openvinotoolkit · samet-akcay · Aug 3, 2022 · Aug 3, 2022 · Aug 3, 2022 · Aug 3, 2022
@@ -2,7 +2,7 @@ name: Docs
 
 on:
   push:
-    branches: [development]
+    branches: [main]
     paths-ignore:
       - ".github/**" # Ignore changes towards the .github directory
   workflow_dispatch: # run on request (no need for PR)

@@ -10,7 +10,7 @@ jobs:
     runs-on: [self-hosted, linux, x64]
     strategy:
       max-parallel: 1
-    if: github.ref == 'refs/heads/development'
+    if: github.ref == 'refs/heads/main'
     steps:
       - name: Print GPU status
         run: nvidia-smi

@@ -2,7 +2,7 @@ name: Pre-Merge Checks
 
 on:
   push:
-    branches: [development, master]
+    branches: [main]
   pull_request:
   workflow_dispatch: # run on request (no need for PR)
 

@@ -0,0 +1,21 @@
+name: Upload Python Package
+on:
+  release:
+    types: [created]
+jobs:
+  deploy:
+    runs-on: ubuntu-20.04
+    steps:
+      - uses: actions/checkout@v2
+      - uses: actions/setup-python@v2
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install setuptools wheel twine
+      - name: Build and publish
+        env:
+          TWINE_USERNAME: __token__
+          TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+        run: |
+          python setup.py sdist bdist_wheel
+          twine upload dist/*
@@ -26,7 +26,7 @@ We utilize GitHub issues to track the feature requests as well. If you are certa
 
 We actively welcome your pull requests:
 
-1. Fork the repo and create your branch from [`development`](https://github.com/openvinotoolkit/anomalib/tree/development).
+1. Fork the repo and create your branch from [`main`](https://github.com/openvinotoolkit/anomalib/tree/main).
 1. If you've added code that should be tested, add tests.
 1. If you've changed APIs, update the documentation.
 1. Ensure the test suite passes.

@@ -9,7 +9,7 @@
 [Key Features](#key-features) •
 [Getting Started](#getting-started) •
 [Docs](https://openvinotoolkit.github.io/anomalib) •
-[License](https://github.com/openvinotoolkit/anomalib/blob/development/LICENSE)
+[License](https://github.com/openvinotoolkit/anomalib/blob/main/LICENSE)
 
 [![python](https://img.shields.io/badge/python-3.7%2B-green)]()
 [![pytorch](https://img.shields.io/badge/pytorch-1.8.1%2B-orange)]()
@@ -76,15 +76,15 @@ pip install -e .
 
 ## ⚠️ Anomalib < v.0.4.0
 
-By default [`python tools/train.py`](https://gitlab-icv.inn.intel.com/algo_rnd_team/anomaly/-/blob/development/train.py)
+By default [`python tools/train.py`](https://gitlab-icv.inn.intel.com/algo_rnd_team/anomaly/-/blob/main/train.py)
 runs [PADIM](https://arxiv.org/abs/2011.08785) model on `leather` category from the [MVTec AD](https://www.mvtec.com/company/research/datasets/mvtec-ad) [(CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/) dataset.
 
 ```bash
 python tools/train.py    # Train PADIM on MVTec AD leather
 ```
 
 Training a model on a specific dataset and category requires further configuration. Each model has its own configuration
-file, [`config.yaml`](https://gitlab-icv.inn.intel.com/algo_rnd_team/anomaly/-/blob/development/padim/anomalib/models/padim/config.yaml)
+file, [`config.yaml`](https://gitlab-icv.inn.intel.com/algo_rnd_team/anomaly/-/blob/main/padim/anomalib/models/padim/config.yaml)
 , which contains data, model and training configurable parameters. To train a specific model on a specific dataset and
 category, the config file is to be provided:
 
@@ -156,7 +156,7 @@ We introduce a new CLI approach that uses [PyTorch Lightning CLI](https://pytorc
 anomalib fit --config <path/to/new/config/file>
 ```
 
-For instance, to train a [PatchCore](https://github.com/openvinotoolkit/anomalib/tree/development/anomalib/models/patchcore) model, the following command would be run:
+For instance, to train a [PatchCore](https://github.com/openvinotoolkit/anomalib/tree/main/anomalib/models/patchcore) model, the following command would be run:
 
 ```bash
 anomalib fit --config ./configs/model/patchcore.yaml

@@ -38,7 +38,7 @@ After building the image, you can run it as follows
 	anomalib \
 	/bin/bash
 
-This creates an interactive bash session inside the Docker container, in which you can run all anomalib commands as described in the `readme <https://github.com/openvinotoolkit/anomalib/blob/development/README.md>`_.
+This creates an interactive bash session inside the Docker container, in which you can run all anomalib commands as described in the `readme <https://github.com/openvinotoolkit/anomalib/blob/main/README.md>`_.
 
