Fix packaging and Address pre-commit updates.

.pre-commit-config.yaml

@@ -3,7 +3,7 @@ default_language_version:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.5.0
+    rev: v4.6.0
     hooks:
       # list of supported hooks: https://pre-commit.com/hooks.html
       - id: trailing-whitespace
@@ -15,7 +15,7 @@ repos:
 
   # Ruff version.
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: "v0.1.5"
+    rev: "v0.5.0"
     hooks:
       # Run the linter.
       - id: ruff
@@ -27,35 +27,35 @@ repos:
 
   # python static type checking
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: "v1.7.0"
+    rev: "v1.10.1"
     hooks:
       - id: mypy
         additional_dependencies: [types-PyYAML, types-setuptools]
         exclude: "tests"
 
   # add bandit for security checks
   - repo: https://github.com/PyCQA/bandit
-    rev: 1.7.7
+    rev: 1.7.9
     hooks:
       - id: bandit
         args: ["-c", "pyproject.toml"]
         additional_dependencies: ["bandit[toml]"]
 
   # notebooks.
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.7.0
+    rev: 1.8.5
     hooks:
       - id: nbqa-ruff
         # Ignore unsorted imports. This is because jupyter notebooks can import
         # packages in a different order than the rest of the codebase.
         args: ["--ignore=D100,D407,I001"]
 
   - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v3.1.0
+    rev: v4.0.0-alpha.8
     hooks:
       - id: prettier
 
   - repo: https://github.com/igorshubovych/markdownlint-cli
-    rev: v0.37.0
+    rev: v0.41.0
     hooks:
       - id: markdownlint

CHANGELOG.md

@@ -34,6 +34,8 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Remove deprecated `pkg_resources` dependencies, install `packaging` instead by @davnn in (<https://github.com/openvinotoolkit/anomalib/pull/2082>)
+- WinCLIP: set device in text embedding collection and apply forward pass with no grad, by @djdameln in https://github.com/openvinotoolkit/anomalib/pull/1984
 - 🔨 Move all export functionalities to AnomalyModule as base methods by @thinhngo-x in (<https://github.com/openvinotoolkit/anomalib/pull/1803>)
 - ⬆️ Update torch and lightning package versions by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/1949
 - 🔨 Use default model-specific eval transform when only train_transform specified by @djdameln(https://github.com/djdameln) in (<https://github.com/openvinotoolkit/anomalib/pull/1953>)

MAINTAINERS.md

@@ -28,7 +28,7 @@ We welcome contributions from everyone. If you're interested in helping out, ple
 Here is a list of contributors of Anomalib:
 
 <a href="https://github.com/openvinotoolkit/anomalib/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=openvinotoolkit/anomalib" />
+  <img src="https://contrib.rocks/image?repo=openvinotoolkit/anomalib" alt="Contributors to openvinotoolkit/anomalib" />
 </a>
 
 ## 🙏 Acknowledgements

README.md

@@ -1,6 +1,6 @@
 <div align="center">
 
-<img src="https://github.com/raw/openvinotoolkit/anomalib/main/docs/source/_static/images/logos/anomalib-wide-blue.png" width="600px">
+<img src="https://github.com/raw/openvinotoolkit/anomalib/main/docs/source/_static/images/logos/anomalib-wide-blue.png" width="600px" alt="Anomalib Logo">
 
 **A library for benchmarking, developing and deploying deep learning anomaly detection algorithms**
 
@@ -30,7 +30,7 @@
 Anomalib is a deep learning library that aims to collect state-of-the-art anomaly detection algorithms for benchmarking on both public and private datasets. Anomalib provides several ready-to-use implementations of anomaly detection algorithms described in the recent literature, as well as a set of tools that facilitate the development and implementation of custom models. The library has a strong focus on visual anomaly detection, where the goal of the algorithm is to detect and/or localize anomalies within images or videos in a dataset. Anomalib is constantly updated with new algorithms and training/inference extensions, so keep checking!
 
 <p align="center">
-  <img src="https://github.com/raw/openvinotoolkit/anomalib/main/docs/source/_static/images/readme.png" width="1000">
+  <img src="https://github.com/raw/openvinotoolkit/anomalib/main/docs/source/_static/images/readme.png" width="1000" alt="A prediction made by anomalib">
 </p>
 
 ## Key features
@@ -304,5 +304,5 @@ For those who would like to contribute to the library, see [CONTRIBUTING.md](CON
 Thank you to all of the people who have already made a contribution - we appreciate your support!
 
