def otsu_one(img, img_file, man_img, mask=None):
# cv2.GaussianBlur(img, (5,5),0)
# Bilateral Filter is used separately so it can be adjusted for each type of segmentation
blur = cv2.bilateralFilter(img, 5, 5, 5)
th = single_threshold_otsu(blur, mask)
if mask is None:
ret, thresh = cv2.threshold(blur, th, 255, cv2.THRESH_BINARY)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh = cv2.threshold(combined_img, th, 255, cv2.THRESH_BINARY)
# Otsu result image
out_img_o = thresh
# morphological ops
kernel = morphologicalOps.open_center_kernel()
out_img_o = morphologicalOps.opening(out_img_o, kernel)
out_info_o = "_otsu_%d" % (th)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
f = open('o1_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) +
" " + str(t[3]) + "\n")
f.close()
def otsuTwo(img, img_file, man_img, mask=None):
# blur = cv2.GaussianBlur(img, (5,5),0)
blur = cv2.bilateralFilter(img, 5, 100, 100)
thresholds = multithresholdOtsu(blur,mask)
th1 = thresholds[0]
th2 = thresholds[1]
if mask is None:
ret, thresh1 = cv2.threshold(blur,th1,255,cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(blur,th2,255,cv2.THRESH_BINARY_INV)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh1 = cv2.threshold(combined_img,th1,255,cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(combined_img,th2,255,cv2.THRESH_BINARY_INV)
out_img_o = cv2.bitwise_and(thresh1, thresh2, mask=None)
out_info_o = "_otsu_%d-%d" % (th1, th2)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
f = open('o2_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def otsuTwo(img, img_file, man_img, mask=None):
# blur = cv2.GaussianBlur(img, (5,5),0)
blur = cv2.bilateralFilter(img, 5, 100, 100)
thresholds = multithresholdOtsu(blur, mask)
th1 = thresholds[0]
th2 = thresholds[1]
if mask is None:
ret, thresh1 = cv2.threshold(blur, th1, 255, cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(blur, th2, 255, cv2.THRESH_BINARY_INV)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh1 = cv2.threshold(combined_img, th1, 255, cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(combined_img, th2, 255,
cv2.THRESH_BINARY_INV)
out_img_o = cv2.bitwise_and(thresh1, thresh2, mask=None)
out_info_o = "_otsu_%d-%d" % (th1, th2)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
f = open('o2_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) +
" " + str(t[3]) + "\n")
f.close()
def otsuThree(img, img_file, man_img, mask=None):
# blur = cv2.GaussianBlur(img, (5,5),0)
blur = cv2.bilateralFilter(img, 5, 100, 100)
thresholds = threeThresholdOtsu(blur, mask)
th1 = thresholds[0]
th2 = thresholds[1]
th3 = thresholds[2]
# if mask is None:
# ret, thresh1 = cv2.threshold(blur,th1,150,cv2.THRESH_BINARY)
# ret, thresh2 = cv2.threshold(blur,th2,150,cv2.THRESH_BINARY_INV)
# lower_img = cv2.bitwise_and(thresh1, thresh2, mask=None)
# ret, thresh2 = cv2.threshold(blur, th2, 200, cv2.THRESH_BINARY)
# ret, thresh3 = cv2.threshold(blur, th3, 200, cv2.THRESH_BINARY_INV)
# middle_img = cv2.bitwise_and(thresh2, thresh3, mask=None)
# ret, upper_img = cv2.threshold(blur, th3, 255, cv2.THRESH_BINARY)
# else:
# combined_img = cv2.bitwise_and(blur, blur, mask=mask)
# ret, thresh1 = cv2.threshold(combined_img,th1,150,cv2.THRESH_BINARY)
# ret, thresh2 = cv2.threshold(combined_img,th2,150,cv2.THRESH_BINARY_INV)
# lower_img = cv2.bitwise_and(thresh1, thresh2, mask=mask)
# ret, thresh2 = cv2.threshold(blur, th2, 200, cv2.THRESH_BINARY)
# ret, thresh3 = cv2.threshold(blur, th3, 200, cv2.THRESH_BINARY_INV)
# middle_img = cv2.bitwise_and(thresh2, thresh3, mask=mask)
# ret, upper_img = cv2.threshold(blur, th3, 255, cv2.THRESH_BINARY)
# out_img_one = cv2.bitwise_or(lower_img, middle_img, mask=mask)
# out_img_o = cv2.bitwise_or(out_img_one, upper_img, mask=mask)
if mask is None:
