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
  • Assign Annotation Jobs
  • Provide Annotation Instructions
  • Job Notifications
  • Annotation Jobs Board
  • Job Details
  • Review Mode

Was this helpful?

  1. Annotate

Collaborate on Annotations

Now your entire team can help annotate. Including labeling statistics.

PreviousAutomated Annotation with Auto LabelNextAnnotation Insights

Last updated 1 year ago

Was this helpful?

Whether you have a small team working annotating hundreds of images or a large team working on millions, creating a dataset is about more than drawing boxes. A big part of annotation is in the process of getting an image from the real world into a trained model's stored knowledge that involves image collection, storage, organization, selection, assignment, annotation, and review.

Roboflow offers collaborative features that allow you to:

  • Divide work between multiple team members by assigning annotation jobs to anyone on the team

  • Organize images into batches as you upload them

  • Provide image annotation instructions to help guide work and ensure consistency

  • Get an at-a-glance view of annotation work in progress

  • See a historical timeline of all annotation work

  • Revert changes

  • Add comments to images and view image comment history

  • Send images with annotation issues back to team members for changes

  • Approve or reject annotations before including them in a dataset

Assign Annotation Jobs

You can divide annotation work amongst a team or assign it to specific people responsible for annotation. Assigning jobs to individual team members means you won't have to worry about stepping on each others' work if you're online at the same time.

You can choose to assign jobs to one or more people on your team and if you haven’t included a team member to your workspace yet, you can also invite them and assign an annotation job to be completed at the same time.

Provide Annotation Instructions

You can provide instructions to annotators from the Assign Images tab. Click "Add Instructions" to add instructions to a batch before assigning the batch to an annotator. When you have set your instructions, click "Assign Images".

Job Notifications

Once an annotation job has been assigned, a notification will alert your team members when there's work assigned to them.

Annotation Jobs Board

The annotations jobs board gives an at-a-glance view of the current state of your individually assigned jobs as they go through the annotation process.

To view statistics for a particular labeler, specify a value in the Labeler dropdown.

Job Details

Clicking on individual jobs on the annotation jobs board gives a more detailed view of the individual job and its progress. You can quickly see images that still need annotation and re-assign jobs to different team members as needed.

Review Mode

You can individually approve or reject annotated images and send them back to the annotator for rework when necessary. To do so, click on a batch of images. Then, navigate between the Approved, Rejected, and To Do tabs to view the state of images in a batch.

Example of an Advanced Annotation Workflow board that includes a review stage
Example of an annotation job seen in the default annotation workflow
Example image of an annotation job under review