Roboflow Deployment Integrations

Explore how to use Roboflow in combination with deployment software to solve computer vision problems.

You can use datasets annotated and generated in Roboflow in HuggingFace image models.

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You can train models on datasets in the Roboflow platform directly on the Google Cloud Platform through Cloud Vision.

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Microsoft Azure Vision Training

You can train models on datasets in the Roboflow platform directly on Microsoft Azure's infrastructure.

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IBM Cloud

You can export the data annotated in IBM Cloud into Roboflow for use in generating a dataset with preprocessing and augmentations, and for use in model training.

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Raspberry Pi

You can deploy the Roboflow inference server to a Pi, ideal when you need to deploy your model on a device with a small form factor.

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NVIDIA Jetson

You can deploy models hosted on Roboflow to an NVIDIA Jetson.

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iOS

You can deploy models hosted on Roboflow into native mobile apps using the iOS SDK.

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Glitch.me

You can deploy Roboflow models in the browser in a Glitch.me environment.

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Zapier

Use Zapier and Roboflow to build no-code computer vision applications.

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OBS

Use Roboflow models to control OBS live streams and videos.

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Web Browser

The roboflow.js JavaScript library, built on top of tensorflow.js, provides concise utilities to deploy your models hosted on Roboflow to a web browser.

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Kubernetes

The inference server Docker containers provided by Roboflow can be hosted using Kubernetes.

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Luxonis OAK

Roboflow provides a Python package called roboflowoak that provides easy utilities for running models hosted on Roboflow on an OAK.

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NVIDIA TRT

Roboflow provides a Docker container for use with TensorRT. This container supports inference using Roboflow models for object detection, classification, and instance segmentation tasks.

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