How to add data points to your project for processing


If you’ve already created your first project, you’re probably keen to get started processing some of your data. However, if you already have the correct outputs for any of your input data available (ground truth data), we recommend you upload that first. This will provide a solid foundation for super.AI to measure your project’s performance and better tailor the output to your expectations.

If you don’t have ground truth data available or you’ve already uploaded it, let’s get going.

Dashboard vs API

There are a few different ways to add data points to your project. The method you use will depend on the project type as well as how many data points you’re uploading.

Super.AI provides the following methods of adding data points for processing:

  • Via the dashboard: direct upload from your computer, providing a CSV or JSON file of URLs or inputting raw text
  • Via API: using cURL, the super.AI CLI, or Python

How to add data points through the dashboard

  1. Go to your super.AI dashboard
  2. Open the relevant project
  3. Click Upload data on the left of the page
  4. Choose how you would like to provide the data using the bar of buttons at the top of the page
  5. Input or upload your data
  6. There are two further options when you expand the Advanced settings:
  • Add tags to your data points. You can use tags to filter what appears in your work queue for review and download. Learn more on our How to use tags page.
  • You can choose not to add your data points to the queue immediately by checking the
    Park this data (don't queue for processing yet)
    box. Your data points will remain unqueued until you manually send them to the queue in the dashboard. This can be useful if you wish to submit a large number of data points but regulate how many are processed at a time (e.g., if you’re evaluating output accuracy before a large number are processed). For more information, you can see our Data point states page.
  1. Click Submit for processing at the bottom of the page

The dashboard enables you both to add individual data points and to bulk upload. You can bulk upload by putting all your data points in a JSON file (maximum JSON file size: 4 MB) or a CSV file or by dragging and dropping files in the UI.

You can view the newly submitted data points in your work queue by clicking Work queue in the left-hand menu.

How to add data points programmatically

In the dashboard, we provide code for adding data points programmatically using cURL, Python, and the super.AI CLI. If you're new to any or all of these methods, take a look at our Getting started with the super.AI API guides.

To find the dashboard code examples, follow these steps:

  1. Head your super.AI dashboard
  2. Open the relevant project
  3. Click Upload data in the left-hand menu
  4. Go to Via command line or Python
  5. You can copy and paste the code you find here. Make sure to replace the example input with your actual input data.

Our API reference contains detailed information on how to integrate with our API, which also allows you to retrieve job results, resubmit and cancel jobs, and manage your ground truth data and super.AI storage.


Hosting your files

When adding input data that includes files (e.g., images, videos, or audio) to your project, you have three options:

  1. Upload the files to your project directly. This occurs when submitting data points for processing via the dashboard and you choose From computer.
  2. Upload the files somewhere on the web, make them accessible under public URLs, and reference these URLs when adding your data
  3. Upload files to your super.AI storage and reference their private data:// URLs when adding your data

We recommend you use the super.AI storage option in the following scenarios:

  • Your project takes multiple inputs which need to be grouped together
  • You want to use the files multiple times, e.g., in different projects, without uploading them every time

If you want host your files with us, follow our How to upload data to storage guide.

How to delete data points

Deleting data points is a permanent, non-reversible way to remove data points from your work queue. This can be useful when you accidentally upload incorrect or corrupt data or data becomes irrelevant, e.g., when you change your task design.

How to delete a data point

  1. Open the super.AI dashboard
  2. Open the relevant project to bring up its work queue
  3. Open the details card for a data point by clicking on its row in the work queue
  4. Hit the Delete button near the top right
  5. Confirm that you want to permanently delete this data point

How to delete multiple data points

  1. Open the super.AI dashboard
  2. Open the relevant project to bring up its work queue
  3. Choose the data points and delete them. There are 3 ways to do this:
    • To delete all data points, open the Other actions dropdown and click Delete all
    • To delete all data points that match a filter, set a filter using the Filter button above the work queue, then open the Other actions dropdown and click Delete filtered
    • To manually select and delete data points, select them using the checkboxes on the left side of the work queue, then open the Other actions dropdown and hit Delete selected
  4. Confirm your decision by clicking Delete [x] forever in the dialogue


Deleting in progress data points

If you delete data points that are In progress, you may still incur charges for tasks that have been completed on them, even if the data point is not fully processed

What's next

Now you've got the ball rolling, you can keep an eye on your project's progress. If you haven't done so already, add some ground truth data, which will help our system hone the accuracy of your project's output.