import cv2
import numpy as np
import paddle

from . import DOC_TR
from .utils import to_tensor, to_image


def dewarp_image(image):
    img = cv2.resize(image, (288, 288)).astype(np.float32)
    y = to_tensor(image)

    img = np.transpose(img, (2, 0, 1))
    bm = DOC_TR.run(None, {'image': img[None,]})[0]
    bm = paddle.to_tensor(bm)
    bm = paddle.nn.functional.interpolate(
        bm, y.shape[2:], mode='bilinear', align_corners=False
    )
    bm_nhwc = np.transpose(bm, (0, 2, 3, 1))
    out = paddle.nn.functional.grid_sample(y, (bm_nhwc / 288 - 0.5) * 2)
    return to_image(out)