def show_sample( test_A, test_B ):
figure_A = numpy.stack([
test_A,
autoencoder_A.predict( test_A ),
autoencoder_B.predict( test_A ),
], axis=1 )
figure_B = numpy.stack([
test_B,
autoencoder_B.predict( test_B ),
autoencoder_A.predict( test_B ),
], axis=1 )
figure = numpy.concatenate( [ figure_A, figure_B ], axis=0 )
figure = figure.reshape( (4,7) + figure.shape[1:] )
figure = stack_images( figure )
figure = numpy.clip( figure * 255, 0, 255 ).astype('uint8')
cv2.imwrite( '_sample.jpg', figure )
def show_sample(self, test_A, test_B):
figure_A = numpy.stack([
test_A,
autoencoder_A.predict(test_A),
autoencoder_B.predict(test_A),
], axis=1)
figure_B = numpy.stack([
test_B,
autoencoder_B.predict(test_B),
autoencoder_A.predict(test_B),
], axis=1)
figure = numpy.concatenate([figure_A, figure_B], axis=0)
figure = figure.reshape((4, 7) + figure.shape[1:])
figure = stack_images(figure)
figure = numpy.clip(figure * 255, 0, 255).astype('uint8')
if self.arguments.preview is True:
cv2.imshow('', figure)
if not self.arguments.preview or self.arguments.write_image:
cv2.imwrite('_sample.jpg', figure)