Roboflow Docs
DashboardForum
  • Build Vision Models with Roboflow
  • Quickstart
  • Roboflow Enterprise
  • Workspaces
    • Create a Workspace
    • Delete a Workspace
    • Add Team Members
    • Role-Based Access Control
  • Usage Based Pricing
  • Workflows
    • Create a Workflow
    • Build a Workflow
    • Test a Workflow
    • Deploy a Workflow
    • Workflow Examples
      • Multimodal Model Workflow
    • Share a Workflow
      • Workflow Sharing Configuration
    • Advance Workflow Topics
      • JSON Editor
  • Datasets
    • Create a Project
    • Upload Data
      • Import Data from Cloud Providers
        • AWS S3 Bucket
        • Azure Blob Storage
        • Google Cloud Storage
      • Upload Video
      • Import from Roboflow Universe
    • Manage Batches
    • Search a Dataset
    • Create a Dataset Version
    • Preprocess Images
    • Create Augmented Images
    • Add Tags to Images
    • Manage Classes
    • Edit Keypoint Skeletons
    • Create an Annotation Attribute
    • Export Versions
    • Dataset Analytics
    • Merge Projects
    • Delete an Image
    • Delete a Version
    • Delete a Project
    • Project Folders
  • Annotate
    • Annotation Tools
    • Use Roboflow Annotate
      • Annotate Keypoints
      • Label Assist (AI Labeling)
      • Enhanced Smart Polygon with SAM (AI Labeling)
      • Smart Polygon (AI Labeling)
      • Keyboard Shortcuts
      • Comment on an Image
      • Annotation History
      • Similarity Search
      • Box Prompting (AI Labeling)
    • Automated Annotation with Auto Label
    • Collaborate on Annotations
    • Annotation Insights
    • Labeling Best Practices
  • Train
    • Train a Model in Roboflow
      • Train from Scratch
      • Train from a Universe Checkpoint
      • Python Package
      • Roboflow Notebooks (GitHub)
    • Train from Azure Vision
    • Train from Google Cloud
    • View Training Results
    • Evaluate Trained Models
    • Custom Training Notebooks
  • Deploy
    • Deployment Overview
      • Roboflow Managed Deployments Overview
    • Serverless Hosted API
      • Object Detection
      • Classification
      • Instance Segmentation
        • Semantic Segmentation
      • Keypoint Detection
      • Foundation Models
        • CLIP
        • OCR
        • YOLO-World
      • Video Inference
        • Use a Fine-Tuned Model
        • Use CLIP
        • Use Gaze Detection
        • API Reference
        • Video Inference JSON Output Format
      • Pre-Trained Model APIs
        • Blur People API
        • OCR API
        • Logistics API
        • Image Tagging API
        • People Detection API
        • Fish Detection API
        • Bird Detection API
        • PPE Detection API
        • Barcode Detection API
        • License Plate Detection API
        • Ceramic Defect Detection API
        • Metal Defect Detection API
    • Serverless Hosted API V2
    • Dedicated Deployments
      • How to create a dedicated deployment (Roboflow App)
      • How to create a dedicated deployment (Roboflow CLI)
      • How to use a dedicated deployment
      • How to manage dedicated deployment using HTTP APIs
    • SDKs
      • Python inference-sdk
      • Web Browser
        • inferencejs Reference
        • inferencejs Requirements
      • Lens Studio
        • Changelog - Lens Studio
      • Mobile iOS
      • Luxonis OAK
    • Upload Custom Weights
    • Download Roboflow Model Weights
    • Enterprise Deployment
      • License Server
      • Offline Mode
      • Kubernetes
      • Docker Compose
    • Model Monitoring
      • Alerting
  • Roboflow CLI
    • Introduction
    • Installation and Authentication
    • Getting Help
    • Upload Dataset
    • Download Dataset
    • Run Inference
  • API Reference
    • Introduction
    • Python Package
    • REST API Structure
    • Authentication
    • Workspace and Project IDs
    • Workspaces
    • Workspace Image Query
    • Batches
    • Annotation Jobs
    • Projects
      • Initialize
      • Create
      • Project Folders API
    • Images
      • Upload Images
      • Image Details
      • Upload Dataset
      • Upload an Annotation
      • Search
      • Tags
    • Versions
      • View a Version
      • Create a Project Version
    • Inference
    • Export Data
    • Train a Model
    • Annotation Insights
      • Annotation Insights (Legacy Endpoint)
    • Model Monitoring
      • Custom Metadata
      • Inference Result Stats
  • Support
    • Share a Workspace with Support
    • Account Deletion
    • Frequently Asked Questions
Powered by GitBook
On this page
  • Keypoint Skeletons
  • Skeleton Editor

Was this helpful?

  1. Datasets

Edit Keypoint Skeletons

Keypoint Skeletons are the definition for an object's points, edges, and symmetries. Only relevant for Keypoint Detection project types.

PreviousManage ClassesNextCreate an Annotation Attribute

Last updated 1 year ago

Was this helpful?

Keypoint Skeletons

Keypoint Skeletons are a necessary part of a Keypoint Detection project. The skeleton informs the number of keypoints in your objects, as well as their default positions, names, colors, and edges. Before labelling and set up your skeletons.

After adding the name for your class (the overall object name, such as person, or car), you will select Edit Keypoints.

Skeleton Editor

Click anywhere to create your first point, and name it. Then you can keep creating points, or select a point to create an edge, edit the color, or delete it.

Once you are done editing, click Save, and continue to upload and label your images. Your skeleton should show up inside the annotation bounding box.

See .

how to label Keypoints
go to your project Classes
Edit Keypoints button is on the Classes page
Visual representation of the Skeleton Editor