Metadata-Version: 2.4
Name: pixrr
Version: 0.1.0
Summary: A lightweight image processing toolkit for Python
Author-email: Hrishikesh Tiwari <tiwarihrishikesh686@gmail.com>
License: MIT License
        
        Copyright (c) <2025> <Hrishikesh Tiwari>
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/Hrishi11572/pixrr
Project-URL: Documentation, https://github.com/Hrishi11572/pixrr/tree/main/docs
Keywords: image-processing,computer-vision,education,filters,numpy
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Image Processing
Classifier: Intended Audience :: Education
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=2.3.5
Requires-Dist: scipy>=1.16.3
Requires-Dist: matplotlib>=3.10.7
Requires-Dist: pillow>=12.0.0
Requires-Dist: numba>=0.63.1
Dynamic: license-file

# **pixrr : A lightweight image processing toolkit for python**

`pixrr` is a lightweight, beginner-friendly image processing library built for fast experimentation and teaching.
It focuses on simplicity, clean function names, and easy-to-understand code, making it useful both for quick image tasks and for pedagogical environments such as introductory image processing courses.

---

##  Features (Planned & Implemented)

### **Core Utilities**

* Convert color images to grayscale and binary
* Basic I/O helpers (read, write, display)
* Plot and analyze histograms
* Image thresholding
* Image Cropping and Rotation (planned)

### **Filtering & Enhancement**

* Convolution using masks
* Convolution using FFT (planned)
* Contrast enhancement
* Histogram equalization
* Smoothing filters (Gaussian, median, weighted median)
* Sharpening and Laplacian operators

### **Edge and Gradient Detection**

* Prewitt and Sobel (horizontal & vertical)
* Second-order derivatives
* Canny edge detector (planned)

### **Segmentation & Classification**

* Otsu thresholding 
* K-means clustering for image segmentation
* Mean-Shift clustering (planned)
* EM/Bayesian pixel classification (planned)

---

## Project Roadmap

| Stage  | Goal                                                    |
| ------ | ------------------------------------------------------- |
| Part 1 | Basic conversions, contour extraction, histogram tools  |
| Part 2 | Convolution, enhancement techniques, gradient operators |
| Part 3 | Automatic segmentation & clustering                     |
| Part 4 | Advanced edge detection and EM classification           |

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## Installation (when it’s live)

```bash
pip install pixrr
```

*(Currently under development. Not on PyPI yet.)*

---

## Usage Example

```python
import pixrr as pix

# Example 
img = pix.handle_image("peda_img/test_images/test2.png")
grey = pix.convert_to_gray(img)
# Applying gaussian
pix.show_image(pix.gaussian_smoothing(grey, kernel_size=3))
```

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## Contribution

This library is early-stage but open to improvements, bug reports, and algorithm implementations.
Ideal for students learning image processing or developers wanting simple utilities without heavy dependencies.

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