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# 启动
CVAT_HOST=10.71.115.9 docker-compose -f docker-compose.yml -f docker-compose.override.yml -f docker-compose.dev.yml   -f components/analytics/docker-compose.analytics.yml   -f components/serverless/docker-compose.serverless.yml up -d --build

# 备份
mkdir backup
docker run --rm --name temp_backup --volumes-from cvat_db -v $(pwd)/backup:/backup ubuntu tar -cjvf /backup/cvat_db.tar.bz2 /var/lib/postgresql/data --cpu 10
docker run --rm --name temp_backup --volumes-from cvat -v $(pwd)/backup:/backup ubuntu tar -cjvf /backup/cvat_data.tar.bz2 /home/django/data --cpu 10
# [optional]
docker run --rm --name temp_backup --volumes-from cvat_elasticsearch -v $(pwd)/backup:/backup ubuntu tar -cjvf /backup/cvat_events.tar.bz2 /usr/share/elasticsearch/data

#恢复备份
cd <path_to_backup_folder>
docker run --rm --name temp_backup --volumes-from cvat_db -v $(pwd):/backup ubuntu bash -c "cd /var/lib/postgresql/data && tar -xvf /backup/cvat_db.tar.bz2 --strip 4"
docker run --rm --name temp_backup --volumes-from cvat -v $(pwd):/backup ubuntu bash -c "cd /home/django/data && tar -xvf /backup/cvat_data.tar.bz2 --strip 3"
# [optional]
docker run --rm --name temp_backup --volumes-from cvat_elasticsearch -v $(pwd):/backup ubuntu bash -c "cd /usr/share/elasticsearch/data && tar -xvf /backup/cvat_events.tar.bz2 --strip 4"

# command line
python3 cli.py --server-host=10.71.115.8 --auth admin:admin dump --format "CVAT for images 1.1" 103 output.xml

# function yaml
  triggers:
    myHttpTrigger:
      maxWorkers: 2
      kind: 'http'
      workerAvailabilityTimeoutMilliseconds: 10000
      attributes:
        maxRequestBodySize: 33554432 # 32MB
        port: 49164
        ingresses:
          "49164":
            paths:
              - /
            host: 172.17.0.4
         
# 记得开启对应端口的iptables
sudo iptables -A INPUT -p tcp -m tcp --dport 9091 -j ACCEPT
sudo iptables-save

# 部署自动化服务
nuctl deploy --project-name cvat \
  --path serverless/openvino/dextr/nuclio \
  --volume `pwd`/serverless/common:/opt/nuclio/common \
  --platform local

nuctl deploy --project-name cvat \
  --path serverless/pytorch/seasons/PETNet/nuclio \
  --platform local --base-image ubuntu:18.04 \
  --desc "GPU based implementation of PETNet for polyp segmentation." \
  --image cvat/PETNet\
  --triggers '{"myHttpTrigger": {"maxWorkers": 2}}' \
  --resource-limit nvidia.com/gpu=1