🚀 feat(model): add GLASS model into Anomalib

src/anomalib/models/__init__.py

@@ -66,6 +66,7 @@
     Fastflow,
     Fre,
     Ganomaly,
+    Glass,
     Padim,
     Patchcore,
     ReverseDistillation,
@@ -102,6 +103,7 @@ class UnknownModelError(ModuleNotFoundError):
     "Fastflow",
     "Fre",
     "Ganomaly",
+    "Glass",
     "Padim",
     "Patchcore",
     "ReverseDistillation",

src/anomalib/models/components/feature_extractors/__init__.py

@@ -28,7 +28,6 @@
 
 from .timm import TimmFeatureExtractor
 from .utils import dryrun_find_featuremap_dims
-
 __all__ = [
     "dryrun_find_featuremap_dims",
     "TimmFeatureExtractor",

src/anomalib/models/image/__init__.py

@@ -55,6 +55,7 @@
 from .fastflow import Fastflow
 from .fre import Fre
 from .ganomaly import Ganomaly
+from .glass import Glass
 from .padim import Padim
 from .patchcore import Patchcore
 from .reverse_distillation import ReverseDistillation
@@ -76,12 +77,13 @@
     "Fastflow",
     "Fre",
     "Ganomaly",
+    "Glass",
     "Padim",
     "Patchcore",
     "ReverseDistillation",
     "Stfpm",
     "Supersimplenet",
     "Uflow",
     "VlmAd",
-    "WinClip",
+    "WinClip"
 ]

src/anomalib/models/image/glass/__init__.py

@@ -0,0 +1,23 @@
+"""GLASS - Unsupervised anomaly detection via Gradient Ascent for Industrial Anomaly detection and localization.
+
+This module implements the GLASS model for unsupervised anomaly detection and localization. GLASS synthesizes both
+global and local anomalies using Gaussian noise guided by gradient ascent to enhance weak defect detection in
+industrial settings.
+
+The model consists of:
+    - A feature extractor and feature adaptor to obtain robust normal representations
+    - A Global Anomaly Synthesis (GAS) module that perturbs features using Gaussian noise and gradient ascent with
+      truncated projection
+    - A Local Anomaly Synthesis (LAS) module that overlays augmented textures onto images using Perlin noise masks
+    - A shared discriminator trained with features from normal, global, and local synthetic samples
+
+Paper: `A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
+<https://arxiv.org/pdf/2407.09359>`
+"""
+
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from .lightning_model import Glass
+
+__all__ = ["Glass"]