├── maintainers.md ├── contributing.md ├── CODE_OF_CONDUCT.md ├── LICENSE └── README.md /maintainers.md: -------------------------------------------------------------------------------- 1 | # Awesome OpenVINO Repository Maintainers 2 | 3 | Thank you for your interest in contributing to the Awesome OpenVINO Repository! The following individuals are the maintainers responsible for reviewing and managing contributions to this repository. 4 | 5 | ## Maintainers 6 | 7 | ### [Dmitriy Pastushenkov](https://github.com/DimaPastushenkov) 8 | - GitHub: [@DimaPastushenkov](https://github.com/DimaPastushenkov) 9 | - Email: dmitriy.pastushenkov@intel.com 10 | 11 | ### [Pooja Baraskar](https://github.com/Pooja-B) 12 | - GitHub: [@Pooja-B](https://github.com/Pooja-B) 13 | - Email: pooja.baraskar@intel.com 14 | 15 | ## How to Reach Us 16 | 17 | If you have questions, concerns, or need assistance, you can reach out to the maintainers through the following channels: 18 | 19 | - **GitHub Issues:** [Link to Issues](issues) 20 | - **Email:** [pooja.baraskar@intel.com](mailto:pooja.baraskar@intel.com) [dmitriy.pastushenkov@intel.com](mailto:dmitriy.pastushenkov@intel.com) 21 | 22 | 23 | ## Contribution Guidelines 24 | 25 | Before contributing, please read the [Contribution Guidelines](contributing.md) for important information on the contribution process. 26 | 27 | Thank you for your interest in making the Awesome OpenVINO Repository even more awesome! 28 | -------------------------------------------------------------------------------- /contributing.md: -------------------------------------------------------------------------------- 1 | The Awesome OpenVINO is a curated list of 'awesome' OpenVINO based AI projects. This repository is your gateway to a curated collection of resources, tools, and projects that leverage the capabilities of OpenVINO to unlock the full potential of your AI applications. 2 | 3 | # Contributing to the Awesome OpenVINO Repository 4 | 5 | Thank you for considering contributing to the Awesome OpenVINO Repository. By contributing, you help build a vibrant community and provide valuable resources to fellow developers, researchers, and enthusiasts interested in OpenVINO. 6 | 7 | ## How to Contribute 8 | 9 | ### 1. Fork the Repository 10 | 11 | Start by forking the Awesome OpenVINO Repository to your GitHub account. This can be done by clicking the "Fork" button at the top right of the repository's page. 12 | 13 | ### 2. Clone your Fork 14 | 15 | Clone the repository from your account to your local machine: 16 | 17 | ### 3. Create a Branch 18 | Create a new branch to work on your contribution. 19 | 20 | 21 | ### 4. Make Changes 22 | Add your contributions to the repository. This could include adding new resources, updating existing content, or fixing issues. 23 | 24 | ### 5. Commit Changes 25 | Commit your changes with a descriptive commit message: 26 | 27 | 28 | ### 6. Push Changes 29 | Push your changes to your fork 30 | 31 | ### 7. Create a Pull Request 32 | Navigate to your fork on GitHub and create a new Pull Request against the README.md and in the PR comment use this format: 33 | 34 | Name of the project: 35 | 36 | Maintainer: 37 | 38 | Description of the project: 39 | 40 | What version of OpenVINO it supports (if applicable): 41 | 42 | Link to the github/gitlab/other: 43 | 44 | License: 45 | 46 | ## Contribution Guidelines 47 | 48 | To maintain the quality and consistency of the Awesome OpenVINO Repository, please adhere to the following guidelines: 49 | 50 | - Ensure that your contributions are relevant to OpenVINO and aligned with the purpose of the repository. 51 | - Follow a consistent formatting style to keep the repository organized. 52 | - Include a brief description with each contribution to provide context for users. 53 | - Verify that links are working and resources are up-to-date. 54 | 55 | 56 | ## What happens after I submit? 57 | 58 | Over a period of 1-3 days, we will evaluate—we might give feedback on the PR asking for additional information. Once that happens, we'll merge your changes. That's it! 59 | 60 | 61 | Thank you for contributing to the Awesome OpenVINO Repository and being a part of the OpenVINO community! 62 | -------------------------------------------------------------------------------- /CODE_OF_CONDUCT.md: -------------------------------------------------------------------------------- 1 | # Contributor Covenant Code of Conduct 2 | 3 | ## Our Pledge 4 | 5 | In the interest of fostering an open and welcoming environment, we as 6 | contributors and maintainers pledge to making participation in our project and 7 | our community a harassment-free experience for everyone, regardless of age, body 8 | size, disability, ethnicity, gender identity and expression, level of experience, 9 | nationality, personal appearance, race, religion, or sexual identity and 10 | orientation. 