#coding=utf-8
'''颜色串色检测'''
import cv2 as cv
import numpy as np

#裁剪图片
def cutImage(img_addr):
    img = cv.imread(img_addr)
    img_arr = np.array(img)
    hight = img_arr.shape[0]
    wight = img_arr.shape[1]
    dest_img = img_arr[hight/2+20:hight,0:wight,:]
    return dest_img

#得到横坐标点
def getSpot(dest_img):
    edge_img_rgb  = cv.convertScaleAbs(cv.Sobel(dest_img,cv.CV_16S,1,0))
    edge_img_gray = cv.cvtColor(edge_img_rgb,cv.COLOR_BGR2GRAY)
    _,edge_img = cv.threshold(edge_img_gray,50,255,cv.THRESH_BINARY)
    #做一条水平线
    tumple1=[]
    tumple = []
    for y in range(0,edge_img.shape[1],1):
        if edge_img[70][y] == 255:
            tumple1.append(y)
            tumple.append(y)
    count = 0
    for i in range(0,len(tumple1)):
        if i != len(tumple1)-1:
            if tumple1[i+1] - tumple1[i]>15:
                if count == 0:
                    tumple.insert(i+1,".")
                else :
                    tumple.insert(count+i+1,".")
                count= count +1
    tumple.insert(len(tumple),".")
    lines =[]
    recode = 0
    for i in range(0,len(tumple),1):
        if tumple[i] == "." :
            if recode == 0:
                temp_arr = tumple[recode:i]
                recode = i
            else:
                temp_arr = tumple[recode+1:i]
                recode = i
            lines.append(sum(temp_arr)/len(temp_arr))
    return lines

#输入图片地址，返回拆分图片
def  getPartImage(img_addr):
    dest_img = cutImage(img_addr)
    lines = getSpot(dest_img)
    images = []
    for i in range(0,len(lines)):
        if i ==0:
            images.append(dest_img[0:dest_img.shape[0],0:lines[i]-5,:])
        else:
            if i == len(lines)-1:
                images.append(dest_img[0:dest_img.shape[0],lines[i]+5:dest_img.shape[1]-5,:])
            images.append(dest_img[0:dest_img.shape[0],lines[i-1]+5:lines[i]-5,:])
    return images
# 对外提供方法.函数准确度不够。
# 废弃
def cmpPicTotal(picpath1):
    images = getPartImage(picpath1)
    if len(images) != 8:
        print "彩色分离异常"
    else:
        for image in images:
            wight = image.shape[1]
            hight = image.shape[0]
            B, G, R = cv.split(image)
            sum_B = 0
            sum_G = 0
            sum_R = 0
            for x in range(0, hight, 1):
                for y in range(0, wight, 1):
                    sum_B = sum_B + B[x][y]
                    sum_G = sum_G + G[x][y]
                    sum_R = sum_R + R[x][y]
                    avg_B = sum_B / (wight * hight)
                    avg_G = sum_G / (wight * hight)
                    avg_R = sum_R / (wight * hight)
            for x in range(0, hight, 1):
                for y in range(0, wight, 1):
                    if abs(image[x][y][0] - avg_B)>20 or abs(image[x][y][1] - avg_G) >20 or abs(image[x][y][2] -avg_R) >20:
                        return False
                    else:
                        return True