Universal Input2Image Library

A versatile Python library for transforming various types of input data into visual representations. This library provides a unified interface to convert different data formats (tabular data, time series, images, etc.) into meaningful visualizations.

Features

• Transform tabular data (CSV, DataFrames) into heatmap visualizations
• Convert time series data into line plots
• Process image data with various transformations
• Support for multiple input formats
• Easy-to-use API with consistent interface
• Customizable visualization parameters

Installation

You can install the library using pip:

pip install universal-input2image

Requirements

• Python >= 3.6
• numpy
• pandas
• matplotlib
• scipy
• scikit-learn
• networkx
• Pillow

Usage

Here's a quick example of how to use the library:

from universal_input2image import UniversalInput2Image

# Initialize the transformer
transformer = UniversalInput2Image()

# Transform tabular data from CSV
image = transformer.transform("path/to/your/data.csv", save_path='output.png')

# Transform DataFrame
import pandas as pd
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
})
image = transformer.transform(df, save_path='output.png')

# Transform time series data
import numpy as np
time_series = np.sin(np.linspace(0, 10, 100))
image = transformer.transform(time_series, save_path='output.png')

Examples

The repository includes several example scripts demonstrating different use cases:

1. Tabular data transformation
2. DataFrame visualization
3. Image processing
4. Time series visualization

Run the examples using:

python run_example.py

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Contact

For any questions or suggestions, please open an issue in the GitHub repository.