https://github.com/ramesh-x/image-enhancer

Simple Image Enhancing Software to test image pre-processing functions..
https://github.com/ramesh-x/image-enhancer

custom-filter gui image-enhancement image-processing opencv pyqt4-interface python-3-5 python3 python3-5 python35 qthreads

Last synced: 19 days ago
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Simple Image Enhancing Software to test image pre-processing functions..

• Host: GitHub
• URL: https://github.com/ramesh-x/image-enhancer
• Owner: Ramesh-X
• License: mit
• Created: 2018-06-15T16:37:08.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-06-25T16:48:10.000Z (over 6 years ago)
• Last Synced: 2024-12-03T16:55:51.886Z (19 days ago)
• Topics: custom-filter, gui, image-enhancement, image-processing, opencv, pyqt4-interface, python-3-5, python3, python3-5, python35, qthreads
• Language: Python
• Homepage:
• Size: 783 KB
• Stars: 3
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        

# Image Enhancer

This application is an image enhancement application based on `OpenCV` and `PyQt4`. You can use this as a small image enhancement software for day-to-day work.

But I created this to do pre-processing for images before feeding into a Neural Network. You can open a sample image and do enhancements and note down the parameters. Then you can use them in your own application.

## Add Custom Filters

If you want a custom filter to be added other than the filters that are implemented here, you can do it too. You just need to create a new filter class by inheriting `filters/abstract_filter.py` class and add it to the `filters` folder. 
 Then after you start application the filter will automatically be there. You can find more details in the documentation of `filters/abstract_filter.py` file.

## Working with the application

* Click open image button and open a image file you want

* Right click on the list and add a filter(s) you want

* Click on a filter and then change the values of the sliders below to change the effect of the selected filter

* You can change the maximum and minimum values of the slider using the text boxes.

* You can mouse hover in the image to see the original image

* You can remove a filter by right clicking on a filter in the list

* Finally you can save your output image

Tested with PyQt4 with Python 3.5 and Python 2.7 (Master brach is with Python 3.5 support and for Python 2 there is another branch)

## Requirements

* Python

* PyQt4

* OpenCV 3.x

* Numpy

## Run the program

You can run the program by

```python

python main.py

```

Output of the application is shown below

![Main Window](./asset/main.png)