Real-time Face Detection & Recognition App Enhancement
Budget: €250 – €750 EUR
I'm seeking a talented developer with a robust background in artificial intelligence and facial recognition to improve a real-time Face detection, recognition, and liveness check App.
The app, currently running on a Raspberry Pi system, utilizes:
- Face Detection: (mediapipe)
- Face Recognition: (Facenet)
- Liveness Detection: (minnetV1, minnetV2)
- Storing detected face embeddings in an sqlite3 database
The Application is written in Python 3.11
The primary goal is to replace the existing models in the app with YuNet + (FaceNet512 or Sface) while implementing frame skipping to achieve a balance between speed and accuracy.
Key aspects of the project include:
- Prioritizing a balance between speed and accuracy
- Utilizing Sface or FaceNet512 as the primary face recognition model
- Ensuring high accuracy in liveness detection
Freelancers with prior experience in developing similar applications and working with these specific models will be highly preferred. Any other suggestions to enhance the project's outcome are welcome.
The app, currently running on a Raspberry Pi system, utilizes:
- Face Detection: (mediapipe)
- Face Recognition: (Facenet)
- Liveness Detection: (minnetV1, minnetV2)
- Storing detected face embeddings in an sqlite3 database
The Application is written in Python 3.11
The primary goal is to replace the existing models in the app with YuNet + (FaceNet512 or Sface) while implementing frame skipping to achieve a balance between speed and accuracy.
Key aspects of the project include:
- Prioritizing a balance between speed and accuracy
- Utilizing Sface or FaceNet512 as the primary face recognition model
- Ensuring high accuracy in liveness detection
Freelancers with prior experience in developing similar applications and working with these specific models will be highly preferred. Any other suggestions to enhance the project's outcome are welcome.