AI Face Recognition/Person Detection NVR
Machine Learning On The Edge, Turn your Camera into AI-powered with Edge AI device
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.
Features
- FFMpeg with Nvidia Nano hardware decoder
- Face Detector with Nvidia Nano GPU TensorRT MTCNN
- Face Embedding with Nvidia Nano GPU Pytorch InsightFace
- Person Detection with GPU
- Integrate with telegram bot API
DeepCamera Architecture
Demo On Youtube
Get Started on Jetson Nano
Install Docker-compose
sudo apt-get install -y libhdf5-dev python3 python3-pip
pip3 install -U pip
sudo pip3 install docker-compose==1.27.4
Get source code
git clone https://github.com/SharpAI/DeepCamera
Create Token for Telegram Bot
- Create Telegram Bot through @BotFather
- Set Telegram Token in Configure File
- Send message to the new bot you created
Start DeepCamera
cd DeepCamera
./run-on-nano.sh start
Connect To Camera through RTSP URL
On Jetson Nano, Access to 8080 port.
http://localhost:8080
Default username and password is:
username: user@sharpaibox.com
password: SharpAI2018
Tested Camera: DaHua / Lorex / AMCREST, URL Path: /cam/realmonitor?channel=1&subtype=0 Port: 554
When setup done, you will see live view on web page, when detected person in camera, you will receive video clips on telegram.
Label on Web GUI, train face recognition model on device
cat docker/workaipython/ro_serialno
82f28703d001
82f28703d001
is device ID.
Access http://165.232.62.29:3000/
Detail information
Camera streaming URL format
Use Mobile APP to label and train face recognition model on device
Get device serial number
cat docker/workaipython/ro_serialno
82f28703d001
82f28703d001
is device ID.
Generate QRCode of device ID
SharpAI Mobile APP
Download and installConfigure on Mobile APP
Develop your own Application GUI with DeepCamera API Server
If you don't like the GUI or you want to develop your own application.
You can use following API:
Get device serial number
cat docker/workaipython/ro_serialno
82f28703d001
82f28703d001
is device ID
Create User on API Server
REST API:
curl -X POST -H "Content-type: application/json" http://localhost:3000/api/v1/sign-up -d '{"username": "test11", "email": "xxxx@xxx.xx", "password": "xxxxxx"}'
Response:
{
"success": true
}
Get Token of created user
REST API:
curl -X POST -H "Content-type: application/json" http://localhost:3000/api/v1/login/ -d '{"username": "test11", "email": "xxxx@xxx.xx", "password": "123456"}'
Response:
{
"status": "success",
"data": {
"authToken": "t6QsPaU3VdbfUQMkNIf6I3MDtox29WLrPJRAKkOCfpc",
"userId": "tiK8RYG87sGJAErdB"
}
}
Create Group on API Server
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"
}
Add device to Group on API Server
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.
SharpAI/ApiServer
API Server document can be found here:How to run DeepCamera On PC
You can also develop/debug code on your PCDeploy your own API_Server on X86/Cloud Server
Now, you got the idea of DeepCamera,
the public testing server is open to the internet.
You can deploy your own API server on your OWN device.
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
If your have any question or feature request, please feel free to join slack for commercial support
Slack
Click to join sharpai slack channel
Todo List
- Porting to Jetson Nano
- High accurate Face Recognition
- Face Detection
- Inference on ARM Mali GPU
- Support Android TF Lite(GPU/CPU/NPU)
- Support open source embedded linux
- Control from mobile application
- Management System for devices
- Push Notification to Mobile Device
- Object Detection
- Distributed System based on celery
- Plugin to process video by Shinobi CCTV
- Application on Android to decode video with hw acc
- Motion Detection with Android GPU
- Lable and train from Mobile to Edge Device
- Native raspberry pi camera support
- Labelling server and application is down, need BYOD document API server repo
- Image upload to AWS or on premise AWS compatiable server(MINIO)