11 | 12 | ## Our Standards 13 | 14 | Examples of behavior that contributes to creating a positive environment 15 | include: 16 | 17 | * Using welcoming and inclusive language 18 | * Being respectful of differing viewpoints and experiences 19 | * Gracefully accepting constructive criticism 20 | * Focusing on what is best for the community 21 | * Showing empathy towards other community members 22 | 23 | Examples of unacceptable behavior by participants include: 24 | 25 | * The use of sexualized language or imagery and unwelcome sexual attention or 26 | advances 27 | * Trolling, insulting/derogatory comments, and personal or political attacks 28 | * Public or private harassment 29 | * Publishing others' private information, such as physical or electronic 30 | address, without explicit permission 31 | * Other conduct that could reasonably be considered inappropriate in a 32 | professional setting 33 | 34 | ## Our Responsibilities 35 | 36 | Project maintainers are responsible for clarifying the standards of acceptable 37 | behavior and are expected to take appropriate and fair corrective action in 38 | response to any instances of unacceptable behavior. 39 | 40 | Project maintainers have the right and responsibility to remove, edit, or 41 | reject comments, commits, code, wiki edits, issues, and other contributions 42 | that are not aligned to this Code of Conduct, or to ban temporarily or 43 | permanently any contributor for other behaviors that they deem inappropriate, 44 | threatening, offensive, or harmful. 45 | 46 | ## Scope 47 | 48 | This Code of Conduct applies both within project spaces and in public spaces 49 | when an individual is representing the project or its community. Examples of 50 | representing a project or community include using an official project e-mail 51 | address, posting via an official social media account, or acting as an appointed 52 | representative at an online or offline event. Representation of a project may be 53 | further defined and clarified by project maintainers. 54 | 55 | ## Enforcement 56 | 57 | Instances of abusive, harassing, or otherwise unacceptable behavior may be 58 | reported by contacting the project team at pooja.baraskar@intel.com. All 59 | complaints will be reviewed and investigated and will result in a response that 60 | is deemed necessary and appropriate to the circumstances. The project team is 61 | obligated to maintain confidentiality with regard to the reporter of an incident. 62 | Further details of specific enforcement policies may be posted separately. 63 | 64 | Project maintainers who do not follow or enforce the Code of Conduct in good 65 | faith may face temporary or permanent repercussions as determined by other 66 | members of the project's leadership. 67 | 68 | ## Attribution 69 | 70 | This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, 71 | available at [https://contributor-covenant.org/version/1/4][version] 72 | 73 | [homepage]: https://contributor-covenant.org 74 | [version]: https://contributor-covenant.org/version/1/4/ 75 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. Definitions. 8 | 9 | "License" shall mean the terms and conditions for use, reproduction, 10 | and distribution as defined by Sections 1 through 9 of this document. 11 | 12 | "Licensor" shall mean the copyright owner or entity authorized by 13 | the copyright owner that is granting the License. 14 | 15 | "Legal Entity" shall mean the union of the acting entity and all 16 | other entities that control, are controlled by, or are under common 17 | control with that entity. For the purposes of this definition, 18 | "control" means (i) the power, direct or indirect, to cause the 19 | direction or management of such entity, whether by contract or 20 | otherwise, or (ii) ownership of fifty percent (50%) or more of the 21 | outstanding shares, or (iii) beneficial ownership of such entity. 22 | 23 | "You" (or "Your") shall mean an individual or Legal Entity 24 | exercising permissions granted by this License. 25 | 26 | "Source" form shall mean the preferred form for making modifications, 27 | including but not limited to software source code, documentation 28 | source, and configuration files. 29 | 30 | "Object" form shall mean any form resulting from mechanical 31 | transformation or translation of a Source form, including but 32 | not limited to compiled object code, generated documentation, 33 | and conversions to other media types. 34 | 35 | "Work" shall mean the work of authorship, whether in Source or 36 | Object form, made available under the License, as indicated by a 37 | copyright notice that is included in or attached to the work 38 | (an example is provided in the Appendix below). 39 | 40 | "Derivative Works" shall mean any work, whether in Source or Object 41 | form, that is based on (or derived from) the Work and for which the 42 | editorial revisions, annotations, elaborations, or other modifications 43 | represent, as a whole, an original work of authorship. For the purposes 44 | of this License, Derivative Works shall not include works that remain 45 | separable from, or merely link (or bind by name) to the interfaces of, 46 | the Work and Derivative Works thereof. 