import cv2 as cv
import math
import numpy as np
import os, sys

img_cache = {}
hist_rgb_cache = {}


def readImage(img_path):
    global img_cache

    if img_path in img_cache.keys():
        pass

    else:
        # read image
        img_test_rgb = cv.imread(img_path)
        # convert to gray scale
        img_test_rgb = cv.resize(img_test_rgb, (1024, 1024))
        img_cache[img_path] = img_test_rgb

    return img_cache[img_path]


def getCountourDiff():
    pass


def checkCountourImg1(img1):
    try:
        kernel = cv.getStructuringElement(cv.MORPH_RECT, (6, 6))

        # calculation for the area of a circle in img1
        heightCenter1 = img1.shape[0] / 2
        widthCenter1 = img1.shape[1] / 2
        heightCircle1 = img1.shape[0] / 2.3
        widthCircle1 = img1.shape[1] / 2.7

        center1 = (round(widthCenter1), round(heightCenter1))
        axesLength1 = (round(widthCircle1), round(heightCircle1))
        circleArea1 = round(math.pi * widthCircle1 * heightCircle1)

        # calculation for contours and total area of img1
        L, U, V = cv.split(cv.cvtColor(img1, cv.COLOR_BGR2LUV))

        channel1 = cv.merge([U, U, U])
        channel1 = cv.cvtColor(channel1, cv.COLOR_BGR2GRAY)
        closed1 = cv.morphologyEx(channel1, cv.MORPH_CLOSE, kernel)
        closed1 = cv.medianBlur(closed1, 3)
        retval, threshold1 = cv.threshold(closed1, 100, 255, cv.THRESH_BINARY)

        contours1, hierarchy1 = cv.findContours(threshold1, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)

        # cv.drawContours(img1, contours1, -1, (0, 255, 0), 2)
        # cv.imshow("Contours Image 1", img1)
        # cv.waitKey(0)
        # cv.destroyAllWindows()
        # sys.exit()

        return (contours1, circleArea1)
    except Exception as e:
        print(e)


def checkCountourImg2(img2):
    kernel = cv.getStructuringElement(cv.MORPH_RECT, (6, 6))

    try:
        # calculation for the area of a circle in img2
        img2copy = img2.copy()

        height, width, _ = img2.shape
        heightCenter2, widthCenter2 = height / 2, width / 2
        heightCircle2, widthCircle2 = height / 2.3, width / 2.5

        center2 = (round(widthCenter2), round(heightCenter2))
        axesLength2 = (round(widthCircle2), round(heightCircle2))
        circleArea2 = round(math.pi * widthCircle2 * heightCircle2)

        img2circle = cv.ellipse(img2copy, center2, axesLength2, 0, 0, 360, (0, 0, 255), 2)

        # calculation for contours and total area of img2
        L, U, V = cv.split(cv.cvtColor(img2circle, cv.COLOR_BGR2LUV))
        channel2 = cv.merge([U, U, U])
        channel2 = cv.cvtColor(channel2, cv.COLOR_BGR2GRAY)
        closed2 = cv.morphologyEx(channel2, cv.MORPH_CLOSE, kernel)
        closed2 = cv.medianBlur(closed2, 3)
        retval, threshold2 = cv.threshold(closed2, 110, 255, cv.THRESH_BINARY)

        contours2, hierarchy2 = cv.findContours(threshold2, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)

        return (contours2, circleArea2)
    except Exception as e:
        print(e)


def getCountour(img1, img2):
    try:
        kernel = cv.getStructuringElement(cv.MORPH_RECT, (6, 6))
        totalArea1 = 0
        totalArea2 = 0

        # calculation for the area of a circle in img1
        heightCenter1 = img1.shape[0] / 2
        widthCenter1 = img1.shape[1] / 2
        heightCircle1 = img1.shape[0] / 2.3
        widthCircle1 = img1.shape[1] / 2.7

        center1 = (round(widthCenter1), round(heightCenter1))
        axesLength1 = (round(widthCircle1), round(heightCircle1))
        circleArea1 = round(math.pi * widthCircle1 * heightCircle1)

        # calculation for contours and total area of img1
        L, U, V = cv.split(cv.cvtColor(img1, cv.COLOR_BGR2LUV))
        channel1 = cv.merge([U, U, U])
        channel1 = cv.cvtColor(channel1, cv.COLOR_BGR2GRAY)
        closed1 = cv.morphologyEx(channel1, cv.MORPH_CLOSE, kernel)
        closed1 = cv.medianBlur(closed1, 3)
        retval, threshold1 = cv.threshold(closed1, 110, 255, cv.THRESH_BINARY)

        contours1, hierarchy1 = cv.findContours(threshold1, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)

        for contour in contours1:
            totalArea1 += cv.contourArea(contour)

        # calculation for the area of a circle in img2
        img2copy = img2.copy()

        heightCenter2 = img2copy.shape[0] / 2
        widthCenter2 = img2copy.shape[1] / 2
        heightCircle2 = img2copy.shape[0] / 2.3
        widthCircle2 = img2copy.shape[1] / 2.5

        center2 = (round(widthCenter2), round(heightCenter2))
        axesLength2 = (round(widthCircle2), round(heightCircle2))
        circleArea2 = round(math.pi * widthCircle2 * heightCircle2)

        img2circle = cv.ellipse(img2copy, center2, axesLength2, 0, 0, 360, (0, 0, 255), 2)

        # calculation for contours and total area of img2
        L, U, V = cv.split(cv.cvtColor(img2circle, cv.COLOR_BGR2LUV))
        channel2 = cv.merge([U, U, U])
        channel2 = cv.cvtColor(channel2, cv.COLOR_BGR2GRAY)
        closed2 = cv.morphologyEx(channel2, cv.MORPH_CLOSE, kernel)
        closed2 = cv.medianBlur(closed2, 3)
        retval, threshold2 = cv.threshold(closed2, 110, 255, cv.THRESH_BINARY)

        contours2, hierarchy2 = cv.findContours(threshold2, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)

        for contour in contours2:
            totalArea2 += cv.contourArea(contour)

        # calculation of contour area over circle area
        print(totalArea1, circleArea1, totalArea2, circleArea2)
        sys.exit()

        circleRatio1 = totalArea1 / circleArea1
        circleRatio2 = totalArea2 / circleArea2
        difference = circleRatio2 / circleRatio1

        return difference

    except Exception as e:
        print(e)


def getContourDiff(img1_path, img2_path):
    totalArea1 = 0
    totalArea2 = 0

    img1 = readImage(img1_path)
    img2 = readImage(img2_path)

    try:
        (contours1, circleArea1) = checkCountourImg1(img1)
        for contour in contours1:
            totalArea1 += cv.contourArea(contour)

        (contours2, circleArea2) = checkCountourImg2(img2)
        for contour in contours2:
            totalArea2 += cv.contourArea(contour)

        # calculation of contour area over circle area
        circleRatio1 = totalArea1 / circleArea1
        circleRatio2 = totalArea2 / circleArea2
        difference = circleRatio2 / circleRatio1

        return difference

    except Exception as e:
        print(e)