ret, thresh = cv2.threshold(blur, th3, 255, cv2.THRESH_BINARY)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh = cv2.threshold(combined_img, th, 255, cv2.THRESH_BINARY)
out_img_o = thresh
out_info_o = "_otsu_%d-%d-%d" % (th1, th2, th3)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
# f = open('o3_all.txt', 'a')
# f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
# f.close()
# t = evaluation.findTotalsOtsu3(out_img_o, man_img, 150)
# f = open('o3_t1-t2_all.txt', 'a')
# f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
# f.close()
# t = evaluation.findTotalsOtsu3(out_img_o, man_img, 200)
# f = open('o3_t2-t3_all.txt', 'a')
# f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
# f.close()
t = evaluation.findTotalsOtsu3(out_img_o, man_img, 255)
f = open('o3_t3-max_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) +
" " + str(t[3]) + "\n")
f.close()
def otsuThree(img, img_file, man_img, mask=None):
# blur = cv2.GaussianBlur(img, (5,5),0)
blur = cv2.bilateralFilter(img, 5, 100, 100)
thresholds = threeThresholdOtsu(blur,mask)
th1 = thresholds[0]
th2 = thresholds[1]
th3 = thresholds[2]
# if mask is None:
# ret, thresh1 = cv2.threshold(blur,th1,150,cv2.THRESH_BINARY)
# ret, thresh2 = cv2.threshold(blur,th2,150,cv2.THRESH_BINARY_INV)
# lower_img = cv2.bitwise_and(thresh1, thresh2, mask=None)
# ret, thresh2 = cv2.threshold(blur, th2, 200, cv2.THRESH_BINARY)
# ret, thresh3 = cv2.threshold(blur, th3, 200, cv2.THRESH_BINARY_INV)
# middle_img = cv2.bitwise_and(thresh2, thresh3, mask=None)
# ret, upper_img = cv2.threshold(blur, th3, 255, cv2.THRESH_BINARY)
# else:
# combined_img = cv2.bitwise_and(blur, blur, mask=mask)
# ret, thresh1 = cv2.threshold(combined_img,th1,150,cv2.THRESH_BINARY)
# ret, thresh2 = cv2.threshold(combined_img,th2,150,cv2.THRESH_BINARY_INV)
# lower_img = cv2.bitwise_and(thresh1, thresh2, mask=mask)
# ret, thresh2 = cv2.threshold(blur, th2, 200, cv2.THRESH_BINARY)
# ret, thresh3 = cv2.threshold(blur, th3, 200, cv2.THRESH_BINARY_INV)
# middle_img = cv2.bitwise_and(thresh2, thresh3, mask=mask)
# ret, upper_img = cv2.threshold(blur, th3, 255, cv2.THRESH_BINARY)
# out_img_one = cv2.bitwise_or(lower_img, middle_img, mask=mask)
# out_img_o = cv2.bitwise_or(out_img_one, upper_img, mask=mask)
if mask is None:
ret, thresh = cv2.threshold(blur,th3,255,cv2.THRESH_BINARY)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh = cv2.threshold(combined_img,th,255,cv2.THRESH_BINARY)
out_img_o = thresh
out_info_o = "_otsu_%d-%d-%d" % (th1, th2, th3)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
# f = open('o3_all.txt', 'a')
# f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
# f.close()
# t = evaluation.findTotalsOtsu3(out_img_o, man_img, 150)
# f = open('o3_t1-t2_all.txt', 'a')
# f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
# f.close()
# t = evaluation.findTotalsOtsu3(out_img_o, man_img, 200)
# f = open('o3_t2-t3_all.txt', 'a')
# f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
# f.close()
t = evaluation.findTotalsOtsu3(out_img_o, man_img, 255)
f = open('o3_t3-max_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def bilateral_filter(img, seed, th, img_file, out_info, man_img):
