Collaborative Workflow
Now your entire team can help annotate. Including labeling statistics.
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.
In February 2022, Roboflow reimagined the annotation workflow by adding 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
- Have a way to revert changes
- Add comments to images and view image comment history
- Send images with annotation issues back to team members for changes - (Advanced workflow only)
- Approve or reject annotations before including them in a dataset - (Advanced workflow only)
Best of all, most of these new features are available for free to all Roboflow users on our existing plans! If you'd like to add access to the Advanced Annotation Workflow for your team, contact your account rep.
Image Batches are a rudimentary way to upload, categorize, and store images in different buckets that can be immediately used to group and assign to different team members to annotate or store and pull from later.
By default, the image batches are uniquely named by the specific date and time uploaded but the name can be anything that helps your workflow.
Example image of batches named for a specific workflow
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 1 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.
It's important that your annotators are all on the same page, so we've added an instructions pane for passing messages to your teammates.
Once an annotation job has been assigned, a notification will alert your team members when there's work assigned to them. This should help streamline the collaboration process.
Example of email notification a team member may get indicating they have an annotation job in Roboflow
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.
View jobs by assigned Labeler or Reviewer
Example of an Advanced Annotation Workflow board that includes a review stage
View stats by Labeler
If you'd like to add access to the Advanced Annotation Workflow for your team, contact your account rep.
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.
Example of an annotation job seen in the default annotation workflow
It's important to carefully curate the ground truth that enters your training dataset so we've added an additional "review" step for teams that want more advanced controls to be able to make sure a second set of eyes checks your annotators' work. You can individually approve or reject annotated images and send them back to the annotator for rework when necessary.
Example image of an annotation job under review
Add Comments to images to increase collaboration among dispersed teams, personal notes for your records, or contracted labelers and your developers.
Select the 
, in the Labeling UI's toolbar to add Image comments.
Comment button, Filter Comments by Resolved, or Unresolved Comments.
Last modified 2mo ago