https://github.com/rashadgarayev/2dconvolution

2D Convolution in Image Processing
https://github.com/rashadgarayev/2dconvolution

convolution-numpy image-processing-python kernels python-computer-vision

Last synced: 3 months ago
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2D Convolution in Image Processing

• Host: GitHub
• URL: https://github.com/rashadgarayev/2dconvolution
• Owner: RashadGarayev
• License: mit
• Created: 2020-02-10T13:36:56.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-02-11T17:57:52.000Z (over 5 years ago)
• Last Synced: 2025-01-27T16:47:40.205Z (5 months ago)
• Topics: convolution-numpy, image-processing-python, kernels, python-computer-vision
• Language: Jupyter Notebook
• Size: 3.29 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Convolution with Python(numpy and scikit-image)

To show objects distinctly using the deep learning which is the actively using for last years. In this subject I have tried to show how to apply functions , passing through active functions. In the near future, we will gain in-depth knowledge of the results we have obtained in addition to these codes by developing an artificial neural network with a numpy library

### Requirements

python 3   

numpy 1.13.3  

scikit-image  

matplotlib 2.1.0

## Installation ##

>

    $ cd 2DConvolution

    $ pip3 install -r requirements.txt

### Data Visualization using Matplotlib

### for linux

>

    $ sudo apt-get install build-essential

    $ sudo apt-get install qtcreator

    $ sudo apt-get install qt5-default 

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## Usage

  

```python3 main.py```  

![Conv](data/Conv1.png)

-------------------------------

![Conv](data/Conv.png)

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# Kernel

* filter 3x3 

![](data/algo.gif)

## Reference

* http://szeliski.org/Book/drafts/SzeliskiBook_20100903_draft.pdf

* https://en.wikipedia.org/wiki/Kernel_(image_processing)