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Facenet
Ambarella/Facenet
Facenet is a machine learning model from Ambarella. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch.
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At a glance
- Library
- pytorch
- Model type
- llama
- Access
- Public
- Created
- Dec 22, 2025
- Updated
- Sep 11, 2026
- SHA
- 67981fa8
Model card
From the Hugging Face model README
FaceNet is a deep metric learning framework for face recognition and verification that maps face images into a compact embedding space where distances directly correspond to face similarity.
Original paper: FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet-MobilenetV1
This model uses FaceNet with a MobileNetV1 backbone, providing a lightweight, efficient architecture suitable for real-time face recognition on mobile and embedded devices. It is well suited for applications such as authentication, access control, and edge-based identity verification.
Model Configuration:
- Reference implementation: FaceNet MobileNetV1 implementation
- Original Weight: FaceNet MobileNetV1 weight Extraction code: anv6
- Resolution: 3x160x160
- Support Cooper version:
- Cooper SDK: [2.5.4]
- Cooper Foundry: [2.3]
| Model | Device | compression | Model Link |
|---|---|---|---|
| FaceNet | N1-655 | Amba_optimized | Model_Link |
| FaceNet | X7 | Amba_optimized | Model_Link |
| FaceNet | CV7 | Amba_optimized | Model_Link |
| FaceNet | CV72 | Amba_optimized | Model_Link |
| FaceNet | CV75 | Amba_optimized | Model_Link |
- Library
- pytorch
- Type
- llama
- Created
- Dec 22, 2025
- Updated
- Sep 11, 2026