 The source code is mapped into the running container by means of the `-v "$(pwd)":/anomalib` parameter. This facilitates changes to the source code without having to rebuild the Docker image.
 

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<center><img src=\"https://github.com/raw/openvinotoolkit/anomalib/development/docs/source/images/logos/anomalib-wide-blue.png\" alt=\"Paris\" class=\"center\"></center>\n",
+    "<center><img src=\"https://github.com/raw/openvinotoolkit/anomalib/main/docs/source/images/logos/anomalib-wide-blue.png\" alt=\"Paris\" class=\"center\"></center>\n",
     "\n",
     "<center>💙 A library for benchmarking, developing and deploying deep learning anomaly detection algorithms</center>\n",
     "\n",
@@ -74,7 +74,7 @@
     "Currently, there are **7** anomaly detection models available in `anomalib` library. Namely,\n",
     "\n",
     "- [CFlow](https://arxiv.org/pdf/2107.12571v1.pdf)\n",
-    "- [DFKDE](https://github.com/openvinotoolkit/anomalib/tree/development/anomalib/models/dfkde)\n",
+    "- [DFKDE](https://github.com/openvinotoolkit/anomalib/tree/main/anomalib/models/dfkde)\n",
     "- [DFM](https://arxiv.org/pdf/1909.11786.pdf)\n",
     "- [Ganomaly](https://arxiv.org/abs/1805.06725)\n",
     "- [Padim](https://arxiv.org/pdf/2011.08785.pdf)\n",
@@ -109,7 +109,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We could use [get_configurable_parameter](https://github.com/openvinotoolkit/anomalib/blob/development/anomalib/config/config.py#L114) function to read the configs from the path and return them in a dictionary. We use the default config file that comes with Padim implementation, which uses `./datasets/MVTec` as the path to the dataset. We need to overwrite this after loading the config."
+    "We could use [get_configurable_parameter](https://github.com/openvinotoolkit/anomalib/blob/main/anomalib/config/config.py#L114) function to read the configs from the path and return them in a dictionary. We use the default config file that comes with Padim implementation, which uses `./datasets/MVTec` as the path to the dataset. We need to overwrite this after loading the config."
    ]
   },
   {
@@ -486,11 +486,8 @@
   }
  ],
  "metadata": {
-  "interpreter": {
-   "hash": "f26beec5b578f06009232863ae217b956681fd13da2e828fa5a0ecf8cf2ccd29"
-  },
   "kernelspec": {
-   "display_name": "Python 3.8.12 ('anomalib')",
+   "display_name": "Python 3.8.10 ('anomalib')",
    "language": "python",
    "name": "python3"
   },
@@ -504,9 +501,14 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.10"
   },
-  "orig_nbformat": 4
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "6a17319b3a437b8e0e3041e999c0deb965ce85aa030426c7edd15eb3312fca65"
+   }
+  }
  },
  "nbformat": 4,
  "nbformat_minor": 2

@@ -12,7 +12,7 @@
     "- A dataset with good and bad images as well as mask ground-truths for pixel-wise evaluation.\n",
     "- A dataset with good and bad images that is already split into training and testing sets.\n",
     "\n",
-    "To experiment this setting we provide a toy dataset that could be downloaded from the following [https://github.com/openvinotoolkit/anomalib/blob/development/docs/source/data/hazelnut_toy.zip](link). For the rest of the tutorial, we assume that the dataset is downloaded and extracted to `../../datasets`, located in the `anomalib` directory."
+    "To experiment this setting we provide a toy dataset that could be downloaded from the following [https://github.com/openvinotoolkit/anomalib/blob/main/docs/source/data/hazelnut_toy.zip](link). For the rest of the tutorial, we assume that the dataset is downloaded and extracted to `../../datasets`, located in the `anomalib` directory."
    ]
   },
   {