img_b = cv2.bilateralFilter(img, 5, 5, 5)
out_img_b = seeded_region_growing(img_b, seed, th)
out_str_b = out_info + '_b.png'
out_file_b = re.sub(r'\.jpg', out_str_b, img_file)
cv2.imwrite(out_file_b, out_img_b)
t = evaluation.findTotals(out_img_b, man_img)
f = open('b_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def unsmoothed(img, seed, th, img_file, out_info, man_img):
img_n = img
out_img_n = seeded_region_growing(img_n, seed, th)
out_str_n = out_info + '_n.png'
out_file_n = re.sub(r'\.jpg', out_str_n, img_file)
cv2.imwrite(out_file_n, out_img_n)
t = evaluation.findTotals(out_img_n, man_img)
f = open('n_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def bilateral_filter(img, eqImg, seed, th, img_file, out_info, man_img):
img_b = cv2.bilateralFilter(img, 5, 10, 10)
out_img_b = seeded_region_growing(img_b, seed, th)
out_str_b = out_info + '_b.png'
out_file_b = re.sub(r'\.jpg', out_str_b, img_file)
cv2.imwrite(out_file_b, out_img_b)
t = evaluation.findTotals(out_img_b, man_img)
f = open('b_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def unsmoothed(img, eqImg, seed, th, img_file, out_info, man_img):
img_n = img
out_img_n = seeded_region_growing(img_n, seed, th)
out_str_n = out_info + '_n.png'
out_file_n = re.sub(r'\.jpg', out_str_n, img_file)
cv2.imwrite(out_file_n, out_img_n)
t = evaluation.findTotals(out_img_n, man_img)
f = open('n_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def averageFilters(img, eqImg, seed, th, img_file, out_info, man_img):
img_a = cv2.blur(img, (3,3))
img_ah = cv2.blur(eqImg, (3,3))
out_img_a = seeded_region_growing(img_a, seed, th)
out_str_a = out_info + '_a.png'
out_file_a = re.sub(r'\.jpg', out_str_a, img_file)
cv2.imwrite(out_file_a, out_img_a)
t = evaluation.findTotals(out_img_a, man_img)
f = open('a.txt', 'a')
f.write(str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
out_img_ah = seeded_region_growing(img_ah, seed, th)
out_str_ah = out_info + '_ah.png'
out_file_ah = re.sub(r'\.jpg', out_str_ah, img_file)
cv2.imwrite(out_file_ah, out_img_ah)
t = evaluation.findTotals(out_img_ah, man_img)
f = open('ah.txt', 'a')
f.write(str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def GaussianFilters(img, eqImg, seed, th, img_file, out_info, man_img):
img_g = cv2.GaussianBlur(img, (3,3), 0)
img_gh = cv2.GaussianBlur(eqImg, (3,3), 0)
out_img_g = seeded_region_growing(img_g, seed, th)
out_str_g = out_info + '_g.png'
out_file_g = re.sub(r'\.jpg', out_str_g, img_file)
cv2.imwrite(out_file_g, out_img_g)
t = evaluation.findTotals(out_img_g, man_img)
f = open('g_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
out_img_gh = seeded_region_growing(img_gh, seed, th)
out_str_gh = out_info + '_gh.png'
out_file_gh = re.sub(r'\.jpg', out_str_gh, img_file)
cv2.imwrite(out_file_gh, out_img_gh)
t = evaluation.findTotals(out_img_gh, man_img)
f = open('gh_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def averageFilters(img, eqImg, seed, th, img_file, out_info, man_img):
img_a = cv2.blur(img, (3,3))
img_ah = cv2.blur(eqImg, (3,3))
out_img_a = seeded_region_growing(img_a, seed, th)
out_str_a = out_info + '_a.png'
out_file_a = re.sub(r'\.jpg', out_str_a, img_file)
cv2.imwrite(out_file_a, out_img_a)
t = evaluation.findTotals(out_img_a, man_img)
f = open('a_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
out_img_ah = seeded_region_growing(img_ah, seed, th)
out_str_ah = out_info + '_ah.png'
out_file_ah = re.sub(r'\.jpg', out_str_ah, img_file)
