Initial commit

lab6_1/lab6_1.py

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+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)
+
+    cv2.imshow("Image_load",image1)
+    cv2.imshow("erode_cv",image2)
+    cv2.imshow("dilate_cv",image3)
+    cv2.imshow("median_cv",image4)
+    cv2.imshow("erode_ipp",image5)
+    cv2.imshow("dilate_ipp",image6)
+    cv2.imshow("median_ipp",image7)
+    cv2.waitKey(0)
+
+    lstone=sravit_metod(image2)
+    lsttwo=sravit_metod(image5)
+    lsttree=lsttwo[len(lstone):]
+    print("Erode")
+    print("Количество отличий : "+str(len(lsttwo)-len(lstone))+" \nРазница")
+    print(lsttree)
+
+    lstone=sravit_metod(image3)
+    lsttwo=sravit_metod(image5)
+    lsttree=lstone[len(lsttwo):]
+    print("Dilate")
+    print("Количество отличий : "+str(len(lstone)-len(lsttwo))+" \nРазница")
+    print(lsttree)
+
+    lstone=sravit_metod(image4)
+    lsttwo=sravit_metod(image7)
+    lsttree=lstone[len(lsttwo):]
+    print("Median")
+    print("Количество отличий : "+str(len(lstone)-len(lsttwo))+" \nРазница")
+    print(lsttree)
+
+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()