 <a href="https://github.com/openvinotoolkit/anomalib/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=openvinotoolkit/anomalib" />
+  <img src="https://contrib.rocks/image?repo=openvinotoolkit/anomalib" alt="Contributors to openvinotoolkit/anomalib" />
 </a>

notebooks/500_use_cases/501_dobot/README.md

@@ -1,7 +1,7 @@
 # Dobot Use Case Tutorial
 
-| Notebook                 |                                                                                                                                                                                                                                                       |     |
-| ------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --- |
+| Notebook                 | Link                                                                                                                                                                                                                                                   |
+| ------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
 | Training a Model         | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/main/notebooks/500_use_cases/501_dobot/501a_training_a_model_with_cubes_from_a_robotic_arm.ipynb) |
 | Inference with the Model | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/main/notebooks/500_use_cases/501_dobot/501b_inference_with_a_robotic_arm.ipynb)                   |
 

pyproject.toml

@@ -34,6 +34,7 @@ dependencies = [
     "jsonargparse[signatures]>=4.27.7",
     "docstring_parser",     # CLI help-formatter
     "rich_argparse",        # CLI help-formatter
+    "packaging"
 ]
 
 [project.optional-dependencies]

src/anomalib/callbacks/__init__.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import logging
 from importlib import import_module
 from pathlib import Path

src/anomalib/callbacks/metrics.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import logging
 from enum import Enum
 from typing import Any

src/anomalib/callbacks/model_loader.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import logging
 
 import torch

src/anomalib/callbacks/nncf/callback.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import subprocess  # nosec B404
 from pathlib import Path
 from typing import TYPE_CHECKING, Any

src/anomalib/callbacks/nncf/utils.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import logging
 from copy import copy
 from typing import TYPE_CHECKING, Any

src/anomalib/callbacks/normalization/min_max_normalization.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022-2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 from typing import Any
 
 import torch

src/anomalib/callbacks/post_processor.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 from typing import Any
 
 import torch

src/anomalib/callbacks/tiler_configuration.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 from collections.abc import Sequence
 
 import lightning.pytorch as pl

src/anomalib/cli/install.py

@@ -5,15 +5,11 @@
 
 import logging
 
-from pkg_resources import Requirement
+from packaging.version import parse
 from rich.console import Console
 from rich.logging import RichHandler
 
-from anomalib.cli.utils.installation import (
-    get_requirements,
-    get_torch_install_args,
-    parse_requirements,
-)
+from anomalib.cli.utils.installation import get_requirements, get_torch_install_args, parse_requirements
 
 logger = logging.getLogger("pip")
 logger.setLevel(logging.WARNING)  # setLevel: CRITICAL, ERROR, WARNING, INFO, DEBUG, NOTSET
@@ -50,7 +46,7 @@ def anomalib_install(option: str = "full", verbose: bool = False) -> int:
     elif option in requirements_dict:
         requirements.extend(requirements_dict[option])
     elif option is not None:
-        requirements.append(Requirement.parse(option))
+        requirements.append(parse(option))
 
     # Parse requirements into torch and other requirements.
     # This is done to parse the correct version of torch (cpu/cuda).

src/anomalib/cli/pipelines.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import logging
 
 from jsonargparse import Namespace

src/anomalib/cli/utils/installation.py

@@ -11,9 +11,13 @@
 import re
 from importlib.metadata import requires
 from pathlib import Path
+from typing import TYPE_CHECKING
 from warnings import warn
 
-from pkg_resources import Requirement
+from packaging.version import parse
+
+if TYPE_CHECKING:
+    from packaging.requirements import Requirement
 
 AVAILABLE_TORCH_VERSIONS = {
     "2.0.0": {"torchvision": "0.15.1", "cuda": ("11.7", "11.8")},
@@ -50,7 +54,7 @@ def get_requirements(module: str = "anomalib") -> dict[str, list[Requirement]]:
         if isinstance(requirement_extra, list) and len(requirement_extra) > 1:
             extra = requirement_extra[-1].split("==")[-1].strip("'\"")
         _requirement_name = requirement_extra[0]
-        _requirement = Requirement.parse(_requirement_name)
+        _requirement = parse(_requirement_name)
         if extra in extra_requirement:
             extra_requirement[extra].append(_requirement)
         else:
@@ -73,12 +77,12 @@ def parse_requirements(
 
     Examples:
         >>> requirements = [
-        ...     Requirement.parse("torch==1.13.0"),
-        ...     Requirement.parse("onnx>=1.8.1"),
+        ...     parse("torch==1.13.0"),
+        ...     parse("onnx>=1.8.1"),
         ... ]
         >>> parse_requirements(requirements=requirements)
-        (Requirement.parse("torch==1.13.0"),
-        Requirement.parse("onnx>=1.8.1"))
+        (parse("torch==1.13.0"),
+        parse("onnx>=1.8.1"))
 
     Returns:
         tuple[str, list[str], list[str]]: Tuple of torch and other requirements.
@@ -293,9 +297,9 @@ def add_hardware_suffix_to_torch(
             Defaults to False.
 
