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~~tag> NPU RetinaFace FaceNet Edge2 ~~

====== Face Recognition Edge2 Demo - 7 ======

{{indexmenu_n>7}}

<WRAP important >
This demo integrates RetinaFace and FaceNet. Please refer [[retinaface]] and [[facenet]] to convert model. Here only run inference on the NPU.
</WRAP>

===== Run NPU =====

==== Get source code ====

Clone the source code from our [[gh>khadas/edge2-npu]].

```shell
$ git clone https://github.com/khadas/edge2-npu
```

==== Install dependencies ====

```shell
$ sudo apt update
$ sudo apt install cmake libopencv-dev
```

==== Compile and run ====

=== Picture input demo ===

Like facenet, there are also two modes of this demo. One is converting face images into feature vectors and saving vectors in the face library. Another is comparing input face image with faces in the library and outputting Euclidean distance and cosine similarity.

Put ''retinaface.rknn'' and ''facenet.rknn'' in ''edge2-npu/C++/retinaface/data/model''.

```shell
# Compile
$ bash build.sh

# Run mode 1
$ cd install/face_recognition
$ ./face_recognition data/model/retinaface.rknn data/model/facenet.rknn 1
```

After running mode 1, a file named ''face_feature_lib'' will generate in ''edge2-npu/C++/face_recognition/install/face_recognition/data''. With this file generated, you can run mode 2.

```shell
# Run mode 2
$ ./face_recognition data/model/retinaface.rknn data/model/facenet.rknn data/img/lin_1.jpg
```

=== Camera input demo ===

Put ''retinaface.rknn'' and ''facenet.rknn'' in ''edge2-npu/C++/face_recognition_cap/data/model''.

```shell
# Compile
$ bash build.sh
```

Put your full face photo into the ''edge2-npu/C++/face_recognition/data/img''. Recompile and run mode 1 to generate ''face_feature_lib''. Put ''face_feature_lib'' in ''edge2-npu/C++/face_recognition_cap/install/face_recognition_cap/data''.

```shell
# Run
$ cd install/retinaface_cap
$ ./face_recognition data/model/retinaface.rknn data/model/facenet.rknn 33
```

''33'' is camera device index.
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