semvec/pypi-packages huggingface dataset:
sort-my-face 0.1.2
Un outil de tri d'images par reconnaissance faciale.
Requires Python: >=3.8

# INFOB318-template

Acronyme: FS_01
Titre: sort_my_face
Client(s) :Jerome Fink
Ã‰tudiant: Keunang Tchatchou Farida

# ðŸ“Œ sort_my_face

**Description :**

sort_my_face un outil en ligne de commande ergonomique 
permettant de trier des photos contenant des visages d'humains. Sur base d'un dossier 
contenant des photos, l'application sortira un dossier contenant N sous dossier chacun 
correspondant Ã  un visage unique et contenant les photos sur lesquels ce visage apparait.


l'application permet notament de choisir le modÃ¨le d'IA a utiliser : entre la distance euclidienne notÃ©e ED
et le cosinus notÃ© COS .

il est egalement possible de choisir le seuil type de modÃ¨le de tri permettant de rendre la recherche plus ou moins concise .
les differentes valeurs du seuil sont :
    - "strict" : permettant une classification beaucoup plus pointue et meticuleuse.
    - "large" : permettant d'opter cette fois ci pour un tri plus souple .
    -  none ,valeur par defaut : lorsque pas precisÃ© , une valeur par defaut est attribuÃ©e au seuil pour le tri.
    

## ðŸš€ Installation

## PrÃ©requis
- Python 3.8+
- DÃ©pendances requises listÃ©es dans `requirements.txt`

## Ã‰tapes d'installation
lancer la commande "pip install sort_my_face" dans le terminal.
#installer les DÃ©pendances
pip install -r requirements.txt


### ðŸŽ¯ Utilisation
Apres installation , vous pouvez utiliser sort_my_face via le terminal avec la commande suivante :

bash
sort_my_face "C:\Users\X1 Yoga\Desktop\moi\photos_to_test" --seuil_type strict --ia_model ED
Â´Â´Â´Â´

### Explication des paramÃ¨tres
- **`/chemin/vers/le/dossier_a_traiter`** : Chemin du dossier contenant les photos Ã  trier.
- **`--seuil`** : Niveau de filtrage des visages (options : `strict`, `large`, none par defaut).
- **`--ia_model`** : ModÃ¨le d'intelligence artificielle utilisÃ© pour la reconnaissance (`ED`, `COS`,  none par defaut).

Exemple :
```bash
python -m sort_my_face ~/Images/photos_to_test --seuil strict --modele ED
```

## ðŸ“Œ Technologies utilisÃ©es
- Python 3.8+
- OpenCV
- TensorFlow / PyTorch (selon le modÃ¨le IA utilisÃ©)


#### ðŸ“œ Licence
Ce projet est sous licence **MIT**.
awslabs.mcp-bedrock-kb-retrieval-expert 0.0.311803
An AWS Labs Model Context Protocol (MCP) server bedrock-kb-retrieval expert
Requires Python: >=3.13

# mcp-bedrock-kb-retrieval-expert

A Model Context Protocol (MCP) server for accessing Amazon Bedrock Knowledge Bases.

## Features

- Discover knowledge bases and their data sources
- Query knowledge bases with natural language
- Filter results by data source
- Rerank results

## Prerequisites

### Installation Requirements

1. Install `uv` from [Astral](https://docs.astral.sh/uv/getting-started/installation/) or the [GitHub README](https://github.com/astral-sh/uv#installation)
2. Install Python using `uv python install 3.13`

### AWS Requirements

1. **AWS CLI Configuration**: You must have the AWS CLI configured with credentials and an AWS_PROFILE that has access to Amazon Bedrock and Knowledge Bases
2. **Amazon Bedrock Knowledge Base**: You must have at least one Amazon Bedrock Knowledge Base with the tag key `mcp-multirag-kb` with a value of `true`
3. **IAM Permissions**: Your IAM role/user must have appropriate permissions to:
   - List and describe knowledge bases
   - Access data sources
   - Query knowledge bases

### Reranking Requirements

If you intend to use reranking functionality, your Bedrock Knowledge Base needs additional permissions:

1. Your IAM role must have permissions for both `bedrock:Rerank` and `bedrock:InvokeModel` actions
2. The Amazon Bedrock Knowledge Bases service role must also have these permissions
3. Reranking is only available in specific regions: us-west-2, us-east-1, ap-northeast-1, and ca-central-1

For detailed instructions on setting up knowledge bases, see:

- [Create a knowledge base](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-create.html)
- [Managing permissions for Amazon Bedrock knowledge bases](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-prereq-permissions-general.html)
- [Permissions for reranking in Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/rerank-prereq.html)

## Installation

Add the server to your MCP client config (e.g. for Amazon Q CLI MCP, `~/.aws/amazonq/mcp.json`):

```json
{
  "mcpServers": {
    "awslabs.mcp-bedrock-kb-retrieval-expert": {
      "command": "uvx",
      "args": ["awslabs.mcp-bedrock-kb-retrieval-expert"],
      "env": {
        "SHELL": "/usr/bin/zsh",
        "AWS_PROFILE": "your-profile-name"
      }
    }
  }
}
```

## Limitations

- Results with `IMAGE` content type are not included in the KB query response.
- The `reranking` parameter requires additional permissions, Amazon Bedrock model access, and is only available in specific regions.