Update project title and repo links (#1)

* Update project title and repo links

* Update titles and headings w/ (tm)

CONTRIBUTING.md

@@ -1,8 +1,8 @@
-# Contributing to OpenVINO-XAI
+# Contributing to OpenVINO™ Explainable AI Toolkit
 
 ## Code style
 
-Changes to OpenVINO-XAI Python code should conform to [Python Style Guide](./docs/styleguide/PyGuide.md)
+Changes to OpenVINO XAI Python code should conform to [Python Style Guide](./docs/styleguide/PyGuide.md)
 
 Basic code style and static checks are enforced using a `pre-commit` Github action.
 The exact checks that are run are described in the corresponding [config file](./.pre-commit-config.yaml).

GETTING_STARTED.ipynb

@@ -9,9 +9,9 @@
    },
    "source": [
     "## <a id='toc1_1_1_'></a>[*** OUTDATED ***](#toc0_)\n",
-    "### <a id='toc1_1_1_'></a>[OpenVINO-XAI library getting started](#toc0_)\n",
+    "### <a id='toc1_1_1_'></a>[OpenVINO™ Explainable AI Toolkit Getting Started](#toc0_)\n",
     "\n",
-    "**OpenVINO-XAI** library is a tool that provides a suite of Explainable AI (XAI) algorithms for explanation of\n",
+    "**OpenVINO™ Explainable AI (XAI) Toolkit** provides a suite of XAI algorithms for visual explanation of\n",
     "[OpenVINO™](https://github.com/openvinotoolkit/openvino) Intermediate Representation (IR) models.\n",
     "\n",
     "It depicts a heatmap with areas of interest for neural network (classification or detection) where it focuses before making a desicion.\n",
@@ -40,7 +40,7 @@
    },
    "source": [
     "**Table of contents**<a id='toc0_'></a>    \n",
-    "- [OpenVINO-XAI library getting started](#toc1_1_1_)    \n",
+    "- [OpenVINO™ Explainable AI Toolkit Getting Started](#toc1_1_1_)    \n",
     "    - [Installation](#toc1_1_2_)    \n",
     "    - [Preparation](#toc1_1_3_)    \n",
     "    - [Model preparation](#toc1_1_4_)    \n",
@@ -1172,4 +1172,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

README.md

@@ -1,11 +1,11 @@
-# OpenVINO-XAI
+# OpenVINO™ Explainable AI Toolkit
 
-OpenVINO-XAI provides a suite of eXplainable AI (XAI) algorithms for explanation of
-[OpenVINO™](https://github.com/openvinotoolkit/openvino) Intermediate Representation (IR).
+**OpenVINO™ Explainable AI (XAI) Toolkit** provides a suite of XAI algorithms for visual explanation of
+[OpenVINO™](https://github.com/openvinotoolkit/openvino) Intermediate Representation (IR) models.
 
 ## Documentation
 
-OpenVINO-XAI API documentation can be found [here](https://curly-couscous-ovjvm29.pages.github.io/).
+OpenVINO XAI API documentation can be found [here](https://curly-couscous-ovjvm29.pages.github.io/).
 
 ## Installation
 

docs/Usage.md

@@ -1,12 +1,12 @@
-# OpenVINO-XAI (OVXAI) usage
+# OpenVINO™ Explainable AI Toolkit Usage Guide
 
-OpenVINO-XAI provides a suite of eXplainable AI (XAI) algorithms for explanation of OpenVINO™ Intermediate Representation (IR).
+**OpenVINO™ Explainable AI (XAI) Toolkit** provides a suite of XAI algorithms for visual explanation of OpenVINO™ Intermediate Representation (IR) models.
 Model explanation helps to identify the parts of the input that are responsible for the model's prediction,
 which is useful for analyzing model's performance.
 
 Current tutorial is primarily for classification CNNs.
 
-OpenVINO-XAI API documentation can be found [here](https://curly-couscous-ovjvm29.pages.github.io/).
+OpenVINO XAI API documentation can be found [here](https://curly-couscous-ovjvm29.pages.github.io/).
 
 Content:
 

docs/styleguide/PyGuide.md

@@ -2,7 +2,7 @@
 
 ## 1 Introduction
 
-This document gives coding conventions for the Python code comprising [OpenVINO-XAI (OV-XAI)](../../README.md).
+This document gives coding conventions for the Python code comprising [OpenVINO™ Explainable AI Toolkit](../../README.md).
 
