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🚀 Anomalib v2 Stable Release (#2608)
* Create v2 branch Signed-off-by: Samet Akcay <[email protected]> * Remove beta references from readme.md Signed-off-by: Samet Akcay <[email protected]> --------- Signed-off-by: Samet Akcay <[email protected]>
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CHANGELOG.md

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### Added
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- 🚀 Add XPU accelerator and strategy by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2530
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### Removed
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### Changed
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- 🚀 Made OpenVINOInferencer and TorchInferencer predict accept all the following types: str, Path, np.ndarray, PIL.Image.Image, torch.Tensor by @adrianboguszewski in https://github.com/openvinotoolkit/anomalib/pull/2565
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### Deprecated
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### Fixed
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- 🚀 Add Multi-GPU Training Support by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2435
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- 🔨 Refactor: Add missing auxiliary attributes to `AnomalibModule` by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/2460
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- 🔨 Rename `AnomalyModule` to `AnomalibModule` by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/2423
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- 🚀 Add `AUPIMO` metric by [jpcbertoldo](https://github.com/jpcbertoldo) in https://github.com/openvinotoolkit/anomalib/pull/1726 and refactored by [ashwinvaidya17](https://github.com/ashwinvaidya17) in https://github.com/openvinotoolkit/anomalib/pull/2329
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- 📚 Add `AUPIMO` tutorials notebooks in https://github.com/openvinotoolkit/anomalib/pull/2330 and https://github.com/openvinotoolkit/anomalib/pull/2336
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- 🚀 Add XPU accelerator by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2530
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- Add beta release support by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/2493
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- Add merge group to main branch by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2520
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- Add non-strict mode to AnomalibMetric by @djdameln in https://github.com/openvinotoolkit/anomalib/pull/2508
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- Add DCO merge group workflow configuration by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2528
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- Add configuration options to PostProcessor by @djdameln in https://github.com/openvinotoolkit/anomalib/pull/2547
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- Add MVTec backward compatibility by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/2602
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- Add unit tests for MinMax metric by @djdameln in https://github.com/openvinotoolkit/anomalib/pull/2516
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- 🔨 Linting: Enable `PLR6301`, # could be a function, class method or static method by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/2288
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- 🔨 Restructure unit tests and fix ruff issues by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/2306pdate Ruff Config - Add Missing Copyright Headers by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/2281
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- 🔨 optimization/quantization added into 500 series by @paularamo in https://github.com/openvinotoolkit/anomalib/pull/2197
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- 🚀 Made OpenVINOInferencer and TorchInferencer predict accept all the following types: str, Path, np.ndarray, PIL.Image.Image, torch.Tensor by @adrianboguszewski in https://github.com/openvinotoolkit/anomalib/pull/2565
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### Fixed
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- 🐞Replace package_available with module_available by @harimkang in https://github.com/openvinotoolkit/anomalib/pull/2407
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- Fix multi-GPU support for post-processor by @djdameln in https://github.com/openvinotoolkit/anomalib/pull/2499
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- fix minmax by @alexriedel1 in https://github.com/openvinotoolkit/anomalib/pull/2512
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- 🛠️ Fix pre-commit issues by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2517
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- Minor fixes by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2522
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- 🐞Fix ollama by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2519
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- fix synthetic anomaly datasets by @alexriedel1 in https://github.com/openvinotoolkit/anomalib/pull/2497
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- Fix compatibility issue with cPython<=3.11.3 by @Kogia-sima in https://github.com/openvinotoolkit/anomalib/pull/2416
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- Fix onnx input parameter name by @terrarier2111 in https://github.com/openvinotoolkit/anomalib/pull/2525
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- Fix latest torch and torchvision compatibility by @djdameln in https://github.com/openvinotoolkit/anomalib/pull/2548
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- Fix post-processing visualization issues by @djdameln in https://github.com/openvinotoolkit/anomalib/pull/2534
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- Keep weights in state dict when exporting by @ashwinvaidya17 in https://github.com/openvinotoolkit/anomalib/pull/2582
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### New Contributors
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- @Kogia-sima made their first contribution in https://github.com/openvinotoolkit/anomalib/pull/2416
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- @terrarier2111 made their first contribution in https://github.com/openvinotoolkit/anomalib/pull/2525
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## [v1.2.0]
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- OV API1.0 by @paularamo in https://github.com/openvinotoolkit/anomalib/pull/1098
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###  Fixed
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### Fixed
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- Fix Fastflow ONNX export. by @jasonvanzelm in https://github.com/openvinotoolkit/anomalib/pull/1108
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- Fix tile import typo by @xbkaishui in https://github.com/openvinotoolkit/anomalib/pull/1106
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- Remove config dependency from `OpenVINOInferencer` by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/939
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- Remove config from torch inferencer by @samet-akcay in https://github.com/openvinotoolkit/anomalib/pull/1001
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###  Fixed
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### Fixed
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- Bugfix code logic to allow for passing of `nn.Module` to `TorchFXFeatureExtractor` by @ORippler in https://github.com/openvinotoolkit/anomalib/pull/935
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- fix broken links to tutorials (ex guides) by @sergiev in https://github.com/openvinotoolkit/anomalib/pull/957

