ClassKit

ClassKit is the classification and embedding toolkit, launched via classkit.

Purpose

Build identity classifiers from animal crops using embedding models, clustering, and active learning.

Launch

classkit

Workflow

1. Create or open a project with source image directories.
2. Ingest and embed crops using a backbone model.
3. Cluster embeddings and visualize with UMAP.
4. Label identity classes manually or via AprilTag auto-labeling.
5. Train a classification head and evaluate results.
6. Export labeled datasets for downstream use.

Key Features

• Embedding extraction with configurable backbone models
• UMAP-based dimensionality reduction and visualization
• FAISS-powered similarity search and clustering
• AprilTag auto-labeling for marker-based identity assignment
• Active learning for efficient labeling
• Export to Parquet/CSV, ImageFolder, and Ultralytics classification formats