A processing is a piece of code (like a Python script) which interacts with your data on the platform on demand.
To explain this, let's start with a use case:
Let's say that you want to perform data augmentation on a Picsellia Dataset.
Normally, the steps to achieve this would be:
- Downloading your images locally
- Running a script with some data-augmentation techniques (like rotating the image for example) on all of your images
- Creating a new version of the Dataset you are using
- Uploading the augmented images to this new Dataset
We know it can feel a little bit overwhelming 😮💨 Although running a script can be considered an automatic task, this process is fully manual. In addition, you must be using a computer which is actually able to run the code (it has to be in the correct environment, etc...)
This is why we came up with Processings 🎉 To let you automate this process and launch it whenever you want, on the data you want, directly from the platform!
In this guide you will learn:
- How to use the most common Processings already available (handmade by Picsellia ❤️)
- How to create your own Data Processing
- Launch and track your Processings runs
- Package and push your code to be used in a Processing
- Make the most out of Processings with Parameters and Context
As of today, we have only released Data Processings (processings able to run on your datasets) so you can perform actions like:
- Pre-annotation with a Model
- Data Augmentation
- Smart Version Creations
- Or anything you can think of regarding your Data!
In the future, you will find Processings every part of Picsellia:
- Models (automatically optimize and convert model weights)
- Experiments (perform evaluation or run benchmarks)
- Deployments (compute Custom metrics...)
but that's just a tease for now 😉
Updated about 1 month ago