Start Here

We know you're eager to start labeling your data so we made this quick start guide that covers the basics! For more in-depth feature guides explore the topics on the left, or use the search bar above.
Questions? Contact us at [email protected]​
1. Accept your invitation or create an account
Private cloud/enterprise users will log in with a provided sign-in URL to log into their account. Please contact support if you have completed the deployment process to your private cloud but have not received the link.
Accept an Invite
If you've been invited to join an existing Plainsight account via an email invitation, be sure to accept your invitation by clicking the Verify Email link the your email.
Sign Up
If you are creating your own Plainsight an account or organization for the first time, you can sign up here. 
Log In
If you are part of an organization using Plainsight, be sure your organization does not already have an account that they can invite you to.
Log in to your Plainsight web account at app.plainsight.ai. For enterprise users, you will log in through your own sign-in URL.
Before logging in for the first time, you should have received a verification email. Be sure to verify your email address by clicking the Verify Email button.
2. Create a Dataset & Add Sources
When you log in, you will be taken to the Datasets list.
From here you can create a dataset:
1.Click "Create New" to add a new dataset
2.Give the dataset a name
3.Click "Save & Continue to Sources"
4.Click "Add Data" to select which type of datasource to add and fill in the setup details. Repeat for each source.
5.When finished, click "Save & Continue to Label Definitions"
3. Create Label Definitions
Define the types of labels you will use in your dataset.
1.Type label name in "Label Name" field
2.Select label type from "Type" dropdown
3.Select label color from color chooser (if applicable)
4.Click "Save" button
5.Repeat as needed for multiple labels
When you're finished, scroll down and click "Save & Start Labeling"
4. Label Images
1.Select desired label from panel
2.Apply Label to Image (Application will vary by label type)
3.Click "Submit" button
4.Repeat for each image 
See Labeling Data for more about the labeler navigation & shortcuts.
5. Review, then Export or Train
Review your labels
1.Click the "Review" tab
2.Approve or reject images in the list
Train a model in Plainsight
1.Go to the "Versions" tab
2.Lock your dataset. If there are any unapproved labels, you will be prompted to auto-approve all.
3.Select the desired model options for your training run:
Dataset and version. Only locked versions can be used.
Labels to be used in training. A model is trained on only one label type.
Training length, between 1-24 hrs. This is the amount of time spent training your model. Read more about Training Time.
4.Click "Save & Start Training"
Only Rectangles (Bounding Box), Polygons (Instance Segmentation and Semantic Segmentation), Classification, and Regression label types are currently supported in SmartML training. Other label types can be exported and trained outside of Plainsight.
Your model will begin training shortly. You will be notified by email or in-app notification when it is ready.
Export your annotations for training outside of Plainsight
1.Go to the "Versions" tab
2.Lock your dataset. If there are any unapproved labels, you will be prompted to auto-approve all.
3.Select desired format for export
4.Select or de-select desired label types to export 
5.Click "Export Now"
You will be notified by email and in-app notification when your export is ready. The labeled data will be available in a zip file for download.
Your data is now ready to use in your own project!  

Last modified 9mo ago