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chsasank/elastic_transform.py

Forked from fmder/elastic_transform.py
Last active Oct 12, 2020
Elastic transformation of an image in Python
 import numpy as np from scipy.ndimage.interpolation import map_coordinates from scipy.ndimage.filters import gaussian_filter def elastic_transform(image, alpha, sigma, random_state=None): """Elastic deformation of images as described in [Simard2003]_. .. [Simard2003] Simard, Steinkraus and Platt, "Best Practices for Convolutional Neural Networks applied to Visual Document Analysis", in Proc. of the International Conference on Document Analysis and Recognition, 2003. """ assert len(image.shape)==2 if random_state is None: random_state = np.random.RandomState(None) shape = image.shape dx = gaussian_filter((random_state.rand(*shape) * 2 - 1), sigma, mode="constant", cval=0) * alpha dy = gaussian_filter((random_state.rand(*shape) * 2 - 1), sigma, mode="constant", cval=0) * alpha x, y = np.meshgrid(np.arange(shape[0]), np.arange(shape[1]), indexing='ij') indices = np.reshape(x+dx, (-1, 1)), np.reshape(y+dy, (-1, 1)) return map_coordinates(image, indices, order=1).reshape(shape)

chethanjjj commented Mar 15, 2017

 hey, just wondering what code did you use to load in the image?

chsasank commented Apr 17, 2017

 You can load using ``````from skiamge import io img = io.imread(filename) ``````

askerlee commented Oct 14, 2017 • edited

 Thanks for sharing. However an image is usually a 3-d array. This code seems to require the image is a 2-d array?

emma-sjwang commented Dec 18, 2017

 You can add a loop to achieve 3-D image.

pedroortizordep commented Jul 6, 2018

 Sorry about my poor knowledge, but you are using gaussian filter for what exactly?

developer0hye commented Oct 19, 2018

 Sorry about my poor knowledge, but you are using gaussian filter for what exactly? A c++ implementation can be found here Implementation of elastic distortion algorithm in C++ I wrote the reason why we use gaussian filter.

lequocgiom commented Mar 19, 2019

 Sorry about my question, but how to show the transformed image ?

Elaherahimkhani commented Nov 1, 2019

 for those who have trouble with using this code first, the image has to be square like: (x,x,3) second, for showing the transformed image ex: transformed_image=elastic_transform(img,40,2) then using plt.imshow(transformed_image)