Setup additional components in development environment

DL models as serverless functions

Follow this guide to install Nuclio:

You have to install nuctl command line tool to build and deploy serverless functions.
The simplest way to explore Nuclio is to run its graphical user interface (GUI) of the Nuclio dashboard. All you need in order to run the dashboard is Docker. See nuclio documentation for more details.
Create cvat project inside nuclio dashboard where you will deploy new serverless functions and deploy a couple of DL models.

nuctl create project cvat

nuctl deploy --project-name cvat \
    --path serverless/openvino/dextr/nuclio \
    --volume `pwd`/serverless/openvino/common:/opt/nuclio/common \
    --platform local

20.07.17 12:02:23.247                     nuctl (I) Deploying function {"name": ""}
20.07.17 12:02:23.248                     nuctl (I) Building {"versionInfo": "Label: 1.4.8, Git commit: 238d4539ac7783896d6c414535d0462b5f4cbcf1, OS: darwin, Arch: amd64, Go version: go1.14.3", "name": ""}
20.07.17 12:02:23.447                     nuctl (I) Cleaning up before deployment
20.07.17 12:02:23.535                     nuctl (I) Function already exists, deleting
20.07.17 12:02:25.877                     nuctl (I) Staging files and preparing base images
20.07.17 12:02:25.891                     nuctl (I) Building processor image {"imageName": "cvat/openvino.dextr:latest"}
20.07.17 12:02:25.891     nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/handler-builder-python-onbuild:1.4.8-amd64"}
20.07.17 12:02:29.270     nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/uhttpc:0.0.1-amd64"}
20.07.17 12:02:33.208            nuctl.platform (I) Building docker image {"image": "cvat/openvino.dextr:latest"}
20.07.17 12:02:34.464            nuctl.platform (I) Pushing docker image into registry {"image": "cvat/openvino.dextr:latest", "registry": ""}
20.07.17 12:02:34.464            nuctl.platform (I) Docker image was successfully built and pushed into docker registry {"image": "cvat/openvino.dextr:latest"}
20.07.17 12:02:34.464                     nuctl (I) Build complete {"result": {"Image":"cvat/openvino.dextr:latest","UpdatedFunctionConfig":{"metadata":{"name":"openvino.dextr","namespace":"nuclio","labels":{"nuclio.io/project-name":"cvat"},"annotations":{"framework":"openvino","spec":"","type":"interactor"}},"spec":{"description":"Deep Extreme Cut","handler":"main:handler","runtime":"python:3.6","env":[{"name":"NUCLIO_PYTHON_EXE_PATH","value":"/opt/nuclio/python3"}],"resources":{},"image":"cvat/openvino.dextr:latest","targetCPU":75,"triggers":{"myHttpTrigger":{"class":"","kind":"http","name":"","maxWorkers":2,"workerAvailabilityTimeoutMilliseconds":10000,"attributes":{"maxRequestBodySize":33554432}}},"volumes":[{"volume":{"name":"volume-1","hostPath":{"path":"/Users/nmanovic/Workspace/cvat/serverless/openvino/common"}},"volumeMount":{"name":"volume-1","mountPath":"/opt/nuclio/common"}}],"build":{"image":"cvat/openvino.dextr","baseImage":"openvino/ubuntu18_runtime:2020.2","directives":{"postCopy":[{"kind":"RUN","value":"curl -O https://download.01.org/openvinotoolkit/models_contrib/cvat/dextr_model_v1.zip"},{"kind":"RUN","value":"unzip dextr_model_v1.zip"},{"kind":"RUN","value":"pip3 install Pillow"},{"kind":"USER","value":"openvino"}],"preCopy":[{"kind":"USER","value":"root"},{"kind":"WORKDIR","value":"/opt/nuclio"},{"kind":"RUN","value":"ln -s /usr/bin/pip3 /usr/bin/pip"}]},"codeEntryType":"image"},"platform":{},"readinessTimeoutSeconds":60,"eventTimeout":"30s"}}}}
20.07.17 12:02:35.012            nuctl.platform (I) Waiting for function to be ready {"timeout": 60}
20.07.17 12:02:37.448                     nuctl (I) Function deploy complete {"httpPort": 55274}

nuctl deploy --project-name cvat \
    --path serverless/openvino/omz/public/yolo-v3-tf/nuclio \
    --volume `pwd`/serverless/openvino/common:/opt/nuclio/common \
    --platform local

