3. What do you want to achieve with Picsellia ?
Objectives:
- Understand the platform philosophy
- Understand the platform structure
- Use the Quick Start Guide properly depending on your needs
1. Picsellia's philosophy
Picsellia's mission is to empower technical teams to upgrade their Computer Vision Models into Remarkable Computer Vision pipelines.
With Picsellia, AI teams can Structure, Build & Observe their CV pipelines.
- Structure: Increase AI team time spent on high-value tasks by +33% to unleash collective intelligence.
- Operate: Create & Deploy CV models 3X time faster, with scalable infrastructures and automation.
- Observe: Gain actionable insights in seconds with full ML observability & experiment traceability.
You can leverage all the features available on the Picsellia platform to achieve this goal.
2. Platform's structure
The platform is divided into 3 main parts:
- Data Management (upload
Data
, createDataset
) - Data Science (train your
Model
and assess their quality) - Model Operations (Deploy, monitor, and retrain your
Model
automatically)
3. Your needs
Depending on your needs, your goals, and the material you already have, there are different ways to start using Picsellia:
- You have your data but no
Model
trained yet โ Start here - You have a ready-to-be-used
Model
and associated trainingData
โ Start here
4. Vocabulary
Before deepening dive into the documentation, here is a bit of vocabulary used on the Picsellia platform:
Datalake
Unique & shared place gathering allData
(images) related to an OrganizationData
An image & associated Metadata contained in theDatalake
DataTag
AdditionalMetadata
that can be assigned to one or severalData
in order to organize aDatalake
Dataset
A placeholder for multipleDatasetversion
DatasetVersion
A subset ofData
inherited from theDatalake
that will be annotated to be used later for aModelVersion
trainingAsset
An image & associated Metadata contained in aDatasetVersion
, each asset is linked to itsData
from theDatalake
.AssetTag
AdditionalMetadata
that can be assigned to one or severalAsset
in order to organize aDatasetVersion
Label
An object that will store a class name and an id.Annotation
A set ofShapes
annotated by one person.Shape
An annotated object can be a classification, a rectangle, a polygon, a line, or a point.
Updated 24 days ago