Tensorflow docker image for IOT devices
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SharpAI is open source stack for machine learning engineering with private deployment and AutoML for edge computing. DeepCamera is application of SharpAI designed for connect computer vision model to surveillance camera. Developers can run same code on Raspberry Pi/Android/PC/AWS to boost your AI production development.



Please install 32bit system (official raspbian)
Now you need to enable camera support using the raspi-config program you will have used when you first set up your Raspberry Pi. Use the cursor keys to select and open Interfacing Options, and then select Camera and follow the prompt to enable the camera. https://www.raspberrypi.org/documentation/configuration/camera.md
Reference: Installing Docker and Docker Compose on the Raspberry Pi in 5 Simple Steps
git clone https://github.com/SharpAI/DeepCamera
edit configuration on Pi, change following environment variables to PC/Server/Cloud ip address:
AWS_END_POINT='<Server_IP>'
AWS_BUCKET=faces
AWS_READABLE_PREFIX='http://<Server_IP>:9000/faces/'
MQTT_BROKER_ADDRESS=<Server_IP>
API_SERVER_ADDRESS=<Server_IP>
cd DeepCamera
./run-on-rpi.sh start
git clone https://github.com/SharpAI/DeepCamera
cd DeepCamera
./start-cloud.sh start
You need ip address of private cloud server on next step (replace ip address to <Server_IP> on next step).
If you don't want to setup your own server for now, a test server can be used for evaluation, the ip address of test server is 165.232.62.29
cat docker/workaipython/ro_serialno
82f28703d001
82f28703d001 is device ID.
Generate QRCode of device ID









Shinobi login page(device_ip:8080):
username: [email protected]
password: SharpAI2018
Change IP configuration and camera url on the page. Detail information
If you are using other camera support streaming, please check The Shinobi NVR's document
cat docker/workaipython/ro_serialno
82f28703d001
82f28703d001 is device ID
REST API:
curl -X POST -H "Content-type: application/json" http://localhost:3000/api/v1/sign-up -d '{"username": "test11", "email": "[email protected]", "password": "xxxxxx"}'
Response:
{
"success": true
}
REST API:
curl -X POST -H "Content-type: application/json" http://localhost:3000/api/v1/login/ -d '{"username": "test11", "email": "[email protected]", "password": "123456"}'
Response:
{
"status": "success",
"data": {
"authToken": "t6QsPaU3VdbfUQMkNIf6I3MDtox29WLrPJRAKkOCfpc",
"userId": "tiK8RYG87sGJAErdB"
}
}
Rest API:
Fill in X-Auth-Token and X-User-Id in previous response.
curl -X POST -H "X-Auth-Token: t6QsPaU3VdbfUQMkNIf6I3MDtox29WLrPJRAKkOCfpc" -H "X-User-Id: tiK8RYG87sGJAErdB" http://localhost:3000/api/v1/groups -d "name=group01"
Response:
{
"groupId": "e309ff8c7a3a8ceb4011e86e"
}
REST API:
Replace X-Auth-Token and X-User-Id.
Replace group id in requesting URL: http://localhost:3000/api/v1/groups/`e309ff8c7a3a8ceb4011e86e`/devices
curl -X POST -H "X-Auth-Token: t6QsPaU3VdbfUQMkNIf6I3MDtox29WLrPJRAKkOCfpc" -H "X-User-Id: tiK8RYG87sGJAErdB" -H "Content-type: application/json" http://localhost:3000/api/v1/groups/e309ff8c7a3a8ceb4011e86e/devices -d '{"uuid": "82f28703d001", "deviceName": "testDevice", "name":"testdevice","type": "inout"}'
Response:
{
"success": true
}
Then restart DeepCamera service.
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Content type
Image
Digest
Size
718.7 MB
Last updated
about 5 years ago
docker pull shareai/tensorflow:nano_latest