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/** | |
* Convert standard camera intrinsic and extrinsic parameters to a vtkCamera instance for rendering | |
* Assume square pixels and 0 skew (for now). | |
* | |
* focal_len : camera focal length (units pixels) | |
* nx,ny : image dimensions in pixels | |
* principal_pt: camera principal point, | |
* i.e. the intersection of the principal ray with the image plane (units pixels) | |
* camera_rot, camera_trans : rotation, translation matrix mapping world points to camera coordinates | |
* depth_min, depth_max : needed to set the clipping range |
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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. |