Connect YOLO-NAS with S3 Upload

Build a multi-stage computer vision pipeline by connecting YOLO-NAS with S3 Upload and deploy a production application in minutes.

Deploy this Workflow

16,000+ organizations build with Roboflow

YOLO-NAS

YOLO-NAS is a type of Roboflow Object Detection Model.

Use YOLO-NAS in the Roboflow Object Detection Model Roboflow Workflows block.

S3 Upload

Send images and prediction files to AWS S3.

The Amazon S3 Integration block enables seamless integration with Amazon Simple Storage Service (S3), a scalable and durable cloud storage solution provided by Amazon Web Services (AWS). This block empowers you to store images and predictions to an S3 bucket directly from your workflow applications, providing a reliable and efficient solution for data storage and archival.

Deploy Workflows with a Hosted API or on the Edge

Use workflows with YOLO-NAS and S3 Upload in production

Build a Custom Vision AI Application

Connect pre-trained models, open source models, LLM APIs, advanced logic, and external applications. Deploy as an API endpoint, on-prem, or at the edge.

Explore Popular Combinations

This is some text inside of a div block.

YOLO-NAS to Active Learning Data Collector

Build a computer vision workflow that connects YOLO-NAS to Active Learning Data Collector.

YOLOv5 to S3 Upload

Build a computer vision workflow that connects YOLOv5 to S3 Upload.

YOLO-NAS to Kafka Publish

Build a computer vision workflow that connects YOLO-NAS to Kafka Publish.

YOLO-NAS to CSV Sink

Build a computer vision workflow that connects YOLO-NAS to CSV Sink.

YOLO-NAS to Azure Sink

Build a computer vision workflow that connects YOLO-NAS to Azure Sink.

YOLO-NAS to Webhook Publish

Build a computer vision workflow that connects YOLO-NAS to Webhook Publish.

How to Build a Workflow

Learn how to use a low-code open source platform to simplify building and deploying vision AI applications.

Choose a Block

Choose from 40+ pre-built blocks that let you use custom models, open source models, LLM APIs, pre-built logic, and external applications. Blocks can be models from OpenAI or Meta AI, applications like Google Sheets or Pager Duty, and logic like filtering or cropping.

Connect Blocks

Each block can receive inputs, execute code, and send outputs to the next block in your Workflow. You can use the drag-and-drop UI to configure connections and see the JSON definitions of what’s happening behind the scenes.

Deploy Workflows

You’ll receive an output of the final result from your Workflow and the format you want it delivered in, like JSON. Once your Workflow produces sufficient results, you can use the Workflow as a hosted API endpoint or self-host in your own cloud, on-prem, or at the edge.

Deploy Workflows at Scale

Roboflow powers millions of daily inferences for the world’s largest enterprises on-device and in the cloud

Deploy your Workflows directly on fully managed infrastructure through an infinitely-scalable API endpoint for high volume workloads

Run Workflows on-device, internet connection optional, without the headache of environment management, dependencies, and managing CUDA versions.

Isolate dependencies in your software by using the Python SDK or HTTP API to operate and maintain your Workflows separate from other logic within your codebase

Supported devices include ARM CPU, x86 CPU, NVIDIA GPU, and NVIDIA Jetson

Customize Your Pipeline

Connect models from OpenAI or Meta AI, applications like Slack or Pager Duty, and logic like filtering or cropping.

View All Blocks