     Examples:
-        >>> from pkg_resources import Requirement
+        >>> from packaging.requirements import Requirement
         >>> req = "torch>=1.13.0, <=2.0.1"
-        >>> requirement = Requirement.parse(req)
+        >>> requirement = parse(req)
         >>> requirement.name, requirement.specs
         ('torch', [('>=', '1.13.0'), ('<=', '2.0.1')])
 
@@ -304,13 +308,13 @@ def add_hardware_suffix_to_torch(
 
         ``with_available_torch_build=True`` will use the latest available PyTorch build.
         >>> req = "torch==2.0.1"
-        >>> requirement = Requirement.parse(req)
+        >>> requirement = parse(req)
         >>> add_hardware_suffix_to_torch(requirement, with_available_torch_build=True)
         'torch==2.0.1+cu118'
 
         It is possible to pass the ``hardware_suffix`` manually.
         >>> req = "torch==2.0.1"
-        >>> requirement = Requirement.parse(req)
+        >>> requirement = parse(req)
         >>> add_hardware_suffix_to_torch(requirement, hardware_suffix="cu121")
         'torch==2.0.1+cu111'
 
@@ -364,7 +368,7 @@ def get_torch_install_args(requirement: str | Requirement) -> list[str]:
         RuntimeError: If the OS is not supported.
 
     Example:
-        >>> from pkg_resources import Requirement
+        >>> from packaging.requirements import Requirement
         >>> requriment = "torch>=1.13.0"
         >>> get_torch_install_args(requirement)
         ['--extra-index-url', 'https://download.pytorch.org/whl/cpu',
@@ -374,7 +378,7 @@ def get_torch_install_args(requirement: str | Requirement) -> list[str]:
         list[str]: The install arguments.
     """
     if isinstance(requirement, str):
-        requirement = Requirement.parse(requirement)
+        requirement = parse(requirement)
 
     # NOTE: This does not take into account if the requirement has multiple versions
     #   such as torch<2.0.1,>=1.13.0

src/anomalib/data/__init__.py

@@ -28,8 +28,7 @@
 )
 
 
-class UnknownDatamoduleError(ModuleNotFoundError):
-    ...
+class UnknownDatamoduleError(ModuleNotFoundError): ...
 
 
 def get_datamodule(config: DictConfig | ListConfig | dict) -> AnomalibDataModule:

src/anomalib/data/base/__init__.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 from .datamodule import AnomalibDataModule
 from .dataset import AnomalibDataset
 from .depth import AnomalibDepthDataset

src/anomalib/data/base/datamodule.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022-2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import logging
 from abc import ABC, abstractmethod
 from pathlib import Path

src/anomalib/data/depth/__init__.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 from enum import Enum
 
 from .folder_3d import Folder3D

src/anomalib/data/depth/folder_3d.py

@@ -6,7 +6,6 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 from pathlib import Path
 
 from pandas import DataFrame, isna

src/anomalib/data/depth/mvtec_3d.py

@@ -19,7 +19,6 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import logging
 from collections.abc import Sequence
 from pathlib import Path

src/anomalib/data/image/__init__.py

@@ -6,7 +6,6 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 from enum import Enum
 
 from .btech import BTech

src/anomalib/data/image/visa.py

@@ -21,7 +21,6 @@
 # Subset splitting code adapted from https://github.com/amazon-science/spot-diff
 # Original licence: Apache-2.0
 
-
 import csv
 import logging
 import shutil

src/anomalib/data/predict.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022-2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 from pathlib import Path
 from typing import Any
 

src/anomalib/data/utils/augmenter.py

@@ -9,7 +9,6 @@
 # Copyright (C) 2022-2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import math
 import random
 from pathlib import Path

src/anomalib/data/utils/boxes.py

@@ -3,7 +3,6 @@
 # Copyright (C) 2022-2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-
 import torch
 
 from anomalib.utils.cv import connected_components_cpu, connected_components_gpu