https://github.com/mgautam98/chitrapy

Mini Image Processing Library in Python with JIT Compiler for Fast computation.
https://github.com/mgautam98/chitrapy

hacktoberfest image-processing numba numpy python3

Last synced: about 1 month ago
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Mini Image Processing Library in Python with JIT Compiler for Fast computation.

• Host: GitHub
• URL: https://github.com/mgautam98/chitrapy
• Owner: mgautam98
• License: gpl-3.0
• Created: 2018-10-18T15:53:45.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2021-01-14T04:42:52.000Z (almost 4 years ago)
• Last Synced: 2024-10-09T13:13:31.578Z (about 1 month ago)
• Topics: hacktoberfest, image-processing, numba, numpy, python3
• Language: Jupyter Notebook
• Homepage:
• Size: 8.35 MB
• Stars: 6
• Watchers: 2
• Forks: 0
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# [NOT Supported Anymore]ChitraPy [![PyPI-Status](https://img.shields.io/badge/pypi-ChitraPy-blue)](https://pypi.org/project/ChitraPy) [![Build Status](https://travis-ci.com/mgautam98/ChitraPy.svg?branch=master)](https://travis-ci.com/mgautam98/ChitraPy)  [![codecov](https://codecov.io/gh/mgautam98/ChitraPy/branch/master/graph/badge.svg)](https://codecov.io/gh/mgautam98/ChitraPy) [![Documentation Status](https://readthedocs.org/projects/chitrapy/badge/?version=latest)](https://chitrapy.readthedocs.io/en/latest/?badge=latest) [![Downloads](https://pepy.tech/badge/chitrapy)](https://pepy.tech/project/chitrapy)

 

ChitraPy is a digital Image Processing Library in Python.

# Installation

Install ChitraPy with:

```

pip install ChitraPy

```

Find the latest version on PyPi  

https://pypi.org/project/ChitraPy

### Install Dev version

```

git clone https://github.com/mgautam98/ChitraPy.git

cd ChitraPy

python3 setup.py install

```

## Documentation

https://chitrapy.readthedocs.io/en/latest/

## Usage

```

from ChitraPy import filters, helpers

import matplotlib.pyplot as plt

# Load a sample Image

!wget https://i.imgur.com/D24n5DL.png

img = plt.imread('./D24n5DL.png')

plt.imshow(img)

# invert an image

invert = filters.invert(img)

plt.imshow(invert)

```

## Features

* Crop

* Grayscale

* Negative

* Sepia

* Hue

* Salt and Pepper

* Stretch

* Warp

* Rotate

* Invert

* Gaussian blur

* Quick Blur

* Contrast Enhancement (Histogram Equalization)

* Local Contrast Enhancement

* Add Watermark

* Sobel Edge detection

* Halftoning

* Dither

* resize

* sharpen

* Emboss

* Identity

* Outline

* Monochrome

* Zoom

* Contrast adjustment (Histogram sliding)

## References

* https://en.wikipedia.org/wiki/Digital_image_processing

* http://setosa.io/ev/image-kernels/

* http://www.tannerhelland.com/3643/grayscale-image-algorithm-vb6/

* https://www.cs.princeton.edu/courses/archive/fall00/cs426/lectures/dither/dither.pdf

* https://hypjudy.github.io/2017/03/19/dip-histogram-equalization/