semvec/pypi-packages huggingface dataset:
big-pdf-into-images 0.1
A tool to convert PDF files into images, page by page.
License: MIT
Requires Python: >=3.6
Keywords: pdf, images, conversion, pdf2image

# pdf-to-pics
  
A Python project that converts PDF files into images (one image per page). This project utilizes the `pdf2image` library to extract pages from PDF files and save them as images for easier viewing and manipulation.
  
## Features
- Convert PDF pages into images.
- Save each page as an image file (JPG, PNG, etc.).
- Customizable output resolution and image format.
  
## Installation
  
### Prerequisites
- Python 3.7 or above.
- pip (Python package manager).
  
### Steps to Install
  
You can install the project in two ways:
  
#### Option 1: Install via pip
  
1. Install directly from PyPI using pip:
  
   ```bash
   pip install pdf-to-pics
   ```
  
#### Option 2: Clone the Repository
  
1. Clone the repository:
  
   ```bash
   git clone https://github.com/your-username/pdf-to-pics.git
   cd pdf-to-pics
   ```
  
2. Create a virtual environment:

   ```bash
   python -m venv venv
   ```
  
3. Activate the virtual environment:
   
   - On Windows:
     ```bash
     venv\Scripts\activate
     ```
   - On macOS/Linux:
     ```bash
     source venv/bin/activate
     ```
  
4. Install required dependencies:
  
   ```bash
   pip install -r requirements.txt
   ```
  
## Usage
  
Once installed, you can use the command `big-pdf-into-images` to convert a PDF file into images.
    
### Options
  
- By default, the images are saved as PNG files with a resolution of 300 DPI. You can adjust these settings in the script.
  
  
## Dependencies
  
This project uses the following libraries:
  
- `pdf2image`: Convert PDF pages to images.
- `tqdm`: Display a progress bar during conversion.
- `click`: Command-line interface handling.
- `colorama`: Console text formatting.
- `pyfiglet`: Generate ASCII art for visual flair.
- `Pillow`: Image manipulation library for saving and processing images.
  
## Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your improvements or bug fixes.
  
  
## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
  
## Acknowledgments
- The `pdf2image` library for making PDF-to-image conversion easy.
- The Python community for providing excellent open-source libraries.
Topsis-Prarthana-102383015 1.0.0
TOPSIS Implementation
License: MIT

# Topsis Python Package

## Made By
Prarthana Samal (Roll Number 102383015)

## Description
The Topsis Python Package is a Python library that provides an implementation of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. TOPSIS is a multi-criteria decision-making method used to determine the best alternative among a set of alternatives based on their performance on multiple criteria.

## Installation
You can install this package using pip (if published to PyPI) or clone the repository directly:
```bash
pip install topsis-prarthana
```

## Usage
Use the following command to perform TOPSIS analysis on a dataset:

```bash
topsis.py data.csv "1,0,1,0,1" "+,-,+,-,+" output.csv
```

### Arguments:
- `data.csv`: Path to the input CSV file containing the dataset.
- `"1,0,1,0,1"`: Weights for each criterion separated by commas.
- `"+,-,+,-,+"`: Impacts for each criterion (either `+` for maximizing or `-` for minimizing).

## Input
![Screenshot 2025-01-18 120924](https://github.com/user-attachments/assets/6db1365f-5681-4d65-9064-d64a9bc47b1a)

## Output
![Screenshot 2025-01-18 120825](https://github.com/user-attachments/assets/0d806180-6b2a-498c-be85-e600a877ca4e)
Topsis-Varshini-102217252 1.0.0
TOPSIS implementation by Varshini Pallerla
License: MIT
Keywords: Topsis, main, Python, multiclassifier

# TOPSIS Python Package

Made By: **Varshini Pallerla**  
Roll No: **102217252**

## Description

The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision-making method used to rank alternatives based on their similarity to an ideal solution. The TOPSIS Python Package is a library that provides an easy-to-use implementation of this method, helps in selecting the best alternative from a set of alternatives based on their performance across multiple criteria.

## Installation

You can install the package using pip:
pip install topsis-varshinipallerla

## Usage

Use the following command to perform TOPSIS analysis on a dataset:

python topsis.py data.csv "1,0,1,0,1" "+,-,+,-,+" output.csv

- topsis.py: Python file with code
- data.csv: Path to the input CSV file containing the dataset.
- "1,0,1,0,1": Weights for each criterion separated by commas.
- "+,-,+,-,+": Impacts for each criterion (either + for maximizing or - for minimizing).

The output will be saved in a file named output.csv


## Output
<img width="407" alt="Screenshot 2025-01-18 120809" src="https://github.com/user-attachments/assets/5e7ed82d-ed73-4078-8223-92a633930941" />