1. Create a Private Processing

Now it's time to create your own Processing ! To show you the process, we are going to start from scratch and create a Processing that performs simple data-augmentation and put the augmented Data in a new DatasetVersion.

Let's go to our Processing page and create a new one.

Let's describe the different fields:

  • As our Processing is going to simply rotate images, we give it a simple yet clear name rotate-image
  • We give it a little description explaining the action performed by our script
  • We set the task to data augmentation our script enters in this category
  • As our processing is of type data augmentation, it will automatically create a new DatasetVersion to host the augmented image. When you will launch it, you will be prompted to enter a name for this new DatasetVersion.
  • We could set a DatasetVersion Type Constraint, which means that the type of the DatasetVersion created automatically will already be set to the chosen Detection Type. Here we choose to leave it not configured.
  • We don't have any parameters for our script so we leave the default parameters empty.
  • As this script will not require much computing resource, you can leave the default execution requirements to 8 CPUs and 0 GPUs. (Change this value based on the needs of your code)
  • And finally, as the Processing will be packaged in a Docker image (see the next part of the tutorial), we have to enter its future details.
    • As I'm pushing in the Public Docker Hub, my Docker Image name is my Docker username followed by the chosen name for our Processing. Here it is processing-rotate
    • I will set the Image tag to 1.0, you could have many tags for the same image, just enter the correct one.
    • We could add some flags to the Docker Run command but here we don't need anything so we leave this empty.

And that's it! Now you can just click Create and see our brand new Processing is available on Picsellia πŸŽ‰

Now, move on to the next part of the tutorial to see how to Build and Package your own Processing and push it to a Docker Registry.