metadata: name: openvino.omz.semantic-segmentation-adas-0001 namespace: cvat annotations: name: Semantic segmentation for ADAS type: detector framework: openvino spec: | [ { "id": 0, "name": "road" }, { "id": 1, "name": "sidewalk" }, { "id": 2, "name": "building" }, { "id": 3, "name": "wall" }, { "id": 4, "name": "fence" }, { "id": 5, "name": "pole" }, { "id": 6, "name": "traffic light" }, { "id": 7, "name": "traffic sign" }, { "id": 8, "name": "vegetation" }, { "id": 9, "name": "terrain" }, { "id": 10, "name": "sky" }, { "id": 11, "name": "person" }, { "id": 12, "name": "rider" }, { "id": 13, "name": "car" }, { "id": 14, "name": "truck" }, { "id": 15, "name": "bus" }, { "id": 16, "name": "train" }, { "id": 17, "name": "motorcycle" }, { "id": 18, "name": "bicycle" }, { "id": 19, "name": "ego-vehicle" }, { "id": 20, "name": "background" } ] spec: description: Segmentation network to classify each pixel into typical 20 classes for ADAS runtime: "python:3.6" handler: main:handler eventTimeout: 30s env: - name: NUCLIO_PYTHON_EXE_PATH value: /opt/nuclio/common/python3 build: image: cvat/openvino.omz.intel.semantic-segmentation-adas-0001 baseImage: openvino/ubuntu18_dev:2020.2 directives: 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 semantic-segmentation-adas-0001 -o /opt/nuclio/open_model_zoo postCopy: - kind: RUN value: apt update && DEBIAN_FRONTEND=noninteractive apt install --no-install-recommends -y python3-skimage - kind: RUN value: pip3 install "numpy<1.16.0" # workaround for skimage triggers: myHttpTrigger: maxWorkers: 2 kind: "http" workerAvailabilityTimeoutMilliseconds: 10000 attributes: maxRequestBodySize: 33554432 # 32MB platform: attributes: restartPolicy: name: always maximumRetryCount: 3