GaitSetPy

Overview

GaitSetPy is a modular Python package for gait analysis and recognition, supporting both modern class-based and legacy function-based APIs. It provides tools for dataset loading, preprocessing, feature extraction, EDA, and machine learning classification—all organized with singleton managers and plugin-based extensibility.

Key Features

• Modular architecture with abstract base classes and managers
• Support for multiple gait datasets and feature extractors
• Preprocessing pipelines and EDA tools
• Machine learning models: Random Forest, MLP, LSTM, BiLSTM, GNN
• Extensible via plugin registration
• Available on PyPI: gaitsetpy

Example Workflow

from gaitsetpy import load_and_analyze_physionet, train_gait_classifier

data = load_and_analyze_physionet(data_dir='path/to/data')
features = data['features']

model = train_gait_classifier(features, model_type='random_forest')

Learn More

See the GitHub repository for documentation, examples, and source code.

Read the full API documentation.