47 | 48 | "Contribution" shall mean any work of authorship, including 49 | the original version of the Work and any modifications or additions 50 | to that Work or Derivative Works thereof, that is intentionally 51 | submitted to Licensor for inclusion in the Work by the copyright owner 52 | or by an individual or Legal Entity authorized to submit on behalf of 53 | the copyright owner. For the purposes of this definition, "submitted" 54 | means any form of electronic, verbal, or written communication sent 55 | to the Licensor or its representatives, including but not limited to 56 | communication on electronic mailing lists, source code control systems, 57 | and issue tracking systems that are managed by, or on behalf of, the 58 | Licensor for the purpose of discussing and improving the Work, but 59 | excluding communication that is conspicuously marked or otherwise 60 | designated in writing by the copyright owner as "Not a Contribution." 61 | 62 | "Contributor" shall mean Licensor and any individual or Legal Entity 63 | on behalf of whom a Contribution has been received by Licensor and 64 | subsequently incorporated within the Work. 65 | 66 | 2. Grant of Copyright License. Subject to the terms and conditions of 67 | this License, each Contributor hereby grants to You a perpetual, 68 | worldwide, non-exclusive, no-charge, royalty-free, irrevocable 69 | copyright license to reproduce, prepare Derivative Works of, 70 | publicly display, publicly perform, sublicense, and distribute the 71 | Work and such Derivative Works in Source or Object form. 72 | 73 | 3. Grant of Patent License. Subject to the terms and conditions of 74 | this License, each Contributor hereby grants to You a perpetual, 75 | worldwide, non-exclusive, no-charge, royalty-free, irrevocable 76 | (except as stated in this section) patent license to make, have made, 77 | use, offer to sell, sell, import, and otherwise transfer the Work, 78 | where such license applies only to those patent claims licensable 79 | by such Contributor that are necessarily infringed by their 80 | Contribution(s) alone or by combination of their Contribution(s) 81 | with the Work to which such Contribution(s) was submitted. If You 82 | institute patent litigation against any entity (including a 83 | cross-claim or counterclaim in a lawsuit) alleging that the Work 84 | or a Contribution incorporated within the Work constitutes direct 85 | or contributory patent infringement, then any patent licenses 86 | granted to You under this License for that Work shall terminate 87 | as of the date such litigation is filed. 88 | 89 | 4. Redistribution. You may reproduce and distribute copies of the 90 | Work or Derivative Works thereof in any medium, with or without 91 | modifications, and in Source or Object form, provided that You 92 | meet the following conditions: 93 | 94 | (a) You must give any other recipients of the Work or 95 | Derivative Works a copy of this License; and 96 | 97 | (b) You must cause any modified files to carry prominent notices 98 | stating that You changed the files; and 99 | 100 | (c) You must retain, in the Source form of any Derivative Works 101 | that You distribute, all copyright, patent, trademark, and 102 | attribution notices from the Source form of the Work, 103 | excluding those notices that do not pertain to any part of 104 | the Derivative Works; and 105 | 106 | (d) If the Work includes a "NOTICE" text file as part of its 107 | distribution, then any Derivative Works that You distribute must 108 | include a readable copy of the attribution notices contained 109 | within such NOTICE file, excluding those notices that do not 110 | pertain to any part of the Derivative Works, in at least one 111 | of the following places: within a NOTICE text file distributed 112 | as part of the Derivative Works; within the Source form or 113 | documentation, if provided along with the Derivative Works; or, 114 | within a display generated by the Derivative Works, if and 115 | wherever such third-party notices normally appear. The contents 116 | of the NOTICE file are for informational purposes only and 117 | do not modify the License. You may add Your own attribution 118 | notices within Derivative Works that You distribute, alongside 119 | or as an addendum to the NOTICE text from the Work, provided 120 | that such additional attribution notices cannot be construed 121 | as modifying the License. 122 | 123 | You may add Your own copyright statement to Your modifications and 124 | may provide additional or different license terms and conditions 125 | for use, reproduction, or distribution of Your modifications, or 126 | for any such Derivative Works as a whole, provided Your use, 127 | reproduction, and distribution of the Work otherwise complies with 128 | the conditions stated in this License. 129 | 130 | 5. Submission of Contributions. Unless You explicitly state otherwise, 131 | any Contribution intentionally submitted for inclusion in the Work 132 | by You to the Licensor shall be under the terms and conditions of 133 | this License, without any additional terms or conditions. 