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 Python SDK

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  1. Data Management

Edit Tags for Pictures

PreviousUpload assets to your LakeNextCreate a Dataset

Last updated 3 years ago

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With the Platform

Tags allow you to quickly search for pictures in your Lake

From your "Data lake" tab you can select the pictures on which you want to add or delete some tags.

Once pictures have been selected you can click on add or delete tags.

To delete a tag, you can click on "x" 🚀

Note that we do not allow tag edition, if you want to change the name of a tag, please delete it and then add another one with the desired name 🚨

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 some assets on your lake with de 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 or remove tags on the fetched assets

clt.datalake.picture.remove_tag(tags=['tag1'])
clt.datalake.picture.add_tag(tags=['tag2'])

You can find a complete reference to the SDK .

here