cv2.imwrite(out_file_ah, out_img_ah)
t = evaluation.findTotals(out_img_ah, man_img)
f = open('ah_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def GaussianFilters(img, eqImg, seed, th, img_file, out_info, man_img):
img_g = cv2.GaussianBlur(img, (3,3), 0)
img_gh = cv2.GaussianBlur(eqImg, (3,3), 0)
out_img_g = seeded_region_growing(img_g, seed, th)
out_str_g = out_info + '_g.png'
out_file_g = re.sub(r'\.jpg', out_str_g, img_file)
cv2.imwrite(out_file_g, out_img_g)
t = evaluation.findTotals(out_img_g, man_img)
f = open('g.txt', 'a')
f.write(str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
out_img_gh = seeded_region_growing(img_gh, seed, th)
out_str_gh = out_info + '_gh.png'
out_file_gh = re.sub(r'\.jpg', out_str_gh, img_file)
cv2.imwrite(out_file_gh, out_img_gh)
t = evaluation.findTotals(out_img_gh, man_img)
f = open('gh.txt', 'a')
f.write(str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def bilateral_filter(img, seed, th, img_file, out_info, man_img):
img_b = cv2.bilateralFilter(img, 5, 5, 5)
# SRG result image
out_img_b = seeded_region_growing(img_b, seed, th)
# morphological ops
kernel = morphologicalOps.open_elliptical_kernel()
out_img_b = morphologicalOps.opening(out_img_b, kernel)
out_str_b = out_info + '_b.png'
out_file_b = re.sub(r'\.jpg', out_str_b, img_file)
cv2.imwrite(out_file_b, out_img_b)
t = evaluation.findTotals(out_img_b, man_img)
f = open('b_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def unsmoothed(img, seed, th, img_file, out_info, man_img):
img_n = img
# SRG result image
out_img_n = seeded_region_growing(img_n, seed, th)
# Morphological op
kernel = morphologicalOps.open_elliptical_kernel()
out_img_n = morphologicalOps.opening(out_img_n, kernel)
out_str_n = out_info + '_n.png'
out_file_n = re.sub(r'\.jpg', out_str_n, img_file)
cv2.imwrite(out_file_n, out_img_n)
t = evaluation.findTotals(out_img_n, man_img)
f = open('n_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def unsmoothed(img, seed, th, img_file, out_info, man_img):
img_n = img
# SRG result image
out_img_n = seeded_region_growing(img_n, seed, th)
# Morphological op
kernel = morphologicalOps.open_cross_kernel()
out_img_n = morphologicalOps.opening(out_img_n, kernel)
out_str_n = out_info + '_n.png'
out_file_n = re.sub(r'\.jpg', out_str_n, img_file)
cv2.imwrite(out_file_n, out_img_n)
t = evaluation.findTotals(out_img_n, man_img)
f = open('n_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def bilateral_filter(img, seed, th, img_file, out_info, man_img):
img_b = cv2.bilateralFilter(img, 5, 5, 5)
# SRG result image
out_img_b = seeded_region_growing(img_b, seed, th)
# morphological ops
kernel = morphologicalOps.open_cross_kernel()
out_img_b = morphologicalOps.opening(out_img_b, kernel)
out_str_b = out_info + '_b.png'
out_file_b = re.sub(r'\.jpg', out_str_b, img_file)
cv2.imwrite(out_file_b, out_img_b)
t = evaluation.findTotals(out_img_b, man_img)
f = open('b_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def otsu_one(img, img_file, man_img, mask=None):
# cv2.GaussianBlur(img, (5,5),0)
# Bilateral Filter is used separately so it can be adjusted for each type of segmentation
blur = cv2.bilateralFilter(img, 5, 100, 100)
th = single_threshold_otsu(blur, mask)
if mask is None:
ret, thresh = cv2.threshold(blur,th,255,cv2.THRESH_BINARY)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh = cv2.threshold(combined_img,th,255,cv2.THRESH_BINARY)
out_img_o = thresh