134 | Notwithstanding the above, nothing herein shall supersede or modify 135 | the terms of any separate license agreement you may have executed 136 | with Licensor regarding such Contributions. 137 | 138 | 6. Trademarks. This License does not grant permission to use the trade 139 | names, trademarks, service marks, or product names of the Licensor, 140 | except as required for reasonable and customary use in describing the 141 | origin of the Work and reproducing the content of the NOTICE file. 142 | 143 | 7. Disclaimer of Warranty. Unless required by applicable law or 144 | agreed to in writing, Licensor provides the Work (and each 145 | Contributor provides its Contributions) on an "AS IS" BASIS, 146 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or 147 | implied, including, without limitation, any warranties or conditions 148 | of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A 149 | PARTICULAR PURPOSE. You are solely responsible for determining the 150 | appropriateness of using or redistributing the Work and assume any 151 | risks associated with Your exercise of permissions under this License. 152 | 153 | 8. Limitation of Liability. In no event and under no legal theory, 154 | whether in tort (including negligence), contract, or otherwise, 155 | unless required by applicable law (such as deliberate and grossly 156 | negligent acts) or agreed to in writing, shall any Contributor be 157 | liable to You for damages, including any direct, indirect, special, 158 | incidental, or consequential damages of any character arising as a 159 | result of this License or out of the use or inability to use the 160 | Work (including but not limited to damages for loss of goodwill, 161 | work stoppage, computer failure or malfunction, or any and all 162 | other commercial damages or losses), even if such Contributor 163 | has been advised of the possibility of such damages. 164 | 165 | 9. Accepting Warranty or Additional Liability. While redistributing 166 | the Work or Derivative Works thereof, You may choose to offer, 167 | and charge a fee for, acceptance of support, warranty, indemnity, 168 | or other liability obligations and/or rights consistent with this 169 | License. However, in accepting such obligations, You may act only 170 | on Your own behalf and on Your sole responsibility, not on behalf 171 | of any other Contributor, and only if You agree to indemnify, 172 | defend, and hold each Contributor harmless for any liability 173 | incurred by, or claims asserted against, such Contributor by reason 174 | of your accepting any such warranty or additional liability. 175 | 176 | END OF TERMS AND CONDITIONS 177 | 178 | APPENDIX: How to apply the Apache License to your work. 179 | 180 | To apply the Apache License to your work, attach the following 181 | boilerplate notice, with the fields enclosed by brackets "[]" 182 | replaced with your own identifying information. (Don't include 183 | the brackets!) The text should be enclosed in the appropriate 184 | comment syntax for the file format. We also recommend that a 185 | file or class name and description of purpose be included on the 186 | same "printed page" as the copyright notice for easier 187 | identification within third-party archives. 188 | 189 | Copyright [yyyy] [name of copyright owner] 190 | 191 | Licensed under the Apache License, Version 2.0 (the "License"); 192 | you may not use this file except in compliance with the License. 193 | You may obtain a copy of the License at 194 | 195 | http://www.apache.org/licenses/LICENSE-2.0 196 | 197 | Unless required by applicable law or agreed to in writing, software 198 | distributed under the License is distributed on an "AS IS" BASIS, 199 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 200 | See the License for the specific language governing permissions and 201 | limitations under the License. 202 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Awesome OpenVINO ![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg) 2 | 3 | A curated list of OpenVINO based AI projects. The most exciting community projects based on OpenVINO are highlighted here. Explore a rich assortment of OpenVINO-based projects, libraries, and tutorials that cover a wide range of topics, from model optimization and deployment to real-world applications in various industries. 4 | 5 | This repository is a collaborative effort, continuously updated to provide you with the latest and most valuable resources for maximizing the potential of OpenVINO in your projects. If you want your project to appear in this list, please create a Pull Request or contact @DimaPastushenkov. 6 | Inspired by [Awesome oneAPI](https://github.com/oneapi-community/awesome-oneapi) 7 | 8 | If your project is featured in this Awesome OpenVINO list, you are welcome to use the 'Mentioned in Awesome' badge on your project's repository. [![Mentioned in Awesome OpenVINO](https://awesome.re/mentioned-badge-flat.svg)](https://github.com/openvinotoolkit/awesome-openvino) 9 | 10 | 11 | ## What is OpenVINO 12 | OpenVINO™ is an open-source toolkit for AI inference optimization and deployment. 