Add release note for v1.1.0

README.md

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+---
+library_name: pytorch
+---
+
+![facenet_logo](resource/Facenet_mobilenet.png)
+
+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](https://arxiv.org/abs/1503.03832)
+
+# FaceNet
+
+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](https://github.com/bubbliiiing/facenet-pytorch)
+- Original Weight: [FaceNet MobileNetV1 weight](https://pan.baidu.com/s/1K20hyxU_UgSej1eZWih0Ag)  
+  Extraction code: anv6
+- Resolution: 3x160x160
+- Support Cooper version:
+    - Cooper SDK: [2.5.2]
+    - Cooper Foundry: [2.2]
+
+| Model | Device | Model Link |
+| :-----: | :-----: | :-----: |
+| FaceNet | N1-655 | [Model_Link](https://huggingface.co/Ambarella/Facenet/blob/main/n1-655_facenet_mobilenet.bin) |
+| FaceNet | CV72 | [Model_Link](https://huggingface.co/Ambarella/Facenet/blob/main/cv72_facenet_mobilenet.bin) |
+| FaceNet | CV75 | [Model_Link](https://huggingface.co/Ambarella/Facenet/blob/main/cv75_facenet_mobilenet.bin) |