https://github.com/anubhav-bhargava/blur-image-detection

https://github.com/anubhav-bhargava/blur-image-detection

Last synced: 5 days ago
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• Host: GitHub
• URL: https://github.com/anubhav-bhargava/blur-image-detection
• Owner: Anubhav-Bhargava
• Created: 2018-05-12T01:03:20.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-06-08T05:15:23.000Z (over 6 years ago)
• Last Synced: 2024-04-17T12:16:38.628Z (7 months ago)
• Language: Jupyter Notebook
• Size: 54.7 KB
• Stars: 4
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Image Blur Detection

This repo contains the code for Image Blur Classifcation. Two methods have been used to solve this problem:-

**Pre-requisites**

> The code is developed for Python 2.7 using Jupyter notebook

> All dependencies are mentioned in requirements.txt

**Laplacian Method**

This method is based on this [tutorial](https://www.pyimagesearch.com/2015/09/07/blur-detection-with-opencv/). 

The test accuracy achieved using this method for :-

1.NaturalBlurSet -> ~77%

2.DigitalBlurSet -> ~96%

**Deep Learning based Method**

This method uses Convolution Neural Network for the classification.

The test accuracy achieved using this method for :-

1.NaturalBlurSet -> ~61%

2.DigitalBlurSet -> ~62%

***Training***

The training was done on Google Colaboratory. The training data was saved in pickle files (generated using files pre-processing directory) and uploaded on the Cloud.

The final trained model weights were downloaded and tested againsta the evaluation set.

**Dataset**

It is trained on [CERTH Image Blur Dataset](http://mklab.iti.gr/files/imageblur/CERTH_ImageBlurDataset.zip)