13 | * Enhances deep learning performance in computer vision, automatic speech recognition, natural language processing, and other common tasks. 14 | * Utilize models trained with popular frameworks such as TensorFlow and PyTorch while efficiently reducing resource demands. 15 | * Deploy seamlessly across a spectrum of Intel® platforms, spanning from edge to cloud. 16 | 17 | 18 | ## Further resources: 19 | 20 | * OpenVINO [GitHub repo](https://github.com/openvinotoolkit/openvino). 21 | 22 | * To download OpenVINO toolkit, go [here](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/overview.html). 23 | 24 | * A collection of ready-to-run Jupyter notebooks for learning and experimenting with the OpenVINO™ toolkit- [OpenVINO Notebooks](https://github.com/openvinotoolkit/openvino_notebooks). 25 | 26 | 27 | ## Table of content 28 | 1. [Generative AI](#Generative-AI) 29 | 2. [Frameworks](#Frameworks) 30 | 3. [AI Computer Vision](#AI-Computer-Vision) 31 | 4. [AI Audio](#AI-Audio) 32 | 5. [OpenVINO API extentions](#OpenVINO-API-extentions) 33 | 6. [Natural Language Processing](#Natural-Language-Processing) 34 | 7. [Multimodal projects](#Multimodal-projects) 35 | 8. [Miscellaneous](#Miscellaneous) 36 | 9. [Educational](#Educational) 37 | 38 | 39 | ### Generative AI 40 | * [MED-LLM-BR-OpenVINO](https://github.com/cabelo/MED-LLM-BR-openvino) - These models were specially developed for the clinical context in Brazilian Portuguese, proving to be efficient in generating synthetic clinical data. The models are essential not only for direct applications in healthcare, but also for training larger models, overcoming the difficulty in accessing patient record data. 41 | * [Stable Diffusion web UI](https://github.com/openvinotoolkit/stable-diffusion-webui/) - This is a repository for a browser interface based on Gradio library for Stable Diffusion 42 | * [stable_diffusion.openvino](https://github.com/bes-dev/stable_diffusion.openvino) - This GitHub project provides an implementation of text-to-image generation using stable diffusion on Intel CPU or GPU. It requires Python 3.9.0 and is compatible with OpenVINO. 43 | * [Fast SD](https://github.com/rupeshs/fastsdcpu) - FastSD CPU is a faster version of Stable Diffusion on CPU. Based on Latent Consistency Models and Adversarial Diffusion Distillation.[Read blog post about Fast Stable Diffusion on CPU using FastSD and OpenVINO.](https://nolowiz.com/fast-stable-diffusion-on-cpu-using-fastsd-cpu-and-openvino/) 44 | Follow the step-by-step guide to seamlessly integrate [ComfyUI with FastSD and OpenVINO](https://nolowiz.com/how-to-use-comfyui-with-fastsdcpu-and-openvino/). 45 | * [OpenVINO™ AI Plugins for GIMP](https://github.com/intel/openvino-ai-plugins-gimp) - Provides a set of OpenVINO based plugins that add AI features to GIMP (GNU IMAGE 46 | MANIPULATION PROGRAM) 47 | * [OpenVINO Code - VSCode extension for AI code completion with OpenVINO](https://github.com/openvinotoolkit/openvino_contrib/tree/master/modules/openvino_code) - VSCode extension for helping developers writing code with AI code assistant. 48 | * [Enhancing Customer Service with Real-Time Sentiment Analysis: Leveraging LLMs and OpenVINO for Instant Emotional Insights](https://github.com/samontab/llm_sentiment) - The integration of LLMs with sentiment analysis models, further optimised by OpenVINO. 49 | * [OV_SD_CPP](https://github.com/yangsu2022/OV_SD_CPP) - The pure C++ text-to-image pipeline, driven by the OpenVINO native API for Stable Diffusion v1.5 with LMS Discrete Scheduler. 50 | * [QuickStyle](https://github.com/Y-T-G/QuickStyle) - A simple stylizing app utilizing OpenVINO to stylize common objects in images. 51 | * [QuickPainter](https://github.com/Y-T-G/QuickPainter) - A simple inpainting app utilizing OpenVINO to remove common objects from images. 52 | * [BlurAnything](https://github.com/Y-T-G/Blur-Anything) - An adaptation of the excellent Track Anything project which is in turn based on Meta's Segment Anything and XMem. 53 | * [Stable Diffusion 2.1 on Intel ARC](https://github.com/jfsunx/OVSD21) - A simple and easy-to-use demo to run Stable Diffusion 2.1 for Intel ARC graphics card based on OpenVINO. 54 | * [AI Video Builder](https://github.com/jediknight813/ai_video_builder) - Make videos with AI images from YouTube videos. 55 | * [LocalAI](https://github.com/mudler/LocalAI) - LocalAI is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. 56 | * [AI structured data Extraction](https://github.com/fabiomatricardi/NuExtract-1.5-openvino) - A streamlit interface with NuExtract-1.5-tiny and openvino-genai to extract data from plain text into structured custom json formats. The Repo also gives a small tutorial on how to convert NuExtract-1.5-tiny into OpenVINO IR format. 