out_info_o = "_otsu_%d" % (th)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
f = open('o1_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def otsuOne(img, img_file, man_img, mask=None):
blur = cv2.GaussianBlur(img, (5,5),0)
th = singlethresholdOtsu(blur,mask)
if mask is None:
ret, thresh = cv2.threshold(blur,th,255,cv2.THRESH_BINARY)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh = cv2.threshold(combined_img,th,255,cv2.THRESH_BINARY)
out_img_o = thresh
out_info_o = "_otsu_%d" % (th)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
f = open('o1.txt', 'a')
f.write(str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def otsuOne(img, img_file, man_img, mask=None):
blur = cv2.GaussianBlur(img, (5,5),0)
th = singlethresholdOtsu(blur,mask)
if mask is None:
ret, thresh = cv2.threshold(blur,th,255,cv2.THRESH_BINARY)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh = cv2.threshold(combined_img,th,255,cv2.THRESH_BINARY)
out_img_o = thresh
out_info_o = "_otsu_%d" % (th)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
f = open('o1_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def otsuThree(img, img_file, man_img, mask=None):
blur = cv2.GaussianBlur(img, (5,5),0)
thresholds = threeThresholdOtsu(blur,mask)
th1 = thresholds[0]
th2 = thresholds[1]
th3 = thresholds[2]
if mask is None:
ret, thresh1 = cv2.threshold(blur,th1,150,cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(blur,th2,150,cv2.THRESH_BINARY_INV)
lower_img = cv2.bitwise_and(thresh1, thresh2, mask=None)
ret, thresh2 = cv2.threshold(blur, th2, 200, cv2.THRESH_BINARY)
ret, thresh3 = cv2.threshold(blur, th3, 200, cv2.THRESH_BINARY_INV)
middle_img = cv2.bitwise_and(thresh2, thresh3, mask=None)
ret, upper_img = cv2.threshold(blur, th3, 255, cv2.THRESH_BINARY)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh1 = cv2.threshold(combined_img,th1,150,cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(combined_img,th2,150,cv2.THRESH_BINARY_INV)
lower_img = cv2.bitwise_and(thresh1, thresh2, mask=mask)
ret, thresh2 = cv2.threshold(blur, th2, 200, cv2.THRESH_BINARY)
ret, thresh3 = cv2.threshold(blur, th3, 200, cv2.THRESH_BINARY_INV)
middle_img = cv2.bitwise_and(thresh2, thresh3, mask=mask)
ret, upper_img = cv2.threshold(blur, th3, 255, cv2.THRESH_BINARY)
out_img_one = cv2.bitwise_or(lower_img, middle_img, mask=mask)
out_img_o = cv2.bitwise_or(out_img_one, upper_img, mask=mask)
out_info_o = "_otsu_%d-%d-%d" % (th1, th2, th3)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
f = open('o3.txt', 'a')
f.write(str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
def otsu_three(img, img_file, man_img, mask=None):
# blur = cv2.GaussianBlur(img, (5,5),0)
# Bilateral Filter is used separately so it can be adjusted for each type of segmentation
blur = cv2.bilateralFilter(img, 3, 20, 20)
thresholds = three_threshold_otsu(blur, mask)
th1 = thresholds[0]
th2 = thresholds[1]
th3 = thresholds[2]
if mask is None:
ret, thresh = cv2.threshold(blur,th3,255,cv2.THRESH_BINARY)
else:
combined_img = cv2.bitwise_and(blur, blur, mask=mask)
ret, thresh = cv2.threshold(combined_img,th,255,cv2.THRESH_BINARY)
out_img_o = thresh
out_info_o = "_otsu_%d-%d-%d" % (th1, th2, th3)
out_str_o = out_info_o + '.png'
out_file_o = re.sub(r'\.jpg', out_str_o, img_file)
cv2.imwrite(out_file_o, out_img_o)
t = evaluation.findTotals(out_img_o, man_img)
f = open('o3_t3-max_all.txt', 'a')
f.write(img_file + " " + str(t[0]) + " " + str(t[1]) + " " + str(t[2]) + " " + str(t[3]) + "\n")
f.close()
