Connect Super Annotator to other blocks to build a custom workflow
The `SupervisionAnnotatorBlock` serves as a pivotal component in workflows that require
visual demonstration of object detection, instance segmentation, and keypoint detection
results. This block is specifically designed to annotate images by overlaying
predictions directly onto them, thus enhancing the visual feedback for analysis,
review, or presentation purposes.
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 Using Super Annotator
Roboflow Instance Segmentation Model to Super Annotator
Build a computer vision workflow that connects Roboflow Instance Segmentation Model to Super Annotator.
YOLOv8 Instance Segmentation to Super Annotator
Build a computer vision workflow that connects YOLOv8 Instance Segmentation to Super Annotator.
YOLOv8 Keypoint Detection to Super Annotator
Build a computer vision workflow that connects YOLOv8 Keypoint Detection to Super Annotator.
YOLOv5 Instance Segmentation to Super Annotator
Build a computer vision workflow that connects YOLOv5 Instance Segmentation to Super Annotator.
Roboflow Classification Model to Super Annotator
Build a computer vision workflow that connects Roboflow Classification Model to Super Annotator.
YOLO-NAS to Super Annotator
Build a computer vision workflow that connects YOLO-NAS to Super Annotator.
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.
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.