README.md

metadata

title: OCR_Projet05
emoji: 🔥
colorFrom: purple
colorTo: purple
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: true
short_description: Projet 05 formation Openclassrooms

projet_05

Déployez un modèle de Machine Learning

Organisation du projet

├── LICENSE            <- Open-source license if one is chosen
├── Makefile           <- Makefile with convenience commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default mkdocs project; see www.mkdocs.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── pyproject.toml     <- Project configuration file with package metadata for 
│                         projet_05 and configuration for tools like black
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.cfg          <- Configuration file for flake8
│
└── projet_05   <- Source code for use in this project.
    │
    ├── __init__.py             <- Makes projet_05 a Python module
    │
    ├── config.py               <- Store useful variables and configuration
    │
    ├── dataset.py              <- Scripts to download or generate data
    │
    ├── features.py             <- Code to create features for modeling
    │
    ├── modeling                
    │   ├── __init__.py 
    │   ├── predict.py          <- Code to run model inference with trained models          
    │   └── train.py            <- Code to train models
    │
    └── plots.py                <- Code to create visualizations

Code hérité réutilisé

• scripts_projet04/brand : charte graphique OpenClassrooms (classe Theme, palettes, YAML). Le module projet_05/branding.py en est la porte d'entrée et applique automatiquement le thème.
• scripts_projet04/manet_projet04/shap_generator.py : fonctions shap_global / shap_local utilisées par projet_05/modeling/train.py pour reproduire les visualisations SHAP.

---

---

title: Projet 05 emoji: 👀 colorFrom: indigo colorTo: green sdk: gradio sdk_version: 5.49.1 app_file: app.py pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

project_title

project_description
Explore the docs »

View Demo · Report Bug · Request Feature

Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. Contributing
6. License
7. Contact
8. Acknowledgments

About The Project

Here's a blank template to get started. To avoid retyping too much info, do a search and replace with your text editor for the following: github_username, repo_name, twitter_handle, linkedin_username, email_client, email, project_title, project_description, project_license

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Built With

• [][Python-url]
• [![SQL][SQL]][SQL-url]

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Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

• npm

  npm install npm@latest -g
  

Installation

pip install -r requirements.txt uvicorn app.main:app --reload

1. Get a free API Key at https://example.com
2. Clone the repo

   git clone https://github.com/github_username/repo_name.git
   

3. Install NPM packages

   npm install
   

4. Enter your API in config.js

   const API_KEY = 'ENTER YOUR API';
   

5. Change git remote url to avoid accidental pushes to base project

   git remote set-url origin github_username/repo_name
   git remote -v # confirm the changes
   

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Usage

Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.

For more examples, please refer to the Documentation

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Roadmap

• Feature 1
• Feature 2
• Feature 3
  • Nested Feature

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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Top contributors:

License

Distributed under the project_license. See LICENSE.txt for more information.

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Contact

Your Name - @twitter_handle - email@email_client.com

Project Link: https://github.com/github_username/repo_name

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Acknowledgments

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