Renumics Spotlight
Spotlight helps you to identify critical data segments and model failure modes. It enables you to build and maintain reliable machine learning models by curating a high-quality datasets.
Introduction
Spotlight is built on the idea that you can only truly understand unstructured datasets if you can interactively explore them. Its core principle is to identify and fix critical data segments by leveraging data enrichments (e.g. features, embeddings, uncertainties). We are building Spotlight for cross-functional teams that want to be in control of their data and data curation processes. Currently, Spotlight supports many use cases based on image, audio, video and time series data.
Quickstart
Get started by installing Spotlight and loading your first dataset.
What you'll need
- Python version 3.10 or higher
Install Spotlight via pip
pip install renumics-spotlight
We recommend installing Spotlight and everything you need to work on your data in a separate virtual environment
To use optional analyzers, install Spotlight with analyzers extra:
pip install renumics-spotlight[analyzers]
To use optional embeddings, install Spotlight with torch extra:
# CPU support
pip install --extra-index-url https://download.pytorch.org/whl/cpu renumics-spotlight[torch]
# Default installation
pip install renumics-spotlight[torch]
# Specific CUDA version support
pip install --extra-index-url https://download.pytorch.org/whl/cu128 renumics-spotlight[torch]
See torch installation for more details.
If you are using Spotlight with Hugging Face
datasetsof version 4 (current default), you'll also need to installtorchextra to use audio data and have FFmpeg installed on your system. See here for more details.
Load a dataset and start exploring
import pandas as pd
from renumics import spotlight
df = pd.read_csv("https://raw.githubusercontent.com/Renumics/spotlight/refs/heads/main/data/mnist/mnist-tiny.csv")
spotlight.show(df, dtype={"image": spotlight.Image, "embedding": spotlight.Embedding})
pd.read_csvloads a sample csv file as a pandas DataFrame.
spotlight.showopens up spotlight in the browser with the pandas dataframe ready for you to explore. Thedtypeargument specifies custom column types for the browser viewer.
Load a Hugging Face dataset
import datasets
from renumics import spotlight
dataset = datasets.load_dataset("olivierdehaene/xkcd", split="train")
df = dataset.to_pandas()
spotlight.show(df, dtype={"image_url": spotlight.Image})
The
datasetspackage can be installed via pip.
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