add face-detect-demo

facedetect-rasyberrypi/README.md

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+# face detect example
+* This demonstration is based on kubeedge, allowing part of the algorithm analysis ability to run on the edge. 
+* Demo is just an example, you can use this as an example to run various algorithm applications on the edge. 
+* The docker image used in this example can be used as a basic image to make images of different business scenarios.
+* The demo does not necessarily have better performance, this is just a scenario demonstration. 
+
+<img src="demo.png">
+
+## Details for the face detect demo, please read the [Demo guide](./guides/face_detect_demo_guide.md)

facedetect-rasyberrypi/dockerfile/Dockerfile

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+FROM kubeedge/face-detect-demo:v1
+
+## add your application code with python3

facedetect-rasyberrypi/guides/face_detect_demo_guide.md

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+# Guide for use Kubeedge to run face detect Demo for edge at a raspberryPi
+* This demonstration is based on kubeedge, allowing part of the algorithm analysis ability to run on the edge. 
+* Demo is just an example, you can use this as an example to run various algorithm applications on the edge. 
+* The docker image used in this example can be used as a basic image to make images of different business scenarios.
+* The demo does not necessarily have better performance, this is just a scenario demonstration. 
+## 1. Prepare Kubeedge environment 
+install guide please refers to the kubeedge install readme
+[Kubeedge installation reference](https://github.com/kubeedge/kubeedge/blob/master/README.md)
+
+## 2. Prepare the raspberryPi environment
+> Demo supports raspberrypi3 and higher
+```shell script
+run rasp-config to enable the raspberryPi camera. and reboot.
+```
+## 3 . Run the face detect demo 
+> Provide two ways to run this face recognition demo on RaspberryPi
+
+### 3.1. By using rtsp stream provided by the raspberryPi built-in camera
+> note: This method supports the camera which support RTSP video stream. Not just the camera that comes with raspberryPi \
+> The following steps use Raspberry Pi as an example
+
++ Step1. Generate RTSP vide stream with build-in camera
+
+> install the dependent packages
+```shell script
+apt-get install cmake liblog4cpp5-dev libv4l-dev
+```
+> [download the rtsp tool](https://github.com/mpromonet/v4l2rtspserver/releases/tag/v0.1.9)
+```shell script
+# install the rtsp tool
+dpkg -i v4l2rtspserver-0.1.9-Linux-armv7l.deb
+```
+> start the RTSP server
+```shell script
+v4l2rtspserver -H 640 -W 480 -F 15 -P 8555 /dev/video0 > rtsp.log 2>&1&
+```
+> -F : the frame rate \
+> -H : the frame height \
+> -W : the frame width \
+> -P : the rtsp server port
+> after finished the above steps, you will get a rtsp server url
+```shell script
+rtsp://hostip:8555/unicast
+# the hostip depends on the configuration on your machine
+```
+
++ Step2. Pull the Demo images
+```shell script
+docker pull kubeedge/face-detect-demo:v1
+```
++ Step3. Run with docker
+```shell script
+docker run -d -p 8099:8099 -e VIDEO_URL=rtsp://${hostip}:8555/unicast kubeedge/face-detect-demo:v1 python3 /opt/src/app_rtsp.py
+```
++ Or run with kubeedge
+> The deployment files are as follows
+```yaml
+apiVersion: v1
+kind: Pod
+metadata:
+  name: face-detect-demo
+  labels:
+    app: demo
+spec:
+  containers:
+  - name: demo
+    image: kubeedge/face-detect-demo:v1
+    imagePullPolicy: IfNotPresent
+    ports:
+    - containerPort: 8099
+      hostPort: 8099
+    args:
+    - /opt/src/app_rtsp.py
+    command:
+    - python3
+    env:
+    - name: VIDEO_URL
+      value: rtsp://${hostip}:8555/unicast
+  nodeSelector:
+    name: ${node_id}
+```
+
+
+### 3.2. By using the picamera module in python (Recommended,Performance will be better)
+> this method just support the raspberryPi, does not support other types of machine
++ Step1. Pull the Demo images
+```shell script
+docker pull docker pull kubeedge/face-detect-demo:v1
+```
+
++ Step2. Run with docker
+> The deployment files are as follows
+```shell script
+docker run -d --privileged=true -v /dev/:/dev/ -p 8099:8099 kubeedge/face-detect-demo:v1 python3 /opt/src/app.py
+```
+
++ Or run with kubeedge
+> The deployment files are as follows
+```yaml
+apiVersion: v1
+kind: Pod
+metadata:
+  name: face-detect-demo
+  labels:
+    app: demo
+spec:
+  containers:
+  - name: demo
+    image: kubeedge/face-detect-demo:v1
+    imagePullPolicy: IfNotPresent
+    ports:
+    - containerPort: 8099
+      hostPort: 8099
+    args:
+    - /opt/src/app.py
+    command:
+    - python3
+    volumeMounts:
+    - name: dev
+      mountPath: /dev/
+    securityContext:
+      privileged: true
+  volumes:
+  - name: dev
+    hostPath:
+      path: /dev/
+  nodeSelector:
+    name: ${node_id}
+```