Welcome to DEEPSECURE, is a Python-based application designed for adversarial image generation and processing, leveraging deep learning techniques.
DEEPSECURE is a Python-based framework designed to generate adversarial examples, analyze their effects on deep learning models, and potentially evaluate model vulnerabilities. It leverages modular and customizable components such as generators, feature extractors, and data loaders to create and train adversarial scenarios.
- Adversarial Image Generation: Create adversarial examples using various generation techniques.
- Pre-trained Model Extraction: Utilize pre-trained models for feature extraction.
- Custom Data Loading: Load and preprocess datasets, such as ImageNet10, for training and evaluation.
Prerequisites:
- Python 3.8+
- Git
- Recommended: virtual environment (e.g.,
venv, Conda)
Steps:
# Clone the repository
git clone https://github.com/rigley007/DEEPSECURE.git
cd DEEPSECURE
# (Optional) Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # or venv\Scripts\activate on Windows
# Install dependencies
pip install -r requirements.txt