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# -*- 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)) |