57 | * [StableLM-3B Chatbot](https://github.com/fabiomatricardi/OpenVINO-StableLM-3B-streamlit) - A streamlit CHATBOT interface with stablelm-zephyr-3b quantized in 4bit and optimum-intel. The Interface has a kind text streaming effect, and the number of turns are handled to not exceed the context window. The Model used is published on Hugging Face Hub and was created with the free HF Space hosting the [NCCF-quantization tool](https://huggingface.co/spaces/OpenVINO/nncf-quantization). 58 | * [Gemma2-2b AI Chat App](https://github.com/fabiomatricardi/OpenVINO-Gemma2B-streamlit) - A beautiful Chat Interface, with interactive tuning parameters, powered by Optimum-Intel[openvino], Streamlit and the small but powerful Gemma2-2b-instruct model by Google. The model is an int4 quantized version, hosted on Hugging Face Hub. 59 | * [LaMini Power](https://github.com/fabiomatricardi/openvino-Lamini) - An experimental text based chat interface in the terminal running the [LaMini-Flan-T5-248M](https://github.com/mbzuai-nlp/lamini-lm/) . This is a breakthrough made possible by openvino, because encoder-decoder model could not be quantized. The LaMini model family is a highly curated herd of very small models achieving strong accuracy even with only 512 tokens of context length. 60 | * [OpenVINO OpenAI API](https://pypi.org/project/openvino-openai-api/) - An OpenAI-compatible API server powered by OpenVINO GenAI for efficient inference on Intel hardware. OpenAI API compatibility for easy integration with existing applications, Powered by OpenVINO for optimized inference on Intel CPUs and GPUs, Support for both streaming and non-streaming responses, Simple command-line interface for launching the server. Easy installation with `pip install openvino-openai-api`. The project is created with AI coding assistance. You can read the journey and steps in the following 3 articles: [part 1](https://pub.towardsai.net/i-created-an-openai-api-server-because-there-wasnt-one-749a33ea90e0?sk=616682e2bec5f1194295a17cc0bb7f52), [part 2](https://pub.towardsai.net/i-created-an-ai-server-with-python-and-5-amazing-features-part-2-bde233681e4e?sk=c7e01ab57e7809388720d17855b88217) and [part 3](https://pub.towardsai.net/openvino-genai-api-server-from-ai-coding-to-pip-package-part-3-da7ab34a34e4?sk=3e98fc5ce1da18dd38d2124ec1603235) 61 | 62 | ### Frameworks 63 | * [Keras 3](https://github.com/keras-team/keras) - Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, PyTorch, NumPy and OpenVINO. User can switch on OpenVINO backend for models inference using Keras API. 64 | 65 | ### AI Computer Vision 66 | 67 | * [VisionGuard](https://github.com/inbasperu/VisionGuard) - A desktop application designed for AI PCs to combat eye strain through real-time gaze tracking, developed during GSoC 2024 under the OpenVINO Toolkit. Built on OpenVINO's gaze estimation demo, VisionGuard offers customizable break reminders, screen time analytics, and multi-device support (CPU/GPU/NPU). It features an intuitive UI with system tray integration, leveraging OpenVINO, Qt, and OpenCV for efficient, privacy-focused local processing. 68 | 69 | * [Visioncom](https://github.com/cabelo/visioncom) Visioncom is based on open_model_zoo project demo, the assisted communication system employs advanced computer vision technologies, using the OpenCV and OpenVINO libraries, to provide an interactive solution for patients with Amyotrophic Lateral Sclerosis (ALS). 70 | * [BMW-IntelOpenVINO-Detection-Inference-API](https://github.com/BMW-InnovationLab/BMW-IntelOpenVINO-Detection-Inference-API) - This is a repository for an object detection inference API using OpenVINO, supporting both Windows and Linux operating systems 71 | * [yolov5_export_cpu](https://github.com/SamSamhuns/yolov5_export_cpu) - The project provides documentation on exporting YOLOv5 models for fast CPU inference using Intel's OpenVINO framework 72 | * [LidarObjectDetection-PointPillars](https://github.com/oneapi-src/oneAPI-samples/tree/master/AI-and-Analytics/End-to-end-Workloads/LidarObjectDetection-PointPillars) (C++ based, requires AI toolkit and OpenVINO). demonstrates how to perform 3D object detection and classification using input data (point cloud) from a LIDAR sensor. 73 | * [Image Processing with OpenVINO](https://github.com/AbhiLegend/Image-Processing-with-OpenVINO) 74 | * [Implementing GAN with OpenVINO](https://github.com/AbhiLegend/GanOpenVINO) 75 | * [RapidOCR](https://github.com/RapidAI/RapidOCR) 76 | * [Pedestrian fall detection](https://github.com/guojin-yan/OpenVINO-CSharp-API/tree/csharp3.0/tutorial_examples/PP-Human_Fall_Detection) - Pedestrian fall detection. Deploying PP-Human based on OpenVINO C # API 77 | * [OpenVINO Tennis Posture](https://github.com/salvino72/openvino-Tennis-Posture/) - Deciphering Tennis Posture with Artificial Intelligence 78 | * [Cigarette Detection](https://github.com/Leviathanlzx/cgr_detection) - The project begins by YOLOv8-pose detecting human body positions and extracting skeletal information from images. Based on the skeletal poses, it assesses the elbow angles and the distance between hands and mouths for each individual. If successful, the RTDETR model is employed to detect cigarettes at the mouth zone. 79 | * [FastSAM_Awesome_OpenVINO](https://github.com/zhg-SZPT/FastSAM_Awsome_Openvino) - The Fast Segment Anything Model(FastSAM) is a CNN Segment Anything Model trained by only 2% of the SA-1B dataset published by SAM authors. The FastSAM achieve a comparable performance with the SAM method at 50× higher run-time speed. 