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.
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 |
|---|
| Notebook | GitHub | Colab |
|---|---|---|
| Getting Started | 001_getting_started |  |
| Notebook | GitHub | Colab |
|---|---|---|
| BTech | 101_btech | |
| MVTec | 102_mvtec | |
| Folder | 103_folder | |
| Notebook | GitHub | Colab |
|---|---|---|
| Model | 201_fastflow | |
| Notebook | GitHub | Colab |
|---|---|---|
| Quantization | 401_NNCF |
| Notebook | GitHub | Colab |
|---|---|---|
| Dobot Dataset Creation | 501a_training | |
| Training | 501b_training |
| 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 | |