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@ -36,7 +36,7 @@ parser = argparse.ArgumentParser(description='Generate a new image by applying s
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formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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add_arg = parser.add_argument
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add_arg('files', nargs='*', default=[])
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add_arg('--zoom', default=4, type=int, help='Resolution increase factor for inference.')
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add_arg('--zoom', default=1, type=int, help='Resolution increase factor for inference.')
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add_arg('--rendering-tile', default=128, type=int, help='Size of tiles used for rendering images.')
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add_arg('--rendering-overlap', default=32, type=int, help='Number of pixels padding around each tile.')
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add_arg('--model', default='small', type=str, help='Name of the neural network to load/save.')
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@ -566,7 +566,7 @@ class NeuralEnhancer(object):
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img = np.transpose(image[y:y+p*2+s,x:x+p*2+s,:] / 127.5 - 1.0, (2, 0, 1))[np.newaxis].astype(np.float32)
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*_, repro = self.model.predict(img)
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output[y*z:(y+s)*z,x*z:(x+s)*z,:] = np.transpose(repro[0] + 1.0, (1, 2, 0))[p*z:-p*z,p*z:-p*z,:]
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print('.', end='')
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print('.', end='', flush=True)
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return scipy.misc.toimage(output * 127.5, cmin=0, cmax=255)
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