20.07.17 12:05:23.377                     nuctl (I) Deploying function {"name": ""}
20.07.17 12:05:23.378                     nuctl (I) Building {"versionInfo": "Label: 1.4.8, Git commit: 238d4539ac7783896d6c414535d0462b5f4cbcf1, OS: darwin, Arch: amd64, Go version: go1.14.3", "name": ""}
20.07.17 12:05:23.590                     nuctl (I) Cleaning up before deployment
20.07.17 12:05:23.694                     nuctl (I) Function already exists, deleting
20.07.17 12:05:24.271                     nuctl (I) Staging files and preparing base images
20.07.17 12:05:24.274                     nuctl (I) Building processor image {"imageName": "cvat/openvino.omz.public.yolo-v3-tf:latest"}
20.07.17 12:05:24.274     nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/handler-builder-python-onbuild:1.4.8-amd64"}
20.07.17 12:05:27.432     nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/uhttpc:0.0.1-amd64"}
20.07.17 12:05:31.462            nuctl.platform (I) Building docker image {"image": "cvat/openvino.omz.public.yolo-v3-tf:latest"}
20.07.17 12:05:32.798            nuctl.platform (I) Pushing docker image into registry {"image": "cvat/openvino.omz.public.yolo-v3-tf:latest", "registry": ""}
20.07.17 12:05:32.798            nuctl.platform (I) Docker image was successfully built and pushed into docker registry {"image": "cvat/openvino.omz.public.yolo-v3-tf:latest"}
20.07.17 12:05:32.798                     nuctl (I) Build complete {"result": {"Image":"cvat/openvino.omz.public.yolo-v3-tf:latest","UpdatedFunctionConfig":{"metadata":{"name":"openvino.omz.public.yolo-v3-tf","namespace":"nuclio","labels":{"nuclio.io/project-name":"cvat"},"annotations":{"framework":"openvino","name":"YOLO v3","spec":"[\n  { \"id\": 0, \"name\": \"person\" },\n  { \"id\": 1, \"name\": \"bicycle\" },\n  { \"id\": 2, \"name\": \"car\" },\n  { \"id\": 3, \"name\": \"motorbike\" },\n  { \"id\": 4, \"name\": \"aeroplane\" },\n  { \"id\": 5, \"name\": \"bus\" },\n  { \"id\": 6, \"name\": \"train\" },\n  { \"id\": 7, \"name\": \"truck\" },\n  { \"id\": 8, \"name\": \"boat\" },\n  { \"id\": 9, \"name\": \"traffic light\" },\n  { \"id\": 10, \"name\": \"fire hydrant\" },\n  { \"id\": 11, \"name\": \"stop sign\" },\n  { \"id\": 12, \"name\": \"parking meter\" },\n  { \"id\": 13, \"name\": \"bench\" },\n  { \"id\": 14, \"name\": \"bird\" },\n  { \"id\": 15, \"name\": \"cat\" },\n  { \"id\": 16, \"name\": \"dog\" },\n  { \"id\": 17, \"name\": \"horse\" },\n  { \"id\": 18, \"name\": \"sheep\" },\n  { \"id\": 19, \"name\": \"cow\" },\n  { \"id\": 20, \"name\": \"elephant\" },\n  { \"id\": 21, \"name\": \"bear\" },\n  { \"id\": 22, \"name\": \"zebra\" },\n  { \"id\": 23, \"name\": \"giraffe\" },\n  { \"id\": 24, \"name\": \"backpack\" },\n  { \"id\": 25, \"name\": \"umbrella\" },\n  { \"id\": 26, \"name\": \"handbag\" },\n  { \"id\": 27, \"name\": \"tie\" },\n  { \"id\": 28, \"name\": \"suitcase\" },\n  { \"id\": 29, \"name\": \"frisbee\" },\n  { \"id\": 30, \"name\": \"skis\" },\n  { \"id\": 31, \"name\": \"snowboard\" },\n  { \"id\": 32, \"name\": \"sports ball\" },\n  { \"id\": 33, \"name\": \"kite\" },\n  { \"id\": 34, \"name\": \"baseball bat\" },\n  { \"id\": 35, \"name\": \"baseball glove\" },\n  { \"id\": 36, \"name\": \"skateboard\" },\n  { \"id\": 37, \"name\": \"surfboard\" },\n  { \"id\": 38, \"name\": \"tennis racket\" },\n  { \"id\": 39, \"name\": \"bottle\" },\n  { \"id\": 40, \"name\": \"wine glass\" },\n  { \"id\": 41, \"name\": \"cup\" },\n  { \"id\": 42, \"name\": \"fork\" },\n  { \"id\": 43, \"name\": \"knife\" },\n  { \"id\": 44, \"name\": \"spoon\" },\n  { \"id\": 45, \"name\": \"bowl\" },\n  { \"id\": 46, \"name\": \"banana\" },\n  { \"id\": 47, \"name\": \"apple\" },\n  { \"id\": 48, \"name\": \"sandwich\" },\n  { \"id\": 49, \"name\": \"orange\" },\n  { \"id\": 50, \"name\": \"broccoli\" },\n  { \"id\": 51, \"name\": \"carrot\" },\n  { \"id\": 52, \"name\": \"hot dog\" },\n  { \"id\": 53, \"name\": \"pizza\" },\n  { \"id\": 54, \"name\": \"donut\" },\n  { \"id\": 55, \"name\": \"cake\" },\n  { \"id\": 56, \"name\": \"chair\" },\n  { \"id\": 57, \"name\": \"sofa\" },\n  { \"id\": 58, \"name\": \"pottedplant\" },\n  { \"id\": 59, \"name\": \"bed\" },\n  { \"id\": 60, \"name\": \"diningtable\" },\n  { \"id\": 61, \"name\": \"toilet\" },\n  { \"id\": 62, \"name\": \"tvmonitor\" },\n  { \"id\": 63, \"name\": \"laptop\" },\n  { \"id\": 64, \"name\": \"mouse\" },\n  { \"id\": 65, \"name\": \"remote\" },\n  { \"id\": 66, \"name\": \"keyboard\" },\n  { \"id\": 67, \"name\": \"cell phone\" },\n  { \"id\": 68, \"name\": \"microwave\" },\n  { \"id\": 69, \"name\": \"oven\" },\n  { \"id\": 70, \"name\": \"toaster\" },\n  { \"id\": 71, \"name\": \"sink\" },\n  { \"id\": 72, \"name\": \"refrigerator\" },\n  { \"id\": 73, \"name\": \"book\" },\n  { \"id\": 74, \"name\": \"clock\" },\n  { \"id\": 75, \"name\": \"vase\" },\n  { \"id\": 76, \"name\": \"scissors\" },\n  { \"id\": 77, \"name\": \"teddy bear\" },\n  { \"id\": 78, \"name\": \"hair drier\" },\n  { \"id\": 79, \"name\": \"toothbrush\" }\n]\n","type":"detector"}},"spec":{"description":"YOLO v3 via Intel OpenVINO","handler":"main:handler","runtime":"python:3.6","env":[{"name":"NUCLIO_PYTHON_EXE_PATH","value":"/opt/nuclio/common/python3"}],"resources":{},"image":"cvat/openvino.omz.public.yolo-v3-tf:latest","targetCPU":75,"triggers":{"myHttpTrigger":{"class":"","kind":"http","name":"","maxWorkers":2,"workerAvailabilityTimeoutMilliseconds":10000,"attributes":{"maxRequestBodySize":33554432}}},"volumes":[{"volume":{"name":"volume-1","hostPath":{"path":"/Users/nmanovic/Workspace/cvat/serverless/openvino/common"}},"volumeMount":{"name":"volume-1","mountPath":"/opt/nuclio/common"}}],"build":{"image":"cvat/openvino.omz.public.yolo-v3-tf","baseImage":"openvino/ubuntu18_dev:2020.2","directives":{"postCopy":[{"kind":"USER","value":"openvino"}],"preCopy":[{"kind":"USER","value":"root"},{"kind":"WORKDIR","value":"/opt/nuclio"},{"kind":"RUN","value":"ln -s /usr/bin/pip3 /usr/bin/pip"},{"kind":"RUN","value":"/opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name yolo-v3-tf -o /opt/nuclio/open_model_zoo"},{"kind":"RUN","value":"/opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo"}]},"codeEntryType":"image"},"platform":{},"readinessTimeoutSeconds":60,"eventTimeout":"30s"}}}}
20.07.17 12:05:33.285            nuctl.platform (I) Waiting for function to be ready {"timeout": 60}
20.07.17 12:05:35.452                     nuctl (I) Function deploy complete {"httpPort": 57308}

