https://github.com/BMW-InnovationLab/BMW-Anonymization-API

This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.
https://github.com/BMW-InnovationLab/BMW-Anonymization-API

anonymization-api anonymization-technique bmw computer-vision data-anonymization deep-learning docker image-transformation inference no-code object-detection openvino privacy-enhancing-technologies privacy-protection pytorch semantic-segmentation tensorflow tensorflow-training video video-anonymization

Last synced: about 2 months ago
JSON representation

This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.

• Host: GitHub
• URL: https://github.com/BMW-InnovationLab/BMW-Anonymization-API
• Owner: BMW-InnovationLab
• License: apache-2.0
• Created: 2021-04-08T10:55:20.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2024-02-09T14:07:16.000Z (7 months ago)
• Last Synced: 2024-06-09T02:32:30.476Z (3 months ago)
• Topics: anonymization-api, anonymization-technique, bmw, computer-vision, data-anonymization, deep-learning, docker, image-transformation, inference, no-code, object-detection, openvino, privacy-enhancing-technologies, privacy-protection, pytorch, semantic-segmentation, tensorflow, tensorflow-training, video, video-anonymization
• Language: Python
• Homepage:
• Size: 44.7 MB
• Stars: 176
• Watchers: 5
• Forks: 16
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-oneapi - BMW-Anonymization-API - The BMW Anonymization API is a privacy tool designed to obfuscate sensitive information in images and videos to preserve individual anonymity. Its features include agnostic localization techniques, modular sensitive information training, scalable anonymization techniques, and compatibility with deep learning models (Table of Contents / AI - Frameworks and Toolkits)