👉 The Annotation Fluid is a flexible annotation framework designed to enhance the clarity and consistency of annotations in machine learning datasets. It allows annotators to mark data points with multiple labels, representing the nuanced relationships and complexities often present in real-world data. Unlike traditional binary or multi-label approaches, Annotation Fluid supports fine-grained annotations, enabling annotators to specify the exact boundaries and relationships between different classes or categories. This fluidity is particularly useful in tasks like image segmentation, where objects can overlap or have ambiguous boundaries, or in natural language processing, where context and intent play significant roles. By accommodating these complexities, Annotation Fluid helps create richer, more accurate datasets that better reflect the intricacies of the data being analyzed.
