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The previous commit was meant to remove .github/workflows and removed every tracked path instead — 892 files, the whole repo. This puts back the 874 that were never in scope; the eighteen workflow files stay gone, for the reasons that commit gives. Content is byte-identical to 9d2aec9 outside .github/workflows.
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Anomalib notebooks
This is a great place in our repo where you can try some capabilities and functions you can achive with Anomalib. First follow the installation guide and then explore the notebooks that it offer to you.
⚙️ Installation Guide
To install Python, Git and other required tools, OpenVINO Notebooks repository provides a good documentation. For more details please refer to the Installation Guide.
| Windows | Ubuntu | macOS | Red Hat | CentOS | Azure ML | Docker | Amazon SageMaker |
|---|
Useful Jupyter Notebooks to get started with Anomalib
0. Training and Inference
| Notebook | GitHub | Colab |
|---|---|---|
| Getting Started | 001_getting_started |
1. Data Modules
| Notebook | GitHub | Colab |
|---|---|---|
| BTech | 101_btech | |
| MVTecAD | 102_mvtec | |
| Folder | 103_folder |
2. Models
| Notebook | GitHub | Colab |
|---|---|---|
| Model | 201_fastflow |
3. OpenVINO Optimization
| Notebook | GitHub | Colab |
|---|---|---|
| Quantization | 401_NNCF |
4. Use cases
| Notebook | GitHub | Colab |
|---|---|---|
| Dobot Dataset Creation | 501a_training | |
| Training | 501b_training |
7. Metrics
| Notebook | GitHub | Colab |
|---|---|---|
| AUPIMO basics | 701a_aupimo | |
| AUPIMO representative samples and visualization | 701b_aupimo_advanced_i | |
| PIMO curve and integration bounds | 701c_aupimo_advanced_ii | |
| (AU)PIMO of a random model | 701d_aupimo_advanced_iii | |
| AUPIMO load/save, statistical comparison | 701e_aupimo_advanced_iv |