80 | * [Computer Vision Models As Service](https://github.com/mohammad-oghli/CV-Models-Service) - implements different Computer Vision Deep Learning Models as a service. 81 | * [Dance-with: Dance with your friends with the right pose!](https://github.com/bgb10/dance-with) - Dance-with corrects your dance posture using multi-person OpenPose, 2D pose estimation Deep Learning model. 82 | * [Target-Person-Tracking-System](https://github.com/simpleis6est/Target-Person-Tracking-System) - Integration of face recognition and person tracking. 83 | * [Metin2 Bot](https://github.com/Tigerly1/metin2bot) - bots for video game Metin2. 84 | * [Machine control](https://github.com/5sControl/machine-control) - industrial machine surveillance system designed to help increase efficiency of processes. 85 | * [MeetingCam](https://github.com/nengelmann/MeetingCam) - Run your AI and CV algorithms in online meetings such as Zoom, Meets or Teams! 86 | * [Virtual-Tryon](https://github.com/LZHMS/Virtual-Tryon) - Use AI to try on clothes with your pictures. 87 | * [DepthAI Experiments](https://github.com/njnrn/depthai-experiments) - A collections of projects done with DepthAI. 88 | * [Project Babble](https://github.com/SummerSigh/ProjectBabble) - Mouth tracking project designed to work with any existing VR headset. 89 | * [Group Pose](https://github.com/Michel-liu/GroupPose-Paddle) - A Simple Baseline for End-to-End Multi-person Pose Estimation. 90 | * [Frigate](https://github.com/blakeblackshear/frigate) - NVR With Realtime Object Detection for IP Cameras. 91 | * [CGD OpenVINO Demo](https://github.com/sammysun0711/CGD_OpenVINO_Demo) - Efficient Inference and Quantization of CGD for Image Retrieval. 92 | * [Risk package detection](https://github.com/AJV009/risk-package-detection) - Threat Detection and Unattended Baggage Detection with Associated Person Tracking. 93 | * [YOLOv7-Intel](https://github.com/karnikkanojia/yolov7-intel) - Object Detection For Autonomous Vehicles. 94 | * [Cerberus](https://github.com/gerardocipriano/Cerberus-Dog-Breed-Classification-and-Body-Localization-PyTorch) - Dog Breed Classification and Body Localization. 95 | * [Criminal Activity recognition](https://github.com/ayush9304/Criminal-Activity-Video-Surveillance-using-Deep-Learning) - Criminal Activity Video Surveillance. 96 | * [RapidOCR on OpenVINO GPU](https://github.com/jaggiK/rapidocr_openvinogpu) - A modified verison of RapidOCR to support OpenVINO GPU. 97 | * [Yolov9 with OpenVINO](https://github.com/ahsan-raazaa/yolov9-openvino) - C++ and python implementation of YOLOv9 using OpenVINO 98 | * [OpenVINO-Deploy](https://github.com/wxxz975/OpenVINO-Deploy) - A repository showcasing the deployment of popular object detection AI algorithms using the OpenVINO C++ API for efficient inference. 99 | * [Clip-Chinese](https://github.com/towhee-io/examples/blob/main/image/text_image_search/3_build_chinese_image_search_engine.ipynb) - Chinese image-text similarity matching tasks, leverage OpenVINO and the Towhee embedding library. 100 | 101 | 102 | 103 | ### AI Audio 104 | * [OpenVINO™ AI Plugins for Audacity®](https://github.com/intel/openvino-plugins-ai-audacity) - A set of AI-enabled effects, generators, and analyzers for Audacity® such as Music Stem Separation, Noise Suppression, Transcription, and Music Generation. 105 | * [Whisper OpenVINO](https://github.com/zhuzilin/whisper-openvino) 106 | * [Sangeet Guru](https://github.com/TABREZ-96/Sangeet_Guru) - A music generation app where users input a music style description to get custom audio tracks. 107 | 108 | ### OpenVINO API extentions 109 | * [OpenVINO™ C# API](https://github.com/guojin-yan/OpenVINO-CSharp-API) 110 | * [OpenVINO Java API](https://github.com/Hmm466/OpenVINO-Java-API) 111 | * [OpenVINO LabVIEW API](https://github.com/wangstoudamire/lv_yolov8_openvino) 112 | * [OpenVINO.net](https://github.com/sdcb/OpenVINO.NET) 113 | * [OpenVINO-rs](https://github.com/intel/openvino-rs) 114 | * [OpenVINO-GO Client](https://github.com/AbhiLegend/DrugLiphphilicty) - The end goal is to utilize a Go client to facilitate user-friendly batch processing of molecular data, interfacing with a Flask server that employs OpenVINO for optimized lipophilicity predictions and molecular visualization 115 | 116 | 117 | 118 | ### Natural Language Processing 119 | * [Japanese chatbot Youri](https://github.com/yas-sim/openvino_japanese_chatbot_youri-7b-chat) - LLM Japanese chatbot demo program using Intel OpenVINO toolkit. 120 | * [OpenVINO GPT-Neo](https://github.com/yousseb/ov-gpt-neo) - a port of GPT-Neo that uses OpenVINO. 