semvec/pypi-packages huggingface dataset:
beth 0.2.0
Open source chess AI framework
License: MIT
Requires Python: >=3.7.8,<4.0.0

# ♟ Welcome to ``beth`` documentation

![](assets/beth_home.png)

``beth`` is an open source chess AI framework. Like many, I re-discovered the game of chess by watching the Netflix show **the Queen's Gambit**. As a Data Scientist, it made we want to learn and explore the beauty of the game. 

At first my goal was to develop algorithms to help me learn chess. But over time, it lead to developing more and more features. What you will find is my personal experiments open sourced as a chess framework. I hope this framework to be ideal for chess programmers in Python to ease the development of new algorithms and engines.


> This repo is under active development, many features are still experimental.
> But please fill free to fork or PR

## Installation
You can install the library from PyPi with: 
```
pip install beth
```
Or clone and install from source

## Features
- Definition of a game environment using ``python-chess`` framework, with move parsing, board-to-numpy abstractions, PGN records, move replay. 
- Playing chess in Jupyter notebooks with widgets 
- Different player abstractions: ``HumanPlayer()``, ``RandomPlayer()``, ``AIPlayer()`` - to play Human vs AI, Human vs Human, or AI vs AI. 
- Connection to Stockfis engine to evaluate engine performances, available with ``StockfishAI()`` object abstraction
- Rules-based engine ``TreeSearchAI()`` with minimax tree search, alpha beta pruning, move ordering and board heuristics (~ELO 1000)
- First attempt of ML engine with a LSTM Neural Network to predict next moves

### Next roadmap features
If you are interested, please drop an issue or a PR, or contact me by [email](mailto:theo.alves.da.costa@gmail.com). Meanwhile the roadmap for ``beth`` is:

- Implementing a GUI (or connecting to an existing one) to ease experimentation
- ELO or TrueSkill measurement for any engine
- Improving minimax engine speed
- Developing ML engines:
  - Self supervised learning with Transformers
  - Reinforcement Learning


## Repo Structure
```
- beth/
- data/
    - raw/
    - processed/
- docs/                             # Documentation folder and website (.md, .ipynb) using Mkdocs
- notebooks/                        # Jupyter notebooks only (.ipynb)
- tests/                            # Unitary testing using pytest
- .gitignore
- LICENSE                           # MIT License
- poetry.lock                       # Poetry lock file
- pyproject.toml                    # Configuration file to export and package the library using Poetry
```
herbie-vision 0.1.6
Package for 2d object detection
License: MIT
Requires Python: >=3.5

# Herbie Vision
<p float="left">
  <img src="assets/herbie.jpg" width="300">
</p>

<H1>Introduction</H1>
<p>
In this project, we explore the challenges in maintaining and deploying an object detection model. The main goal of this work is to construct a machine learning system that is robust and strives for simplicity and ease of use. We demo the results of our system in the form of a web application that can easilt be deployed on the google cloud platform given the current repository structure.
<\p>
  
<p>  
This project is currently under construction 🏗, below you can find the current status of items we are working on:

MVP
- [x] Process and store Waymo data in Coco format on GCP
- [x] Train preliminary models on Waymo data
- [x] Implement Flask application to serve model results
- [x] Create Streamlit application to display results to users
- [x] Deploy web app and model serving application using kubernetes


Demo
- [ ] Add exploratory features to the web application
- [ ] Enhance the training and evaluation processes (submission of training jobs)
- [ ] Create script to compress and deploy model on Nvidia Jetson Nano
- [ ] Write report
<\p>

<H1>Data</H1>
<p>
There are two main sources of data for this project:

- **Waymo Dataset:** https://waymo.com/open/
- **Custom Datasets:** Generated using the Nvidia Jetson Nano
<\p>

<H1>Web Application</H1>
<img src="/assets/webapp.gif?raw=true" width="800px">
PyramidBuilder 0.0.5
Auto compiles HTML, CSS and JS into one file Pyramid App.
License: MIT

# PyramidBuilder
Make an pyramid app only by using HTML, CSS &amp; Javascript. This automatically creates code and configures the file.

As wrote above, anyone can easily develop an app using HTML, CSS and Javascript knowledge. You can use CSS, and Javascript if you want, else neglect them, pure html can also be used to develop an pyramid app, or more precisely a webapp.

- #### And make sure you have python installed on your device.

### Github Repository At : https://github.com/ankitkumar-13/PyramidBuilder
### Issues can be sent at Github's Repository or dropped at : ankitkumar13122003@gmail.com

------------


>  
>Press the Start Menu Button.  
>Search by typing cmd.  
>Click on the app named Command Prompt



- Use the pip command :-
>On Windows :-  
>
>Type the following command :-  
>```cmd
>pip install PyramidBuilder
>```
- Using PyramidBuilder :-
>```cmd
>python -m PyramidBuilder
>```


# A Tutorial:-

## You can get this on : https://github.com/ankitkumar-13/PyramidBuilder
itils 0.1.0
A Python CLI for transforming images.
License: MIT
Requires Python: >=3.6,<4.0
Keywords: image,imaging,cli

# itils

[![security: bandit](https://img.shields.io/badge/security-bandit-yellow.svg)](https://github.com/PyCQA/bandit)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

A Python CLI for transforming images.

Powered by [plac](https://github.com/ialbert/plac) (CLI), [Wand](https://github.com/emcconville/wand) (images), and [halo](https://github.com/ManrajGrover/halo) (spinners).

## Usage

### Interactive mode

```text
itils -i
```

Run `quit` to close `itils`.

### `gslide` subcommand

<!-- poetry run itils gslide -h | pbcopy -->

```text
usage: itils gslide [-h] [-r PCT] input_img

Resize an image to be smaller than 25 megapixels for Google Slides.
The image can be resized using an explicit percentage as well.

positional arguments:
  input_img             The path to the image to be transformed.

optional arguments:
  -h, --help            show this help message and exit
  -r PCT, --resize PCT  The (explicit) percentage value (e.g., 70) to scale
                        both width and height. Values less than 100 reduce the
                        image size.
```

## Development

1. `poetry install`
2. `poetry shell`

## Notes

- `convert image.png -resize 70% smaller_image.png` ([documentation](http://www.imagemagick.org/script/convert.php)).
- ["Improve Windows Support"](https://github.com/manrajgrover/halo/issues/5) (open) issue (halo).