DeepCamera is a computer vision machine learning pipeline. You can use DeepCamera to collect data from Cameras, upload prelabeled images to server, retrieve data and retrain model then deploy model to edge device such as Jetson Nano for example.

• Integration with Home Assistant
• 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
• 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)

• Provide real time pipeline on edge device
• E2E pipeline to support model customization
• Cluster on the edge
• Port to specific edge device/chipset
• Voice application (ASR/KWS) end to end pipeline
• ReID model
• Behavior analysis model
• Transformer model
• Contrastive learning
• Click to join sharpai slack channel for commercial support

sudo apt-get install -y libhdf5-dev python3 python3-pip
pip3 install -U pip
sudo pip3 install docker-compose==1.27.4

git clone https://github.com/SharpAI/DeepCamera

• Create Telegram Bot through @BotFather
• Set Telegram Token in Configure File
• Send message to the new bot you created

cd DeepCamera  
./run-on-nano.sh start

On Jetson Nano, Access to 8080 port. http://localhost:8080
Default username and password is:
username: [email protected]
password: SharpAI2018

Tested Camera: DaHua / Lorex / AMCREST, URL Path: /cam/realmonitor?channel=1&subtype=0 Port: 554

You can use iSpyConnect to get camera streaming URL

When setup done, you will see live view on web page, when detected person in camera, you will receive video clips on telegram.

cat docker/workaipython/ro_serialno 
82f28703d001

82f28703d001 is device ID.

Access http://165.232.62.29:3000/

cat docker/workaipython/ro_serialno 
82f28703d001

82f28703d001 is device ID.
Generate QRCode of device ID

If you don't like the GUI or you want to develop your own application.
You can use following API:

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.

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

Click to join sharpai slack channel