# -*- coding:utf-8 -*-
# Author: RubanSeven
# Reference: https://github.com/RubanSeven/Text-Image-Augmentation-python

# import cv2
import numpy as np
from .warp_mls import WarpMLS


def tia_distort(src, segment=4):
    img_h, img_w = src.shape[:2]

    cut = img_w // segment
    thresh = cut // 3

    src_pts = list()
    dst_pts = list()

    src_pts.append([0, 0])
    src_pts.append([img_w, 0])
    src_pts.append([img_w, img_h])
    src_pts.append([0, img_h])

    dst_pts.append([np.random.randint(thresh), np.random.randint(thresh)])
    dst_pts.append(
        [img_w - np.random.randint(thresh), np.random.randint(thresh)])
    dst_pts.append(
        [img_w - np.random.randint(thresh), img_h - np.random.randint(thresh)])
    dst_pts.append(
        [np.random.randint(thresh), img_h - np.random.randint(thresh)])

    half_thresh = thresh * 0.5

    for cut_idx in np.arange(1, segment, 1):
        src_pts.append([cut * cut_idx, 0])
        src_pts.append([cut * cut_idx, img_h])
        dst_pts.append([
            cut * cut_idx + np.random.randint(thresh) - half_thresh,
            np.random.randint(thresh) - half_thresh
        ])
        dst_pts.append([
            cut * cut_idx + np.random.randint(thresh) - half_thresh,
            img_h + np.random.randint(thresh) - half_thresh
        ])

    trans = WarpMLS(src, src_pts, dst_pts, img_w, img_h)
    dst = trans.generate()

    return dst


def tia_stretch(src, segment=4):
    img_h, img_w = src.shape[:2]

    cut = img_w // segment
    thresh = cut * 4 // 5

    src_pts = list()
    dst_pts = list()

    src_pts.append([0, 0])
    src_pts.append([img_w, 0])
    src_pts.append([img_w, img_h])
    src_pts.append([0, img_h])

    dst_pts.append([0, 0])
    dst_pts.append([img_w, 0])
    dst_pts.append([img_w, img_h])
    dst_pts.append([0, img_h])

    half_thresh = thresh * 0.5

    for cut_idx in np.arange(1, segment, 1):
        move = np.random.randint(thresh) - half_thresh
        src_pts.append([cut * cut_idx, 0])
        src_pts.append([cut * cut_idx, img_h])
        dst_pts.append([cut * cut_idx + move, 0])
        dst_pts.append([cut * cut_idx + move, img_h])

    trans = WarpMLS(src, src_pts, dst_pts, img_w, img_h)
    dst = trans.generate()

    return dst


def tia_perspective(src):
    img_h, img_w = src.shape[:2]

    thresh = img_h // 2

    src_pts = list()
    dst_pts = list()

    src_pts.append([0, 0])
    src_pts.append([img_w, 0])
    src_pts.append([img_w, img_h])
    src_pts.append([0, img_h])

    dst_pts.append([0, np.random.randint(thresh)])
    dst_pts.append([img_w, np.random.randint(thresh)])
    dst_pts.append([img_w, img_h - np.random.randint(thresh)])
    dst_pts.append([0, img_h - np.random.randint(thresh)])

    trans = WarpMLS(src, src_pts, dst_pts, img_w, img_h)
    dst = trans.generate()

    return dst
