semvec/pypi-packages huggingface dataset:
kiwanocr 0.0.8
OCR single or multiple files
Requires Python: >=3.6

# KiwanOCR

This package takes a single PDF file or a list of PDF files and returns their content as a text file.

[<img alt="Kiwano fruit image" width="250px" src="https://www.eatwellwithgina.com/wp-content/uploads/2014/06/photo-2-1-533x400.jpg" />](https://www.google.com/)

- Requirements
- Methods

## Requirements

### ```pip install``` or ```brew install```
Make sure you have installed these dependencies:
- ```brew install tesseract```
- ```brew install poppler```
- ```pip pdf2images```

### ```import```
Import the following:
- ```from PIL import Image```
- ```import pytesseract``` ## python interface for tesseract
- ```import os``` ## navitage, create directories
- ```import shutil``` ## to delete the image folders with their imgs
- ```from pdf2image import convert_from_path``` ## to turn pdf to image
- ```import glob``` ## to glob files into a list
- ```from pathlib import Path``` ## to specify path to your files
- ```from natsort import natsorted, ns``` ## natural sorting
- ```import re``` ## for regex


## Methods

### Setup

1. ```pip install kiwanocr```.
2. ```from kiwano import ocr```

### OCR a single PDF
```ocr.ocr_file(file_name, output_file_name, language, resolution)```

#### Arguments
- file_name: as a string
- output_file_name: as a string
- language: default is English (use ```tesseract --list-langs``` to retrieve langague codes )
- resolution: default is 300 dpi (use integer value between 100 and 1200)

### OCR a list of PDFs
```ocr.ocr_files(list_name, output_file_name, language, resolution)```
- list_name: The only difference is to enter a list name

## Output

A ```.txt``` file is placed in a ```output``` folder.
ifCNV 0.2.1
ifCNV

# ifCNV : a novel isolation-forest-based package to detect copy number variations from various NGS datasets.

## Installation

### From PyPi (recommended)

Make sure you have python >= 3.6

```sh
$ python -version
Python 3.X.X
```

Install pip (https://pip.pypa.io/en/stable/installation/).

```sh
$ python -m ensurepip --upgrade
```

Install ifCNV (https://pypi.org/project/ifCNV/)

```sh
$ pip install ifCNV
```
rlhive 1.0.1
A package to support RL research
Requires Python: >=3.6

[![Python unit tests for Hive](https://github.com/chandar-lab/RLHive/actions/workflows/pull_request_ci.yml/badge.svg)](https://github.com/chandar-lab/RLHive/actions/workflows/pull_request_ci.yml) [![Black Linter](https://github.com/chandar-lab/RLHive/actions/workflows/linter.yml/badge.svg)](https://github.com/chandar-lab/RLHive/actions/workflows/linter.yml)

[**Installing**](#installing) | [**Tutorials**](#tutorials) | [**Contributing**](#contributing)

[![te](docs/hive.svg)](docs/hive.svg) 
# RLHive
RLHive is a framework designed to facilitate research in reinforcement learning. It provides the components necessary to run a full RL experiment, for both single agent and multi agent environments. It is designed to be readable and easily extensible, to allow users to quickly run and experiment with their own ideas.

The full documentation and tutorials are available at https://rlhive.readthedocs.io/.
## Installing
RLHive is available through pip! For the basic RLHive package, simply run 
``pip install rlhive``.

You can also install dependencies necessary for the environments that
RLHive comes with by running ``pip install rlhive[<env_names>]`` where 
``<env_names>`` is a comma separated list made up of the following: 
- atari
- gym_minigrid
- pettingzoo

In addition to these environments, Minatar and Marlgrid are also supported, but
need to be installed separately. 

To install Minatar, run
``pip install MinAtar@git+https://github.com/kenjyoung/MinAtar.git@8b39a18a60248ede15ce70142b557f3897c4e1eb``

To install Marlgrid, run
``pip install marlgrid@https://github.com/kandouss/marlgrid/archive/refs/heads/master.zip``

## Tutorials
- [Creating new agents](https://rlhive.readthedocs.io/en/stable/tutorials/agent_tutorial.html)
- [Using DQN/Rainbow Agents](https://rlhive.readthedocs.io/en/stable/tutorials/dqn_tutorial.html)
- [Using Environments/Creating new Environments](https://rlhive.readthedocs.io/en/stable/tutorials/env_tutorial.html)
- [Configuring your experiments through YAML files and command line](https://rlhive.readthedocs.io/en/stable/tutorials/configuration_tutorial.html)
- [Loggers and Scheduling](https://rlhive.readthedocs.io/en/stable/tutorials/logging_tutorial.html)
- [Registering Custom RLHive Objects](https://rlhive.readthedocs.io/en/stable/tutorials/registration_tutorial.html)
- [Using Replay Buffers](https://rlhive.readthedocs.io/en/stable/tutorials/replay_tutorial.html)
- [Single/Multi-Agent Runners](https://rlhive.readthedocs.io/en/stable/tutorials/runner_tutorial.html)


## Contributing
We'd love for you to contribute your own work to RLHive. Before doing so, please read our 
[contributing guide](https://rlhive.readthedocs.io/en/stable/contributing.html).