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| title: HEART-Gradio | |
| emoji: 🎨 | |
| colorFrom: indigo | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 4.13.0 | |
| app_file: gradio/app.py | |
| pinned: false | |
| license: mit | |
| # Hardened Extension of the Adversarial Robustness Toolbox (HEART) | |
|  | |
| HEART is a Python extension library for Machine Learning Security that builds on the popular Adversarial Robustness algorithms within the [Adversarial Robustness Toolbox (ART)](https://github.com/Trusted-AI/adversarial-robustness-toolbox). The extension library allows the user to leverage core ART algorithms while providing additional benefits to AI Test & Evaluation (T&E) engineers. | |
| - Support for T&E of models for Department of Defense use cases | |
| - Alignment to [MAITE](https://github.com/mit-ll-ai-technology/maite) protocols for seamless T&E workflows | |
| - Essential subset of adversarial robustness methods for targeted AI security coverage | |
| - Quality assurance of model assessments in the form of metadata | |
| - In-depth support for users based on codified T&E expert experience in form of guides and examples | |
| - Front-end application for low-code users: HEART Gradio Application | |
| # Installation | |
| ### From Python Packaging Index (PyPI) | |
| To install the latest version of HEART from PyPI, run: | |
| ```shell | |
| pip install heart-library | |
| ``` | |
| ### From IBM GitHub Source | |
| To install the latest version of HEART from the [heart-library public GitHub](https://github.com/IBM/heart-library), run: | |
| ```shell | |
| git clone https://github.com/IBM/heart-library.git | |
| cd heart-library | |
| pip install . | |
| ``` | |
| ### (Optional) Development Environment via Poetry | |
| In some cases, it may be beneficial for developers to set up an environment from a reproducible source of truth. This environment is useful for developers that wish to work within a pull request or leverage the same development conditions used by HEART contributors. Please follow the instructions for installation via Poetry within the official HEART repository: | |
| - [Poetry Installation Instructions](https://github.com/IBM/heart-library/blob/main/poetry_installation.md) | |
| # Getting Started With HEART | |
| IBM has published a catalog of notebooks designed to assist developers of all skill levels with the process of getting started utilizing HEART in their AI T&E workflows. These Jupyter notebooks can be accessed within the official heart-library GitHub repository: | |
| - [HEART Jupyter Notebooks](https://github.com/IBM/heart-library/tree/main/notebooks) | |
| # HEART Modules | |
| The HEART library is organized into three primary modules: attacks, estimators, and metrics. | |
| ### heart_library.attacks | |
| > The HEART attacks module contains implementations of attack algorithms for generating adversarial examples and evaluating model robustness. | |
| ### heart_library.estimators | |
| > The HEART estimators module contains classes that wrap and extend the evaluated model to make it compatible with attacks and metrics. | |
| ### heart_library.metrics | |
| > The HEART metrics module implements industry standard, commonly-used T&E metrics for model evaluation. | |