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bicycle_rider_detector_002

Object Detection

Inference Endpoints

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bicycle_rider_detector_002 / function.yaml

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	metadata:
	name: custom-model-yolov8
	namespace: cvat
	annotations:
	name: custom-model-yolov8
	type: detector
	framework: pytorch
	# change this accordingly to your model output/classes
	spec: \|
	[
	{"id": 0, "name": "bicycle_rider"}
	]
	spec:
	description: custom-model-yolov8
	runtime: 'python:3.9'
	handler: main:handler
	eventTimeout: 30s

	build:
	image: custom-model-yolov8
	baseImage: ubuntu:22.04

	directives:
	preCopy:
	- kind: ENV
	value: DEBIAN_FRONTEND=noninteractive
	- kind: RUN
	value: apt-get update && apt-get -y install curl git python3 python3-pip
	- kind: RUN
	value: apt-get -y install libgl1-mesa-glx libglib2.0-dev
	- kind: WORKDIR
	value: /opt/nuclio
	#
	# make sure that for the next step (at least) the ultralytics package version
	# is compatible to that of the the ultralytics package used to train the custom model
	- kind: RUN
	value: pip3 install ultralytics==8.0.114 opencv-python==4.7.0.72 numpy==1.24.3
	#
	- kind: RUN
	value: ln -s /usr/bin/pip3 /usr/local/bin/pip
	- kind: RUN
	value: ln -s /usr/bin/python3 /usr/local/bin/python

	triggers:
	myHttpTrigger:
	maxWorkers: 1
	kind: 'http'
	workerAvailabilityTimeoutMilliseconds: 10000
	attributes:
	maxRequestBodySize: 33554432 # 32MB

	platform:
	attributes:
	restartPolicy:
	name: always
	maximumRetryCount: 3
	mountMode: volume