import numpy as np
import cv2
import math
 
imgcolor = cv2.imread('riz.jpg')

img=cv2.cvtColor(imgcolor, cv2.COLOR_BGR2GRAY);

print(img[0][0])
print(img[254][0])
#ret,thresh1 = cv2.threshold(img,60,255,cv2.THRESH_BINARY)
# find otsu's threshold value with OpenCV function


blur = cv2.GaussianBlur(img,(5,5),0)
ret, thresh1= cv2.threshold(blur,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)

kernel = np.ones((3,3),np.uint8)
erosion = cv2.erode(thresh1,kernel,iterations = 2)
ouverture = cv2.dilate(erosion,kernel,iterations = 1)

contours, hierarchy = cv2.findContours(ouverture,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
i=0
for data in contours:
    print("The contours have this data "+str(data))
    rect = cv2.minAreaRect(data)
    l=rect[1][1]
    m=rect[1][0]
    w=max(l,m)
    h=min(l,m)
    if h>0:
        aspect=float(w/h)
    else: 
        aspect=10000000  
    area = cv2.contourArea(data)    
    hull = cv2.convexHull(data) 
    hull_area = cv2.contourArea(hull)          
    if hull_area>0:
        solidity=float(area/hull_area)
    else:
        solidity=10000000000

    perimeter = cv2.arcLength(data,True)
    #if i%2==0 :
    if aspect>1.9 and aspect<6 and area>40 and area<200 and solidity>0.8 and perimeter<45:
        cv2.drawContours(imgcolor,data,-1,(0,0,255),1)
        i=i+1
    else:
        cv2.drawContours(imgcolor,data,-1,(0,255,0),1)



print("hierarchy    "+str(hierarchy    ))
#cv2.drawContours(imgcolor,contours,-1,(0,255,0),1)

print(ret)
print ("il y a "+str(i)+ " grains de riz")

#sauver au format png pour compression sans perte
'''cv2.imwrite('riz_ouverture.png',ouverture)
cv2.imwrite('riz_erosion.png',erosion)
cv2.imwrite('riz_thresh1.png',thresh1)
cv2.imwrite('riz_out.png',img)'''
cv2.imwrite('riz_out_contour.png',imgcolor)
cv2.imshow('image',imgcolor)
cv2.waitKey(0)
cv2.destroyAllWindows()
print("fini")