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Project Description

This is a Python implementation of Total Variation Denoising method proposed by Guy Gilboa.

Reduces the total-variation of the image. Filters out noise while preserving edges. Textures and fine-scale details are also removed.

Requirements

To run this code you need the following packages:

Everything but OpenCV can be installed via “pip install -r requirements“

Installation

To install everything just type:

pip install py-tvd

For manual installation:

python setup.py install

Probably you have to run it with sudo.

Testing

Test are provided via unittest.

To run them all:

nosetests

Examples

import cv2
from tvd import TotalVariationDenoising
import os

image = cv2.imread(os.path.dirname(__file__) + '/../assets/example.bmp')
image = cv2.cvtColor(image, cv2.COLOR_BGR2YCR_CB)
subject = TotalVariationDenoising(image[:, :, 0])
output = subject.generate()
cv2.imshow('Total Variation Denoising image', output / 255)
cv2.waitKey(0)
cv2.destroyAllWindows()

The conversion to YCbCr color space is optionally (sure?)

Release History

Release History

1.0

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
py-tvd-1.0.tar.gz (2.9 kB) Copy SHA256 Checksum SHA256 Source Nov 3, 2014

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