 This style guide supplements the [PEP 8 -- Style Guide for Python Code](https://www.python.org/dev/peps/pep-0008/)
 with a list of *dos and don'ts* for Python code. If no guidelines were found in this style guide then

notebooks/xai_classification/README.md

@@ -1,14 +1,14 @@
 <!-- markdownlint-disable -->
 TODO (Galina): enable
 
-# OpenVINO-XAI: Classification explanation
+# OpenVINO™ Explainable AI Toolkit: Classification Explanation
 
-This notebook shows an example how to use OpenVINO-XAI.
-
-**OpenVINO-XAI** library is a tool that provides a suite of Explainable AI (XAI) algorithms for explanation of
+**OpenVINO™ Explainable AI (XAI) Toolkit** provides a suite of XAI algorithms for visual explanation of
 [OpenVINO™](https://github.com/openvinotoolkit/openvino) Intermediate Representation (IR) models.
 
-It depicts a heatmap with areas of interest where neural network (classification or detection) focuses before making a decision. 
+This notebook shows an example how to use OpenVINO XAI.
+
+It depicts a heatmap with areas of interest where neural network (classification or detection) focuses before making a decision.
 
 Example: Saliency map for `person` class for EfficientV2 classification model:
 
@@ -19,9 +19,9 @@ Example: Saliency map for `person` class for EfficientV2 classification model:
 The tutorial consists of the following steps:
 
 - Update IR model with XAI branch to use it in own pipelines
-- Create CustomInferrer to infer model and receive outputs 
+- Create CustomInferrer to infer model and receive outputs
 - Explain model with White-Box Explainer (updating original IR)
-- Explain model with the Black-Box explainer 
+- Explain model with the Black-Box explainer
 
 ## Installation Instructions
 
@@ -39,4 +39,4 @@ pip install torch==1.13.1 --extra-index-url https://download.pytorch.org/whl/cpu
 # Package installation
 %pip install -q ..
 
-```
+```

notebooks/xai_classification/xai_classification.ipynb

@@ -4,18 +4,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# <a id='toc1_'></a>[OpenVINO-XAI: Classification explanation](#toc0_)"
+    "# <a id='toc1_'></a>[OpenVINO™ Explainable AI Toolkit: Classification Explanation](#toc0_)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This notebook shows an example how to use OpenVINO-XAI.\n",
-    "\n",
-    "**OpenVINO-XAI** library is a tool that provides a suite of Explainable AI (XAI) algorithms for explanation of\n",
+    "**OpenVINO™ Explainable AI (XAI) Toolkit** provides a suite of XAI algorithms for visual explanation of\n",
     "[OpenVINO™](https://github.com/openvinotoolkit/openvino) Intermediate Representation (IR) models.\n",
     "\n",
+    "This notebook shows an example how to use OpenVINO XAI.\n",
+    "\n",
     "It depicts a heatmap with areas of interest where neural network (classification or detection) focuses before making a decision. "
    ]
   },
@@ -24,7 +24,7 @@
    "metadata": {},
    "source": [
     "**Table of contents**<a id='toc0_'></a>    \n",
-    "- [OpenVINO-XAI: Classification explanation](#toc1_)    \n",
+    "- [OpenVINO™ Explainable AI Toolkit: Classification Explanation](#toc1_)    \n",
     "- [Imports](#toc2_)    \n",
     "- [Get IR model](#toc3_)    \n",
     "  - [Download and convert timm models (Optional)](#toc3_1_)    \n",
@@ -582,7 +582,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "For more convenient saliency map processing, you can use OpenVINO-XAI API:\n",
+    "For more convenient saliency map processing, you can use OpenVINO XAI API:\n",
     "- To return saliency maps only for predicted classes using `TargetExplainGroup.PREDICTIONS`\n",
     "- To return predictions and its confidence with `explanation.prediction`\n",
     "- To apply built-in postprocessing with overlay/resize using `PostProcessParameters`\n",

notebooks/xai_saliency_map_interpretation/README.md

@@ -1,14 +1,14 @@
 <!-- markdownlint-disable -->
 TODO (Galina): enable
 
-# OpenVINO-XAI: Classification explanation
+# OpenVINO™ Explainable AI (XAI) Toolkit: Classification Explanation
 
-This notebook shows an example how to use OpenVINO-XAI.
-
-**OpenVINO-XAI** library is a tool that provides a suite of Explainable AI (XAI) algorithms for explanation of
+**OpenVINO™ Explainable AI (XAI) Toolkit** provides a suite of XAI algorithms for visual explanation of
 [OpenVINO™](https://github.com/openvinotoolkit/openvino) Intermediate Representation (IR) models.
 
-It depicts a heatmap with areas of interest where neural network (classification or detection) focuses before making a desicion. 
+This notebook shows an example how to use OpenVINO XAI.
+
+It depicts a heatmap with areas of interest where neural network (classification or detection) focuses before making a desicion.
 