@@ -59,7 +59,7 @@
             "source": [
                 "## Data Module\n",
                 "\n",
-                "To train the model end-to-end, we do need to have a dataset. In our [previous notebooks](https://github.com/openvinotoolkit/anomalib/tree/development/notebooks/100_datamodules), we demonstrate how to initialize benchmark- and custom datasets. In this tutorial, we will use MVTec AD DataModule. We assume that `datasets` directory is created in the `anomalib` root directory and `MVTec` dataset is located in `datasets` directory."
+                "To train the model end-to-end, we do need to have a dataset. In our [previous notebooks](https://github.com/openvinotoolkit/anomalib/tree/main/notebooks/100_datamodules), we demonstrate how to initialize benchmark- and custom datasets. In this tutorial, we will use MVTec AD DataModule. We assume that `datasets` directory is created in the `anomalib` root directory and `MVTec` dataset is located in `datasets` directory."
             ]
         },
         {

@@ -2,26 +2,26 @@
 
 ## 0. Training and Inference
 
-| Notebook        | GitHub                                                               | Colab                                                                                                                                                                                                                    |
-| --------------- | -------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| Getting Started | [001_getting_started](000_getting_started/001_getting_started.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/development/notebooks/000_getting_started/001_getting_started.ipynb) |
+| Notebook        | GitHub                                                               | Colab                                                                                                                                                                                                             |
+| --------------- | -------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Getting Started | [001_getting_started](000_getting_started/001_getting_started.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/main/notebooks/000_getting_started/001_getting_started.ipynb) |
 
 ## 1. Data Modules
 
-| Notebook | GitHub                                         | Colab                                                                                                                                                                                                       |
-| -------- | ---------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| BTech    | [101_btech](100_datamodules/101_btech.ipynb)   | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/development/notebooks/100_datamodules/101_btech.ipynb)  |
-| MVTec    | [102_mvtec](100_datamodules/102_mvtec.ipynb)   | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/development/notebooks/100_datamodules/102_mvtec.ipynb)  |
-| Folder   | [103_folder](100_datamodules/103_folder.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/development/notebooks/100_datamodules/103_folder.ipynb) |
+| Notebook | GitHub                                         | Colab                                                                                                                                                                                                |
+| -------- | ---------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| BTech    | [101_btech](100_datamodules/101_btech.ipynb)   | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/main/notebooks/100_datamodules/101_btech.ipynb)  |
+| MVTec    | [102_mvtec](100_datamodules/102_mvtec.ipynb)   | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/main/notebooks/100_datamodules/102_mvtec.ipynb)  |
+| Folder   | [103_folder](100_datamodules/103_folder.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/main/notebooks/100_datamodules/103_folder.ipynb) |
 
 ## 2. Models
 
-| Notebook | GitHub                                        | Colab                                                                                                                                                                                                    |
-| -------- | --------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| Model    | [201_fastflow](200_models/201_fastflow.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/development/notebooks/200_models/201_fastflow.ipynb) |
+| Notebook | GitHub                                        | Colab                                                                                                                                                                                             |
+| -------- | --------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Model    | [201_fastflow](200_models/201_fastflow.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/main/notebooks/200_models/201_fastflow.ipynb) |
 
 ## 3. Benchmarking and Hyperparameter Optimization
 
-| Notebook     | GitHub                                                      | Colab                                                                                                                                                                                                              |
-| ------------ | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| Benchmarking | [301_benchmarking](300_benchmarking/301_benchmarking.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/development/notebooks/300_benchmarking/301_benchmarking.ipynb) |
+| Notebook     | GitHub                                                      | Colab                                                                                                                                                                                                       |
+| ------------ | ----------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Benchmarking | [301_benchmarking](300_benchmarking/301_benchmarking.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/anomalib/blob/main/notebooks/300_benchmarking/301_benchmarking.ipynb) |
@@ -8,7 +8,7 @@ matplotlib>=3.4.3
 omegaconf>=2.1.1
 opencv-python>=4.5.3.56
 pandas>=1.1.0
-pytorch-lightning>=1.6.0
+pytorch-lightning>=1.6.0,<1.7.0
 timm==0.5.4
 torchmetrics>=0.9.0,<=0.9.1
 torchvision>=0.9.1,<=0.12.0