import os
import sys
import cv2
import numpy as np
from matplotlib import pyplot as plt
def main():
    lstone=list()
    lsttwo=list()
    image1 = cv2.imread("D:\\MACH\\MACH\\LAB_2\\image0.jpg")
    image2=image1
    image3=image1
    image4=image1
    image5=image1
    image6=image1
    image7=image1
    image2=erode_cv(image2,11)
    image3=dilate_cv(image3,11)
    image4=median_cv(image4,5)
    image5=erode_ipp(image5,14)
    image6=dilate_ipp(image6,14)
    image7=median_ipp(image7,7)


    x = np.linspace(-5, 2, 100)                     # от -5 до 2 сделать 100 точек
    # показать рисунок
    


    
    lstone=sravit_metod(image2)
    lsttwo=sravit_metod(image5)
    lsttree=lsttwo[len(lstone):]
    y1 =len(lstone)*x
    y2 =len(lsttree)*x
    
    
    lstone=sravit_metod(image3)
    lsttwo=sravit_metod(image5)
    
    y3 =len(lstone)*x
    y4 =len(lsttwo)*x
    
    lstone=sravit_metod(image4)
    lsttwo=sravit_metod(image7)
    lsttree=lstone[len(lsttwo):]
    y5 =len(lstone)*x
    y6 =len(lsttwo)*x
    
    fig, ax = plt.subplots()                        
    ax.plot(x, y1, color="blue", label="erode_cv")  
    ax.plot(x, y2, color="red", label="erode_ipp")  
    ax.plot(x, y3, color="green", label="dilate_cv")  
    ax.plot(x, y4, color="yellow", label="dilate_ipp") 
    ax.plot(x, y5, color="orange", label="median_cv")  
    ax.plot(x, y6, color="grey", label="median_ipp")   
    ax.set_xlabel("x")                              
    ax.set_ylabel("y")                              
    ax.legend()                                     
    plt.show()                                      

def erode_cv(s1,s2):
    s1 = cv2.erode(s1, np.ones((s2, s2)))
    return s1
def dilate_cv(s1,s2):
    s1 = cv2.dilate(s1, np.ones((s2, s2)))
    return s1
def median_cv(s1,s2):
    s1 = cv2.medianBlur(s1,s2)
    return s1
def erode_ipp(s1,s2):
    s1 = cv2.erode(s1, np.ones((s2, s2)))
    return s1
def dilate_ipp(s1,s2):
    s1 = cv2.dilate(s1, np.ones((s2, s2)))
    return s1
def median_ipp(s1,s2):
    s1 = cv2.medianBlur(s1,s2)
    return s1

def sravit_metod(s1):
    cv2.imwrite("im1.jpg",s1)
    s1 = cv2.imread("im1.jpg", 0)
    th, threshed = cv2.threshold(s1, 100, 255,cv2.THRESH_BINARY_INV|cv2.THRESH_OTSU)
    cnts = cv2.findContours(threshed, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)[-2]
    t1= 3
    t2 = 20
    xcnts = []
    for cnt in cnts:
        if t1<cv2.contourArea(cnt) <t2:
            xcnts.append(cnt)
    os.remove("im1.jpg")
    return xcnts

if __name__=="__main__":
    main()