Display a list of running serverless functions using nuctl command or see them in nuclio dashboard:

nuctl get function

  NAMESPACE |                             NAME                              | PROJECT | STATE | NODE PORT | REPLICAS
  nuclio    | openvino.dextr                                                | cvat    | ready |     55274 | 1/1
  nuclio    | openvino.omz.public.yolo-v3-tf                                | cvat    | ready |     57308 | 1/1

Test your deployed DL model as a serverless function. The command below should work on Linux and Mac OS.

image=$(curl https://upload.wikimedia.org/wikipedia/en/7/7d/Lenna_%28test_image%29.png --output - | base64 | tr -d '\n')
cat << EOF > /tmp/input.json
{"image": "$image"}
EOF
cat /tmp/input.json | nuctl invoke openvino.omz.public.yolo-v3-tf -c 'application/json'

20.07.17 12:07:44.519    nuctl.platform.invoker (I) Executing function {"method": "POST", "url": "http://:57308", "headers": {"Content-Type":["application/json"],"X-Nuclio-Log-Level":["info"],"X-Nuclio-Target":["openvino.omz.public.yolo-v3-tf"]}}
20.07.17 12:07:45.275    nuctl.platform.invoker (I) Got response {"status": "200 OK"}
20.07.17 12:07:45.275                     nuctl (I) >>> Start of function logs
20.07.17 12:07:45.275 ino.omz.public.yolo-v3-tf (I) Run yolo-v3-tf model {"worker_id": "0", "time": 1594976864570.9353}
20.07.17 12:07:45.275                     nuctl (I) <<< End of function logs

> Response headers:
Date = Fri, 17 Jul 2020 09:07:45 GMT
Content-Type = application/json
Content-Length = 100
Server = nuclio

> Response body:
[
    {
        "confidence": "0.9992254",
        "label": "person",
        "points": [
            39,
            124,
            408,
            512
        ],
        "type": "rectangle"
    }
]

Run Cypress tests

Install Сypress as described in the documentation.
Run cypress tests:

    cd <cvat_local_repository>/tests
    <cypress_installation_directory>/node_modules/.bin/cypress run --headless --browser chrome

For more information, see the documentation.