Connect Roboflow Keypoint Detection Model with Super Annotator

Build a multi-stage computer vision pipeline by connecting Roboflow Keypoint Detection Model with Super Annotator and deploy a production application in minutes.

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Roboflow Keypoint Detection Model

Run inference on a keypoint detection model.

Run inference on a keypoint detection model hosted on or uploaded to Roboflow. You can query any model that is private to your account, or any public model available on [Roboflow Universe](https://universe.roboflow.com). You will need to set your Roboflow API key in your Inference environment to use this block. To learn more about setting your Roboflow API key, [refer to the Inference documentation](https://inference.roboflow.com/quickstart/configure_api_key/).

Super Annotator

Enhance images with visual annotations based on detection predictions, combining bounding boxes and labels for clarity.

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.

Deploy Workflows with a Hosted API or on the Edge

Use workflows with Roboflow Keypoint Detection Model and Super Annotator 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

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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.

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