In order to ease data scientists' lives and navigation across all the features of Picsellia, the platform has been divided into three main parts that handle each step of any Computer Vision project lifecycle.
- Data Management
- Data Science
- Model Operations
In this first main part of Picsellia, the purpose is to upload your raw images and at the end get the ideal
Dataset. Data management is composed of two main features which are
Dataset available on top of the left sidebar.
Datalake you will gather & organize all your
Data in a single and shared place.
Datalake subsets, you will then be able to create your
Datasets. Datasets management features will allow you to version, annotate, and process your different
You can create your own
Processingsand browse among the public ones in the Processings tab.
The Data Science part of Picsellia is mainly related to experiment tracking.
Projects feature available on the left sidebar, you'll retrieve all your different Data Science projects.
Project is composed of one or several
Experiment creation, you'll be able to launch the training of your
Model, assess the quality of the training through the Experiment Tracking dashboard, and evaluate the
Model performances in the evaluation interface.
Model Operations features are used to operate a ready-to-deploy
Models created with Picsellia or not.
Models are stored and versioned in your private
Registry, from here, you can deploy them on Picsellia serving infra or on your own infrastructure.
When deployed, keep trace and monitor your models in the Monitoring Dashboard accessible from the
Deployment tab, also available in the left sidebar.
Create your pipelines
Deployment, you can set your data pipeline up in order to retrain & redeploy continuously your
Updated 27 days ago