadInfo, Split, TestSplitMode, ValSplitMode, download_and_extract
+
+logger = logging.getLogger(__name__)
+
+
+DOWNLOAD_INFO = DownloadInfo(
+    name="adam_3d",
+    url="https://huggingface.co/datasets/pmchard/3D-ADAM_anomalib/blob/main/adam3d_cropped.zip",
+    hashsum="ffc4c52afa1566a4165c42300c21758ec8292ff04305c65e81e830abb8200c36",
+)
+
+
+class ADAM3D(AnomalibDataModule):
+    """3D-ADAM Datamodule.
+
+    Args:
+        root (Path | str): Path to the root of the dataset.
+            Defaults to ``"./datasets/ADAM3D"``.
+        category (str): Category of the 3D-ADAM dataset (e.g. ``"1m1"`` or
+            ``"spiral_gear"``). Defaults to ``"1m1"``.
+        train_batch_size (int, optional): Training batch size.
+            Defaults to ``32``.
+        eval_batch_size (int, optional): Test batch size.
+            Defaults to ``32``.
+        num_workers (int, optional): Number of workers for data loading.
+            Defaults to ``8``.
+        train_augmentations (Transform | None): Augmentations to apply dto the training images
+            Defaults to ``None``.
+        val_augmentations (Transform | None): Augmentations to apply to the validation images.
+            Defaults to ``None``.
+        test_augmentations (Transform | None): Augmentations to apply to the test images.
+            Defaults to ``None``.
+        augmentations (Transform | None): General augmentations to apply if stage-specific
+            augmentations are not provided.
+        test_split_mode (TestSplitMode | str): Method to create test set.
+            Defaults to ``TestSplitMode.FROM_DIR``.
+        test_split_ratio (float): Fraction of data to use for testing.
+            Defaults to ``0.2``.
+        val_split_mode (ValSplitMode | str): Method to create validation set.
+            Defaults to ``ValSplitMode.SAME_AS_TEST``.
+        val_split_ratio (float): Fraction of data to use for validation.
+            Defaults to ``0.5``.
+        seed (int | None, optional): Random seed for reproducibility.
+            Defaults to ``None``.
+    """
+
+    def __init__(
+        self,
+        root: Path | str = "./datasets/ADAM3D",
+        category: str = "1m1",
+        train_batch_size: int = 32,
+        eval_batch_size: int = 32,
+        num_workers: int = 8,
+        train_augmentations: Transform | None = None,
+        val_augmentations: Transform | None = None,
+        test_augmentations: Transform | None = None,
+        augmentations: Transform | None = None,
+        test_split_mode: TestSplitMode | str = TestSplitMode.FROM_DIR,
+        test_split_ratio: float = 0.2,
+        val_split_mode: ValSplitMode | str = ValSplitMode.SAME_AS_TEST,
+        val_split_ratio: float = 0.5,
+        seed: int | None = None,
+    ) -> None:
+        super().__init__(
+            train_batch_size=train_batch_size,
+            eval_batch_size=eval_batch_size,
+            num_workers=num_workers,
+            train_augmentations=train_augmentations,
+            val_augmentations=val_augmentations,
+            test_augmentations=test_augmentations,
+            augmentations=augmentations,
+            test_split_mode=test_split_mode,
+            test_split_ratio=test_split_ratio,
+            val_split_mode=val_split_mode,
+            val_split_ratio=val_split_ratio,
+            seed=seed,
+        )
+
+        self.root = Path(root)
+        self.category = category
+
+    def _setup(self, _stage: str | None = None) -> None:
+        """Set up the datasets.
+
+        Args:
+            _stage (str | None, optional): Stage of setup. Not used.
+                Defaults to ``None``.
+        """
+        self.train_data = ADAM3DDataset(
+            split=Split.TRAIN,
+            root=self.root,
+            category=self.category,
+        )
+        self.test_data = ADAM3DDataset(
+            split=Split.TEST,
+            root=self.root,
+            category=self.category,
+        )
+
+    def prepare_data(self) -> None:
+        """Download the dataset if not available."""
+        if (self.root / self.category).is_dir():
+            logger.info("Found the dataset.")
+        else:
+            download_and_extract(self.root, DOWNLOAD_INFO)

src/anomalib/data/datasets/__init__.py

@@ -13,6 +13,7 @@
 Depth Datasets:
     - ``Folder3DDataset``: Custom RGB-D dataset from folder structure
     - ``MVTec3DDataset``: MVTec 3D AD dataset with industrial objects
+    - ``ADAM3DDataset``: 3D ADAM dataset with additive manufactured objects
 
 Image Datasets:
     - ``BTechDataset``: BTech dataset containing industrial objects
@@ -40,7 +41,7 @@
 """
 
 from .base import AnomalibDataset, AnomalibDepthDataset, AnomalibVideoDataset
-from .depth import Folder3DDataset, MVTec3DDataset
+from .depth import ADAM3DDataset, Folder3DDataset, MVTec3DDataset
 from .image import (
     BTechDataset,
     DatumaroDataset,
@@ -62,6 +63,7 @@
     # Depth
     "Folder3DDataset",
     "MVTec3DDataset",
+    "ADAM3DDataset",
     # Image
     "BTechDataset",
     "DatumaroDataset",

src/anomalib/data/datasets/depth/__init__.py

@@ -8,6 +8,7 @@
 
 - ``Folder3DDataset``: Custom dataset for loading RGB-D data from a folder structure
 - ``MVTec3DDataset``: Implementation of the MVTec 3D-AD dataset
+- ``ADAM3DDataset``: Implementation of the 3D-ADAM dataset
 
 Example:
     >>> from anomalib.data.datasets import Folder3DDataset
@@ -25,7 +26,8 @@
     ... )
 """
 
+from .adam_3d import ADAM3DDataset
 from .folder_3d import Folder3DDataset
 from .mvtec_3d import MVTec3DDataset
 
-__all__ = ["Folder3DDataset", "MVTec3DDataset"]
+__all__ = ["Folder3DDataset", "MVTec3DDataset", "ADAM3DDataset"]