Pigeon

Integrate Pigeon, a lightweight and intuitive data annotation tool, with ZenML to effortlessly label your datasets directly within Jupyter notebooks. This integration simplifies the annotation process for text classification, image classification, and text captioning tasks, making it ideal for quick labeling during the exploratory phase of your ML projects.

Features with ZenML

• Seamless Integration with Jupyter Notebooks
  ‍Annotate your data without leaving your familiar Jupyter notebook environment, ensuring a smooth workflow.
• Easy Setup and Configuration
  ‍Installing and registering the Pigeon annotator with ZenML is a straightforward process, requiring minimal effort.
• Efficient Data Management
  ‍Utilize ZenML's annotator dataset commands to easily list, delete, and retrieve statistics for your annotated datasets.
• Streamlined ML Workflows
  ‍Incorporate Pigeon annotations seamlessly into your ZenML pipelines, enabling efficient data labeling within your ML workflows.

Main Features

• Ultra-lightweight and open-source
• Supports text classification, image classification, and text captioning
• Intuitive interface for quick and easy labeling
• Ideal for small to medium-sized datasets
• Facilitates collaborative labeling within Jupyter notebooks

How to use ZenML with Pigeon

from zenml.client import Client

annotator = Client().active_stack.annotator

annotations = annotator.launch(
    data=[
        'This movie was fantastic!',
        'I was disappointed by the ending of the book.'
    ],
    options=[
        'positive',
        'negative'
    ]
)

Additional Resources

• Explore the Pigeon Python package on PyPI