# -*- coding: utf-8 -*-
"""
Functions for transforming and preprocessing images for training
"""
import numpy as np
import pandas as pd
import cv2
from scipy.ndimage.interpolation import map_coordinates


def coordinates_remap(image, factor_alpha, factor_sigma):
    """Transforming image using remaping coordinates."""
    alpha = image.shape[1] * factor_alpha
    sigma = image.shape[1] * factor_sigma
    shape = image.shape
    
    blur_size = int(4*sigma) | 1
    dx = alpha * cv2.GaussianBlur((np.random.rand(*shape) * 2 - 1),
                                  ksize=(blur_size, blur_size),
                                  sigmaX=sigma)
    dy = alpha * cv2.GaussianBlur((np.random.rand(*shape) * 2 - 1),
                                  ksize=(blur_size, blur_size),
                                  sigmaX=sigma)
    
    x, y = np.meshgrid(np.arange(shape[1]), np.arange(shape[0]))
    indices = np.reshape(y+dy, (-1, 1)), np.reshape(x+dx, (-1, 1))

    # TODO use cv2.remap(image, dx, dy, interpolation=cv2.INTER_LINEAR)
    return np.array(map_coordinates(image, indices, order=1, mode='constant').reshape(shape))