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Good-GYM

yo-WASSUP/Good-GYM

AI-powered fitness assistant for real-time pose estimation, exercise counting, and workout feedback

GitHub

GraphCanon updated Sep 24, 2026 · GitHub synced Sep 24, 2026

41views this month

412 stars73 forksLast push Jul 2, 2026 Python MIT

Decision brief

Good-GYM offers real-time pose estimation and exercise counting with optional GPU acceleration but requires running from source for full benefits.

Good fit when

If you need real-time feedback on your workouts and can install dependencies directly, including Python and a webcam.
When you want to leverage optional CPU or GPU modes by installing the required libraries from source code.

Avoid when

Avoid if relying solely on pre-packaged EXE files as they only support CPU mode without potential for GPU acceleration.
Do not use if your deployment requires strict adherence to closed-source distribution, since running from source is needed for full functionality.

Observed Jul 17, 2026 · Source: enrich:decision_facts

Good-GYM alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Steady (83d since push); As of Sep 24, 2026
Provenance: Not a fork · Personal account; As of Sep 24, 2026
Security (OSV): 79 low (79 low); As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install Good-GYM

PyPI

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Good-GYM is an AI-driven fitness tracker that provides real-time pose estimation, counts repetitions of exercises, and offers feedback during workouts.

Capability facts

Languages: python
Source: github.language · Sep 24, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 24, 2026)

- Python 3.9

Source link

README

📋 Requirements Python 3.9 Webcam Windows/Mac/Linux : Runs on CPU by default. Optional GPU acceleration is available when running from source, but CPU is generally recommended. Installation 1. Clone and install 2. Run the application 2. Install CUDA runtime libraries through pip...

For agents

This page has a .md twin and JSON over the API.

/tools/yo-wassup-good-gym.md GET /api/graphcanon/tools/yo-wassup-good-gym GET /api/graphcanon/graph?tool=yo-wassup-good-gym