Chainer で Lanczos 補間による画像二倍縮小層の実装

chainer-lanczos0.5x.py

import numpy as np
from chainer import Link
from chainer.functions import pad, convolution_2d

def lanczos(x, n):
    return 0.0 if abs(x) > n else np.sinc(x) * np.sinc(x / n)

class Lanczos2xDownsampler(Link):

    def __init__(self, n=3):
        super().__init__()
        ys = np.array([lanczos(i / 2 + 0.25, n) for i in range(-2 * n, 2 * n)])
        ys = ys / np.sum(ys)
        k = ys.reshape(1, n * 4) * ys.reshape(n * 4, 1)
        self.w = np.array([[k]], dtype=np.float32)
        self.n = n

    def __call__(self, x):
        b, c, h, w = x.shape
        p = self.n * 2 - 1
        h1 = x.reshape(b * c, 1, h, w)
        h2 = pad(h1, ((0, 0), (0, 0), (p, p), (p, p)), mode="symmetric")
        h3 = convolution_2d(h2, self.xp.array(self.w), stride=2)
        return h3.reshape(b, c, h // 2, w // 2)