# grt を Homebrew でインストール

grt のインストール経路、実行ファイル、メタデータ、AI エージェント向けセキュリティノートを確認します。

## インストール

```sh
sudo av install brew:grt
```

追加のインストールコマンド:

### macOS

- Homebrew (100%):

```sh
brew install grt
```

  証拠: local Homebrew formula metadata

## パッケージ情報

- **パッケージキー:** brew:grt
- **パッケージマネージャ:** Homebrew
- **バージョン:** 0.2.4
- **ソース概要:** Gesture Recognition Toolkit for real-time machine learning
- **ホームページ:** <https://nickgillian.com/grt/>
- **リポジトリ:** <https://github.com/nickgillian/grt>
- **生成日時:** 2026-08-03T19:37:03+00:00

## 実行可能ファイル

- grt-lin-reg-tool (エイリアス)
- grt-log-reg-tool (エイリアス)
- grt-merge-tool (エイリアス)
- grt-mlp-tool (エイリアス)
- grt-rf-tool (エイリアス)
- grt-softmax-tool (エイリアス)
- grt-split-tool (エイリアス)
- grt-svm-tool (エイリアス)
- grt-test-tool (エイリアス)

## インストール挙動

- Bottle: 利用不可

## バージョンと鮮度

- ページ生成日: 2026-08-03
- マネージャ版: 0.2.4
## プロジェクトの歴史と使われ方

The Gesture Recognition Toolkit, or GRT, is an open-source C++ machine-learning toolkit for real-time gesture recognition. Its research paper and project documentation emphasize accessibility for non-specialists building interactive systems from sensor data.

### プロジェクトの歴史

GRT grew out of Nicholas Gillian and Joseph A. Paradiso's work at the MIT Media Lab Responsive Environments Group and was described in a 2014 Journal of Machine Learning Research paper. The paper presents it as a cross-platform C++ library for real-time gesture recognition, feature extraction, automatic gesture spotting, classification, regression, and clustering.

The GitHub repository was created in January 2014 and the public release stream on GitHub includes version 0.1.0 in February 2016, 0.2.0 in August 2016, and 0.2.4 in December 2016. The repository README describes both a C++ API and GUI, plus .grt and CSV data/model files.

### 採用の歴史

GRT found a niche in creative coding, interactive music, sensor interfaces, and human-computer interaction rather than broad systems administration. Its README lists extensions and users such as ofxGrt for openFrameworks, ml-lib for Max and Pure Data, and ESP, showing adoption through research and media-arts tooling.

### 使われ方

The Homebrew package exposes small command-line tools for common models and data preparation tasks, while the library itself is normally embedded in C++ projects. Users build pipelines from preprocessing, feature extraction, and classifier modules, train models from labeled sensor data, and run predictions in real time.

### パッケージ好きにとっての重要性

GRT is interesting in package-manager culture because it packages academic interactive-machine-learning work as a reusable native library plus command-line helpers. It sits at the boundary between research code, creative-coding ecosystems, and reproducible Unix installation.

### タイムライン

- 2014: GRT described in the Journal of Machine Learning Research.
- 2014: GitHub repository created for nickgillian/grt.
- 2016: GRT Version 0.1.0 published on GitHub releases.
- 2016: GRT Version 0.2.0 published.
- 2016: GRT Version 0.2.4 published.

### Related projects

- ofxGrt integrates GRT with openFrameworks.
- ml-lib uses GRT concepts in Max and Pure Data contexts.
- ESP is listed by the GRT project as an application using GRT as a backend machine-learning system.

### ソース

- <https://api.github.com/repos/nickgillian/grt>
- <https://api.github.com/repos/nickgillian/grt/releases?per_page=30>
- <https://github.com/nickgillian/grt>
- <https://nickgillian.com/grt/>
- <https://www.jmlr.org/papers/volume15/gillian14a/gillian14a.pdf>


## セキュリティノート

narrow executable package without higher-risk signals.

- **Geiger リスク:** グリーン / 低
- narrow executable package without higher-risk signals


## Combined YAML source

View the package source record on GitHub. [combined/grt.yml](https://github.com/mxcl/pkgdb/blob/main/combined/grt.yml)


## ソース

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- cross-ecosystem install command graph