121 | * [Resume-Based Interview Preparation Tool](https://github.com/serinryu/interviewhelper_openvino) - The Resume-Based Interview Preparation Tool is a software application designed to streamline the interview process by helping interviewers generate relevant and meaningful questions based on a candidate's resume or portfolio page. 122 | 123 | ### Multimodal projects 124 | * [Scene Explorer for kids](https://github.com/AJV009/explore-scene-w-object-detection) - Integration of a chat bot with an object detection algorithm. 125 | * [Indoor Care Chatbot](https://github.com/AJV009/indoor-care-chatbot) - An Elderly Indoor Care Chatbot with an object detection algorithm. 126 | * [SA2](https://github.com/LHBuilder/SA-Segment-Anything) - Vision-Oriented MultiModal AI. 127 | 128 | ### openSUSE 129 | * [OpenVINO Support](https://en.opensuse.org/SDB:Install_OpenVINO) This initiative generated openVINO compatibility with the openSUSE Linux platform. Because dependencies were added to tools and libraries for software development using C/C++ and other compilation directives for the programming language. 130 | 131 | ### Educational 132 | * [NTUST Edge AI 2023 Artificial Intelligence and Edge Computing Practice ](https://github.com/OmniXRI/NTUST_EdgeAI_2023) - Educational meterials about AI and Edge Computing Practice GNU IMAGE 133 | MANIPULATION PROGRAM 134 | 135 | ### Miscellaneous 136 | 137 | * [The Power of Florence-2 with OpenVINO & FiftyOne: Real-World Applications in Image Analysis](https://github.com/Gabriellgpc/computer-vision-dataset-maker.git) - Highlighting the Power and Flexibility of Using OpenVINO, Florence-2, and FiftyOne to Efficiently Create, Annotate, Explore, and Curate a Computer Vision Dataset. 138 | 139 | * [JAX: Artificial Intelligence for everyone.](https://github.com/cabelo/jax) - JAX (Just an Artificial Intelligence Extended) is an optimized version of the openSUSE Linux image to work with openVINO. This platform was designed to facilitate the access and development of AI applications. 140 | * [Shared Memory for AI inference](https://github.com/aiblockly/aixbroad_code_example) - Shared memory interface between OpenVINO and CODESYS. It allows to exchange variable between Control Application, written in IEC and OpenVINO Application, which performs inference 141 | * [webnn-native](https://github.com/webmachinelearning/webnn-native)- WebNN Native is an implementation of the Web Neural Network API, providing building blocks, headers, and backends for ML platforms including DirectML, OpenVINO, and XNNPACK. 142 | * [NVIDIA GPU Plugin](https://github.com/openvinotoolkit/openvino_contrib/tree/master/modules/nvidia_plugin) - allows to perform deep neural networks inference on NVIDIA GPUs using CUDA, using OpenVINO API. 143 | * [Token Merging for Stable Diffusion running with OpenVINO](https://github.com/openvinotoolkit/openvino_contrib/tree/master/modules/token_merging) - An OpenVINO adopted version of Token Merging method. 144 | * [Drug Discovery “Lipophilicity” using OpenVINO toolkit](https://github.com/AbhiLegend/DrugDisOpenVINO)- Finding Lipophilicity of peptides, proteins and molecules. 145 | * [Drug Discovery “Openshift and Pytorch” using OpenVINO toolkit]([https://github.com/AbhiLegend/DrugDisOpenVINO](https://github.com/AbhiLegend/AIDrugDiscoveryOpenVINO)-The complete Drug Discovery Pipeline using OpenVINO,IPEX,RAG on Red HAT OpenshiftAI Sandboxed environment. 146 | * [OpenVINO Quantization](https://github.com/AbhiLegend/OpenVinoQuantization)- Image Quantization Classification using STL 10 Dataset. 147 | * [who_what_benchmark](https://github.com/andreyanufr/who_what_benchmark) - Simple and quick accuracy test for compressed, quantized, pruned, distilled LLMs from [NNCF](https://github.com/openvinotoolkit/nncf), Bitsandbytes, GPTQ, and BigDL-LLM. 148 | * [OpenVINO with Docker](https://github.com/jonathanyeh0723/openvino-with-docker) - Dockerizing OpenVINO applications. 149 | * [OpenVINO AICG Samples](https://github.com/sammysun0711/OpenVINO_AIGC_Samples) - A collection of samples for NLP and Image Generation. 150 | * [OpenVINO Model Server k8s Terraform](https://github.com/dummyuser42/openvino-model-server-k8s-terraform) - Deploying Kubernetes cluster via Terraform as well as deploying and hosting a OpenVINO Model Server on it. 151 | 152 | * [Application of Vision Language Models with ROS 2](https://github.com/nilutpolkashyap/vlms_with_ros2_workshop) - Dives into vision-language models for Robotics applications using ROS 2 and Intel OpenVINO toolkit. 153 | 154 | ### Related Communities 155 | See [Awesome oneAPI](https://github.com/oneapi-community/awesome-oneapi) for leading oneAPI and SYCL projects across diverse industries. 156 | 157 | OpenVINO takes advantage of the discrete GPUs using Intel oneAPI, an open programming model for multiarchitecture programming. The [oneAPI-samples 158 | repository](https://github.com/oneapi-src/oneAPI-samples) demonstrates the performance and productivity offered by Intel oneAPI and its toolkits such as oneDNN in a multi-architecture environment. 159 | --------------------------------------------------------------------------------