import cv2
import numpy as np
import matplotlib.pyplot as plt
import imutils
from collections import defaultdict
#import datetime

#start = datetime.datetime.now()
import time
start = time.process_time()
def makepic():
    count = 11
    for x in range(count):
        img = np.ones((1, 60), dtype=np.uint8)
        img[0, range(0, 20)] = 250
        img[0, range(20, 40)] = 250
        img[0, range(40, 60)] = 250
        filename = 'make' + str(x) + '.bmp'
        #print(filename)
        cv2.imwrite(filename, img)

    for x in range(11, 18):
        img = np.ones((1, 60), dtype=np.uint8)
        img[0, range(0, 20)] = 250
        img[0, range(20, 40)] = 30
        img[0, range(40, 60)] = 250
        filename = 'make' + str(x) + '.bmp'
        #print(filename)
        cv2.imwrite(filename, img)

    count = 968
    for x in range(18, count):
        img = np.ones((1, 60), dtype=np.uint8)
        img[0, range(0, 20)] = 250
        img[0, range(20, 40)] = 30
        img[0, range(40, 60)] = 250
        filename = 'make' + str(x) + '.bmp'
        #print(filename)
        cv2.imwrite(filename, img)

    for x in range(968, 1000):
        img = np.ones((1, 60), dtype=np.uint8)
        img[0, range(0, 20)] = 250
        img[0, range(20, 40)] = 250
        img[0, range(40, 60)] = 250
        filename = 'make' + str(x) + '.bmp'
        #print(filename)
        cv2.imwrite(filename, img)




def detectionpic():
    image = cv2.imread("make0.bmp")
    image2 = cv2.imread("make1.bmp")
    image_v = cv2.vconcat([image, image2])  # 垂直組合

    count = 998
    for x in range(count):
        # 讀取圖檔
        filename = 'make' + str(int(x * 1)) + '.bmp'
        #print(filename)
        image = cv2.imread(filename)
        image_v = cv2.vconcat([image_v, image])
        #cv2.imwrite("total.bmp", image_v)
    # 讀取圖檔
    filename = 'total.bmp'
    image = cv2.imread(filename)
    # 轉為灰階
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    # 模糊化圖片
    blurred = cv2.GaussianBlur(gray, (11, 11), 0)
    #cv2.imshow('Blur',blurred)
    #cv2.waitKey(0)

    # Canny 尋找邊緣
    edged = cv2.Canny(blurred, 30, 150)
    #cv2.imshow('Edged',edged)
    #cv2.waitKey(0)

    # findContour 確定輪廓
    _,contours, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    img2 = image.copy()
    cv2.drawContours(img2, contours, -1, (0, 255, 0), 2)
    #cv2.imshow('contour',img2)
    #cv2.imwrite('check.bmp',img2)
    #cv2.waitKey(0)

    cnt = contours[0]

    #contourArea 計算面積
    area = cv2.contourArea(cnt)  #計算面積
    perimeter = cv2.arcLength(cnt,True)    #計算周長

    if area < 19119:
        print('破損豆噴調',area)
    else:
        pass
    print('面積:',area, '周長:',perimeter)  #印出結果
    '''
    p = 0
    d = 0
    tt = np.array(gray[0])
    print(tt)
    count = len(tt)
    print(len(tt))
    
    for i in tt[:]:
        if i >= 150:
            p = p + 1
        elif i <= 130:
            d = d + 1
    print('要得豆子像素:',p)
    print('壞的豆子像素:',d)

    coffeebean = (d / count)*100
    print('壞豆佔全部百分比:',coffeebean)
    if coffeebean > 60:
        record = record + 1
        print('紀錄次數:', record)
    else:
        pass
    if record == 50:
        j = 1
        # record=0
        print('噴嘴啟動')
        # break
        # continue
'''
makepic()
detectionpic()
#end = datetime.datetime.now()
#print("執行時間：", end - start)
# 結束測量
end = time.process_time()
# 輸出結果
print("執行時間：%f 秒" % (end - start))