import numpy as np
import argparse
import cv2
from photoAnalysisUtils import *

def menuAnalyseIMG(url):
    result_vector = []
    img_tested = url
    image = img_tested


    blurred = cv2.GaussianBlur(image, (5, 5), 0)
    edged = cv2.Canny(blurred, 20, 50)
    height = image.shape[0]
    width = image.shape[1]

    referencePoint = open("referencePoint.txt", "r")
    checkBoxesCords = open("checkBoxesCords.txt", "r")
    referencePoint = referencePoint.readlines()
    checkBoxesCords = checkBoxesCords.readlines()


    for corners in referencePoint:
        template_x, template_y = corners.split()

    image, x, y = searchReferencePointCorner(image)

    offsetX = int(template_x) - x
    offsetY = int(template_y) - y
    i=1

    for checkBox in checkBoxesCords:
        x, y, w, h = checkBox.split()
        x = int(x) - offsetX
        y = int(y) - offsetY
        w = int(w)
        h = int(h)
        cv2.rectangle(image, (x, y), (x + w, y + h), (36, 255, 12), 2)
        crop_img = edged[y:y + h, x:x + w]
        n_white_pix = np.sum(crop_img == 255)
        n_black_pix = np.sum(crop_img == 0)
        if(n_white_pix+n_black_pix)*0.2 < n_white_pix:
            #print(str(i)+" FILL")
            result_vector.append([i, 1])
        else:
            #print(str(i)+" EMPTY")
            result_vector.append([i, 0])
        #print("White i ="+str(i)+" white = "+str(n_white_pix))
        #print("Black i ="+str(i)+" black = "+str(n_black_pix))
        #cv2.imwrite("maska"+str(i)+".jpg", crop_img)
        i = i+1


    cv2.imwrite("tested.jpg", image)
    return result_vector

# img_tested = cv2.imread('orders/1.jpg')
# menuAnalyseIMG(img_tested)