README.md

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> 🌟 **Announcing v2.0.0 Beta Release!** 🌟
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> 🌟 **Announcing v2.0.0 Release!** 🌟
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> We're excited to announce the beta release of Anomalib v2.0.0! This version introduces significant improvements and customization options to enhance your anomaly detection workflows. Please be aware that there are several API changes between `v1.2.0` and `v2.0.0`, so please be careful when updating your existing pipelines. We invite you to try it out and share your feedback:
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> We're excited to announce the release of Anomalib v2.0.0! This version introduces significant improvements and customization options to enhance your anomaly detection workflows. Please be aware that there are several API changes between `v1.2.0` and `v2.0.0`, so please be careful when updating your existing pipelines. Key features include:
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> - Multi-GPU support
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> - New [dataclasses](https://anomalib.readthedocs.io/en/latest/markdown/guides/how_to/data/dataclasses.html) for model in- and outputs.
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> - Customizable model evaluation workflow with new [Metrics API](https://anomalib.readthedocs.io/en/latest/markdown/guides/how_to/evaluation/metrics.html) and [`Evaluator`](https://anomalib.readthedocs.io/en/latest/markdown/guides/how_to/evaluation/evaluator.html) module.
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> - Configurable module for visualization via `Visualizer` (docs guide: coming soon)
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> We value your input! Please test and share feedback via [GitHub Issues](https://github.com/openvinotoolkit/anomalib/issues) or our [Discussions](https://github.com/openvinotoolkit/anomalib/discussions)
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> Install beta: `pip install anomalib==2.0.0b2`
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> We value your input! Please share feedback via [GitHub Issues](https://github.com/openvinotoolkit/anomalib/issues) or our [Discussions](https://github.com/openvinotoolkit/anomalib/discussions)
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# 👋 Introduction
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Anomalib provides multiple installation options to suit your needs. Choose the one that best fits your requirements:
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## 🚀 Quick Install (Stable)
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## 🚀 Install from PyPI
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```bash
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# Basic installation
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# Basic installation from PyPI
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pip install anomalib
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# Full installation with all dependencies
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pip install anomalib[full]
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```
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## 🌟 Beta Version (v2.0.0b2)
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Try our latest beta release with new features and improvements:
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```bash
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# Basic beta installation
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pip install anomalib==2.0.0b2
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pip install anomalib[full]==2.0.0b2
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```
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### 🛠️ Installation Options
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Use the CLI for customized installation:
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```bash
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# Get help for installation options
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anomalib install -h
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# Full package installation
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anomalib install
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# Core package only (for training and evaluation)
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anomalib install --option core
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# OpenVINO optimization support
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anomalib install --option openvino
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```
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### 🔧 Development Install
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## 🔧 Install from Source
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For contributing or customizing the library:
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src/anomalib/__init__.py

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from enum import Enum
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__version__ = "2.0.0b3"
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__version__ = "2.0.0"
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class LearningType(str, Enum):

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