Roboflow Docs
DashboardResourcesProducts
  • Documentation
  • Developer Reference
  • Changelog
  • Roboflow Documentation
  • Quickstart
  • Workspaces
    • Workspaces, Projects, and Models
    • Create a Workspace
    • Manage Team Members
    • Role-Based Access Control
    • Usage Based Pricing
    • Delete a Workspace
  • Workflows
    • Create a Workflow
    • Build a Workflow
    • Test a Workflow
    • Deploy a Workflow
    • Workflow Examples
      • Multimodal Model Workflow
    • Share a Workflow
  • Datasets and Labeling
    • 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 Datasets
      • Dataset Batches
      • Search a Dataset
      • Set Dataset Classes
      • Add Tags to Images
      • Create an Annotation Attribute
      • Delete an Image
    • Dataset Versions
      • Create a Dataset Version
      • Preprocess Images
      • Augment Images
      • Delete a Version
      • Export a Dataset Version
    • Dataset Analytics
    • Merge Projects
    • Delete a Project
    • Project Folders
    • Make a Project Public
  • 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)
    • Auto Label
    • Collaborate on Annotations
    • Edit Keypoint Skeletons
    • Annotation Insights
  • Train
    • Train a Model
      • Train from a Universe Checkpoint
      • Train from Azure Vision
      • Train from Google Cloud
    • View Training Results
    • View Trained Models
    • Evaluate Trained Models
  • Deploy
    • Deploy a Model or Workflow
      • 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
      • Create a Dedicated Deployment
      • Make Requests to a Dedicated Deployment
      • Manage Dedicated Deployments with an API
    • SDKs
      • Python inference-sdk
      • Web Browser
        • inferencejs Reference
        • inferencejs Requirements
      • Lens Studio
        • Changelog - Lens Studio
      • Luxonis OAK
    • Upload Custom Model Weights
    • Download Model Weights
    • Enterprise Deployment
      • License Server
      • Offline Mode
      • Kubernetes
      • Docker Compose
    • Monitor Deployed Models
      • Alerting
  • Support
    • Share a Workspace with Support
    • Account Deletion
Powered by GitBook
On this page
  • Managing Batches
  • Deleting a Batch

Was this helpful?

  1. Datasets and Labeling
  2. Manage Datasets

Dataset Batches

Batches are groups of images and labels that you can track across your annotation dashboard.

PreviousManage DatasetsNextSearch a Dataset

Last updated 19 hours ago

Was this helpful?

Once you into Roboflow, that data you uploaded turns into a batch. They're a group of images, so you can easily track them through the dataset process in Roboflow. You can view this process on the Annotate page.

Managing Batches

  • Once images are uploaded, they are in the Unassigned column.

  • You can assign the batch for someone to annotate, sending it to the Annotating column.

    • You can assign a portion, in which case the excess is put into a new batch in Unassigned

  • Once they are annotated, they are sent to Review (for users with Review Mode available) or to the Dataset column.

  • If batches are in the Review column, some or all are either approved or rejected. Approved batches will go into the Dataset column. Rejected batches are sent back to the Annotating column

Deleting a Batch

Keep in mind that deletions are permanent and irreversible. Please make sure you are confident deleting the project.

You can delete batches by clicking on the three dots next to the batch name and clicking "Delete Batch".

You can only delete a batch in the Unassigned column. If the batch you want to delete is in the Annotating, Review or Dataset column, you will have to click Move to unassigned before clicking Delete Job.

upload your data
The view in the Annotate page. Note: The review column may not be available for Public users.