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from PIL import Image
import numpy as np
import torch
from .view_base import BaseView
class SkewView(BaseView):
def __init__(self, skew_factor=1.5):
self.skew_factor = skew_factor
def skew_image(self, im, skew_factor):
'''
Roll each column of the image by increasing displacements.
This is a permutation of pixels
'''
# Params
c,h,w = im.shape
h_center = h//2
# Roll columns
cols = []
for i in range(w):
d = int(skew_factor * (i - h_center)) # Displacement
col = im[:,:,i]
cols.append(col.roll(d, dims=1))
# Stack rolled columns
skewed = torch.stack(cols, dim=2)
return skewed
def view(self, im):
return self.skew_image(im, self.skew_factor)
def inverse_view(self, noise):
return self.skew_image(noise, -self.skew_factor)
def make_frame(self, im, t):
im_size = im.size[0]
frame_size = int(im_size * 1.5)
skew_factor = t * self.skew_factor
# Convert to tensor, skew, then convert back to PIL
im = torch.tensor(np.array(im) / 255.).permute(2,0,1)
im = self.skew_image(im, skew_factor)
im = Image.fromarray((np.array(im.permute(1,2,0)) * 255.).astype(np.uint8))
# Paste on to canvas
frame = Image.new('RGB', (frame_size, frame_size), (255, 255, 255))
frame.paste(im, ((frame_size - im_size) // 2, (frame_size - im_size) // 2))
return frame
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