Deploying an object detection application to the cloud using Kubernetes and Helm

1. pipeless

   1 24 767 9.6 Rust

   An open-source computer vision framework to build and deploy apps in minutes

   

   helm install pipeless . --set worker.application.git_repo="https://github.com/pipeless-ai/pipeless.git",worker.application.subPath="examples/onnx-yolo",worker.plugins.order="draw",worker.inference.model_uri="file:///app/yolov8n.onnx" --set worker.replicaCount=4

2. Stream

   getstream.io featured

   Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.

   

3. pipeless

   2 7 104 10.0 Python

   Discontinued An open-source computer vision framework to build and deploy apps in minutes without worrying about multimedia pipelines [Moved to: https://github.com/pipeless-ai/pipeless] (by miguelaeh)

   

4. pipelessassets

   3 1 - -

5. k3s

   4 324 31,686 9.6 Go

   Lightweight Kubernetes

   

   Before deploying our application with Helm, we need a Kubernetes cluster. There are many options to deploy a Kubernetes cluster. You can use Minikube to do it locally, K3s or you can create a cluster in AWS, Azure or Google Cloud.

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