 Example: Saliency map for `person` class for EfficientV2 classification model:
 
@@ -20,12 +20,12 @@ The tutorial consists of the following steps:
 
 - Update IR model with XAI branch to receive saliency maps
 - Create CustomInferrer to infer model and receive outputs
-- Explain model 
+- Explain model
 - Adding ImageNet label names to add them in saliency maps
 - Saliency map examples in different usecases and its interpretations
     - True Positive High confidence
-    - True Positive Low confidence   
-    - False Positive High confidence  
+    - True Positive Low confidence
+    - False Positive High confidence
     - Two mixed predictions
 
 
@@ -41,4 +41,4 @@ The tutorial consists of the following steps:
 # Package installation
 %pip install -q ../..
 
-```
+```

notebooks/xai_saliency_map_interpretation/xai_saliency_map_interpretation.ipynb

@@ -4,18 +4,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# <a id='toc1_'></a>[OpenVINO-XAI: Classification explanation](#toc0_)\n"
+    "# <a id='toc1_'></a>[OpenVINO™ Explainable AI Toolkit: Classification Explanation](#toc0_)\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This notebook shows an example of how to use OpenVINO-XAI library and interpret the resulting saliency maps. \n",
-    "\n",
-    "**OpenVINO-XAI** library is a tool that provides a suite of Explainable AI (XAI) algorithms for explanation of\n",
+    "**OpenVINO™ Explainable AI (XAI) Toolkit** provides a suite of XAI algorithms for visual explanation of\n",
     "[OpenVINO™](https://github.com/openvinotoolkit/openvino) Intermediate Representation (IR) models.\n",
     "\n",
+    "This notebook shows an example of how to use OpenVINO XAI Toolkit and interpret the resulting saliency maps. \n",
+    "\n",
     "It depicts a heatmap with areas of interest where neural network (classification or detection) focuses before making a desicion. \n",
     "\n",
     "This notebook shows which saliency map are generated in different scenarios, in case of correct and confident prediction, in case of low-confident prediction and in case of mixed up classes. "
@@ -26,7 +26,7 @@
    "metadata": {},
    "source": [
     "**Table of contents**<a id='toc0_'></a>    \n",
-    "- [OpenVINO-XAI: Classification explanation](#toc1_)    \n",
+    "- [OpenVINO™ Explainable AI Toolkit: Classification Explanation](#toc1_)    \n",
     "- [Imports](#toc2_)    \n",
     "- [Download dataset](#toc3_)    \n",
     "- [Prepare IR model](#toc4_)    \n",
@@ -192,7 +192,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "To receive explanations (saliency maps) from the model, first we need to insert the XAI branch. This will create an extra output for model, a low resolution saliency map. It later can be postprocessed, resized and applied over an original image, using `PostProcessor` component of the `OpenVINO-XAI` library."
+    "To receive explanations (saliency maps) from the model, first we need to insert the XAI branch. This will create an extra output for model, a low resolution saliency map. It later can be postprocessed, resized and applied over an original image, using `PostProcessor` component of the `OpenVINO XAI` Toolkit."
    ]
   },
   {

pyproject.toml

@@ -21,13 +21,14 @@ authors = [
 maintainers = [
   {name = "Intel(R) Corporation"},
 ]
-description = "OpenVINO XAI: a toolbox for explaining models in OpenVINO format"
+description = "OpenVINO™ Explainable AI (XAI) Toolkit: Visual Explanation for OpenVINO Models"
 readme = "README.md"
 license = {file = "LICENSE"}
-keywords = ["pytorch", "cnn", "transformer", "xai", "black-box"]
+keywords = ["openvino-toolkit", "explainable-ai", "xai", "cnn", "transformer", "black-box", "white-box"]
 classifiers = [
   "License :: OSI Approved :: MIT Apache Software License",
-  "Programming Language :: Python :: 3.9"
+  "Programming Language :: Python :: 3.10",
+  "Programming Language :: Python :: 3.11",
 ]
 
 [project.optional-dependencies]
@@ -43,9 +44,9 @@ dev_timm = [
 ]
 
 [project.urls]
-Homepage = "https://github.com/intel-sandbox/openvino_xai"
+Homepage = "https://github.com/openvinotoolkit/openvino_xai"
 Documentation = "https://curly-couscous-ovjvm29.pages.github.io/"
-Repository = "https://github.com/intel-sandbox/openvino_xai.git"
+Repository = "https://github.com/openvinotoolkit/openvino_xai.git"
 
 [tool.setuptools.packages.find]
 include = ["openvino_xai*"]