# Installer blockhash avec Homebrew, Nix

Consultez les chemins d'installation, exécutables, métadonnées et notes de sécurité de blockhash pour les workflows d'agents IA.

## installation

```sh
sudo av install brew:blockhash
```

Commandes d'installation supplémentaires:

### macOS

- Homebrew (100%):

```sh
brew install blockhash
```

  Preuve: local Homebrew formula metadata

### Linux

- Nix (92%):

```sh
nix profile install nixpkgs#blockhash
```

  Preuve: nixpkgs package indexes: pkgs/by-name/bl/blockhash/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1

## Faits du paquet

- **Clé du paquet:** brew:blockhash
- **Gestionnaire de paquets:** Homebrew
- **Version:** 0.3.3
- **Résumé source:** Perceptual image hash calculation tool
- **Page d'accueil:** <https://github.com/commonsmachinery/blockhash>
- **Dépôt:** <https://github.com/commonsmachinery/blockhash>
- **Dernière mise à jour:** 2026-07-06T11:06:08Z
- **Généré:** 2026-08-03T19:37:03+00:00

## exécutables

- blockhash (alias)

## Comportement d'installation

- Bouteille: non disponible

## Version et fraîcheur

- page générée: 2026-08-03
- version du gestionnaire: 0.3.3
## Historique du projet et usages

blockhash is a small Commons Machinery command-line tool for computing perceptual image hashes. It packages the block mean value perceptual-hashing algorithm into a Unix-style utility that can hash one or more images from the shell.

### Historique du projet

The official README says blockhash is based on the algorithm described in 'Block Mean Value Based Image Perceptual Hashing' by Bian Yang, Fan Gu, and Xiamu Niu. GitHub metadata dates the repository to September 2014, and the README copyright line names Commons Machinery in 2014.

The release history shows v0.1 in December 2014, follow-up 0.2 releases in January 2017, v0.3 in November 2017, and later maintenance releases through v0.3.3 in January 2023.

### Historique d'adoption

blockhash has narrow but durable package adoption. The input metadata records Homebrew and Nix packages, which is enough for scripts and reproducible media-processing environments to depend on the CLI without building the ImageMagick-backed source manually.

### Modes d'utilisation

The README documents a direct CLI workflow: run `blockhash` with a list of images to calculate hashes, or `blockhash --help` for options. Building from source requires ImageMagick's MagickWand development library and the waf build script.

### Pourquoi les passionnés de paquets s'y intéressent

blockhash matters as a compact packaged implementation of perceptual hashing, useful for duplicate detection, image comparison, media archives, and content pipelines where cryptographic hashes are too brittle because visually similar images may have different bytes.

### Chronologie

- 2014: Official repository created and v0.1 released.
- 2017: 0.2 and v0.3 releases published.
- 2023: v0.3.3 maintenance release published.

### Related projects

- ImageMagick/MagickWand is the image-processing dependency named in the README.
- The underlying perceptual-hashing method comes from the block mean value image hashing paper cited by the README.
- Other perceptual-hash tools and media duplicate-detection pipelines are adjacent use cases.

### Sources

- GitHub repository metadata via gh api repos/commonsmachinery/blockhash
- <https://github.com/commonsmachinery/blockhash#readme>
- <https://github.com/commonsmachinery/blockhash/releases>
- source_facts.package-manager


## Notes de sécurité

broad file, network, media, or database tool signal.

- **Risque Geiger:** blue / moyen
- broad file, network, media, or database tool signal

## Autres enregistrements de gestionnaires de paquets

- Nix - blockhash: normalized package name match | nixpkgs package indexes: pkgs/by-name/bl/blockhash/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1


## Combined YAML source

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


## Sources

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