ade20k_loader.py 文件源码

def transform(self, img, lbl):
        img = img[:, :, ::-1]
        img = img.astype(np.float64)
        img -= self.mean
        img = m.imresize(img, (self.img_size[0], self.img_size[1]))
        # Resize scales images from 0 to 255, thus we need
        # to divide by 255.0
        img = img.astype(float) / 255.0
        # NHWC -> NCWH
        img = img.transpose(2, 0, 1)

        lbl = self.encode_segmap(lbl)
        classes = np.unique(lbl)
        lbl = lbl.astype(float)
        lbl = m.imresize(lbl, (self.img_size[0], self.img_size[1]), 'nearest', mode='F')
        lbl = lbl.astype(int)
        assert(np.all(classes == np.unique(lbl)))

        img = torch.from_numpy(img).float()
        lbl = torch.from_numpy(lbl).long()
        return img, lbl