Picsellia
  • Picsellia
  • Getting started
    • Start using Picsellia
    • Create, annotate, review a Dataset
    • Create a new Dataset Version with merged labels
    • Train a custom Object Detection model
    • Train a custom Classification model
    • Deploy model in production (Tensorflow only)
    • Feedback loop - Send predictions from models to Datalake or Datasets
  • Data Management
    • Upload assets to your Lake
    • Edit Tags for Pictures
    • Create a Dataset
    • Add data to a Dataset
    • Create a new Dataset version
    • Configure your Labels
    • Import annotation from other Dataset version
  • Experiment Tracking
    • Initialize an experiment
    • Checkout an experiment
    • Log your results to Picsell.ia
    • Store your files to Picsell.ia
    • Evaluate your models
    • Retrieve and update your assets
    • Publish your model
    • Namespace
  • Hyperparameter tuning
    • Overview
    • Install Picsell CLI
    • Config
    • Launch your Hyperparameters tuning
  • Models
    • Model HUB
  • References
    • API Reference
    • Python SDK Reference
    • Python Training Reference
  • Organization
  • Website
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  • With the Platform
  • With Python SDK

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  1. Data Management

Add data to a Dataset

PreviousCreate a DatasetNextCreate a new Dataset version

Last updated 3 years ago

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With the Platform

In order to add assets to a dataset, you need to go to your "Datalake" page and select the assets that you want to add.

Then click on "add to dataset"

You can then select the target dataset to import assets

Then select the specific version to add images.

With Python SDK

pip install picsellia

First make sure that you have Picsellia Python package installed

then you will need to initialize the Client with your API Token, available in you profile page.

from picsellia.client import Client
clt = Client(api_token="your token")

you can now search for some assets on your lake with the datalake.fetch() method:

pictures = clt.datalake.picture.fetch(quantity=1, tags=['tag1'])

You can use Client.datalake.pictures.status() to vizualize the fetched assets

then you can add data to your dataset

clt.datalake.dataset.add_data(name='dataset2', 
                            version='latest',
                            pictures=pictures)

You can find a complete reference to the SDK .

here