Silhouettefree
Silhouettefree is an open-source project focused on privacy-preserving image recognition and analysis. The initiative aims to develop tools that allow users to analyze images without relying on traditional methods that require uploading or storing sensitive visual data. By leveraging techniques such as differential privacy, federated learning, and on-device processing, Silhouettefree seeks to minimize exposure of personal or confidential information.
The project was inspired by concerns over privacy violations in cloud-based image analysis services, where uploaded
Key components of Silhouettefree include:
- **On-device processing**: Models are executed locally, preventing the need to transmit raw images to external servers.
- **Differential privacy**: Techniques are applied to obscure individual data points within datasets, reducing the risk of
- **Federated learning**: Multiple devices collaboratively train models without sharing their raw data, enabling collective learning while
The project is community-driven, with contributions from developers, researchers, and privacy advocates. It provides documentation, code
For those interested in exploring privacy-focused alternatives to traditional image recognition systems, Silhouettefree offers a promising