Connect S3 Upload to other blocks to build a custom workflow
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.
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.
Build a computer vision workflow that connects YOLOv5 to S3 Upload.
Roboflow Instance Segmentation Model to S3 Upload
Build a computer vision workflow that connects Roboflow Instance Segmentation Model to S3 Upload.
YOLOv8 Classification to S3 Upload
Build a computer vision workflow that connects YOLOv8 Classification to S3 Upload.
YOLOv9 to S3 Upload
Build a computer vision workflow that connects YOLOv9 to S3 Upload.
Roboflow Classification Model to S3 Upload
Build a computer vision workflow that connects Roboflow Classification Model to S3 Upload.
YOLO-NAS to S3 Upload
Build a computer vision workflow that connects YOLO-NAS to S3 Upload.
How to Build a Workflow
Learn how to use a low-code open source platform to simplify building and deploying vision AI applications.
1
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.
2
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.
3
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.
Find Other Blocks in the Utility Category
No items found.
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.
