def dent_detection(img, num, angle):
accum = np.zeros_like(img)
ksize = 9
for theta in np.arange(0, np.pi, np.pi / 4):
kernel = cv2.getGaborKernel((ksize, ksize), 10, theta, 18, 0.25, 0, ktype=cv2.CV_32F)
kernel /= 1.5 * kernel.sum()
fimg = cv2.filter2D(img, cv2.CV_8UC3, kernel)
np.maximum(accum, fimg, accum)
#
# save_image('A2_accum', accum)
_, thresh = cv2.threshold(accum, 161, 255, cv2.THRESH_BINARY)
sobel = convolve_sobel(img=accum,
threshold=18,
sobel_kernel_left_right=True,
sobel_kernel_right_left=True,
sobel_kernel_top_bottom=True,
sobel_kernel_bottom_top=True,
sobel_kernel_diagonal_top_left=True,
sobel_kernel_diagonal_bottom_left=False,
sobel_kernel_diagonal_top_right=True,
sobel_kernel_diagonal_bottom_right=False)
sobel = cv2.convertScaleAbs(sobel)
#save_image("A2_sobel" + str(num), sobel)
# pos = np.where(accum < 162)
# test_image[pos] = 255
# save_image("A5_test_image" + str(num), test_image)
test_image = np.zeros_like(sobel)
pos_y, pos_x = np.where(sobel == 255)
if pos_x.size != 0:
if angle > -45:
#right teeth
print("right teeth",angle)
for x in np.nditer(pos_x):
for y in np.nditer(pos_y):
if x < 80:
test_image[(y, x)] = sobel[(y, x)]
save_image('testimage' + str(num), test_image)
if angle < -45 and angle > -75:
#left teeth
print("left teeth" + str(num), angle)
for x in np.nditer(pos_x):
for y in np.nditer(pos_y):
if x > 20:
test_image[(y, x)] = sobel[(y, x)]
save_image('testimage' + str(num), test_image)
if angle < -75:
# front teeth
test_image = sobel
save_image('testimage' + str(num), test_image)
return True
def test_for_lap(image):
global stack_img
image = cv2.medianBlur(image,5)
# cv2.imshow("blur",image)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
# if debug:
# showimage("blur",blur)
sobel = convolve_sobel(img=image,
threshold=30,
sobel_kernel_left_right=True,
sobel_kernel_right_left=True,
sobel_kernel_top_bottom=False,
sobel_kernel_bottom_top=False,
sobel_kernel_diagonal_top_left=False,
sobel_kernel_diagonal_bottom_left=False,
sobel_kernel_diagonal_top_right=False,
sobel_kernel_diagonal_bottom_right=False)
sobel = cv2.convertScaleAbs(sobel)
if debug:
showimage("sobel",sobel)
gaus = cv2.GaussianBlur(sobel, (3,3), -1)
if debug:
showimage("Gaussian",gaus)
_,thresh = cv2.threshold(gaus,200,255,cv2.THRESH_BINARY)
if debug:
showimage("thresh",thresh)
stack_img = cv2.bitwise_or(stack_img,thresh)
if debug:
showimage("stack image",stack_img)
def flank_dent_detection(img, num):
accum = np.zeros_like(img)
test_image = np.zeros_like(img)
ksize = 9
for theta in np.arange(0, np.pi, np.pi / 4):
kernel = cv2.getGaborKernel((ksize, ksize),
10,
theta,
18,
0.25,
0,
ktype=cv2.CV_32F)
kernel /= 1.5 * kernel.sum()
fimg = cv2.filter2D(img, cv2.CV_8UC3, kernel)
np.maximum(accum, fimg, accum)
#
showimage('A2_accum', accum)
_, thresh = cv2.threshold(accum, 161, 255, cv2.THRESH_BINARY)
showimage("A3_thresh" + str(num), thresh)
sobel = convolve_sobel(img=accum,
threshold=10,
sobel_kernel_left_right=True,
sobel_kernel_right_left=True,
sobel_kernel_top_bottom=True,
sobel_kernel_bottom_top=True,
sobel_kernel_diagonal_top_left=True,
sobel_kernel_diagonal_bottom_left=False,
sobel_kernel_diagonal_top_right=True,
sobel_kernel_diagonal_bottom_right=False)
sobel = cv2.convertScaleAbs(sobel)
showimage("A2_sobel" + str(num), sobel)
pos = np.where(accum < 162)
test_image[pos] = 255
showimage("A5_test_image" + str(num), test_image)
return test_image
def test_for_lap(image):
global stack_img
blur = cv2.medianBlur(image, 3)
# if debug:
# showimage("blur",blur)
sobel = convolve_sobel(img=blur,
threshold=50,
sobel_kernel_left_right=True,
sobel_kernel_right_left=True,
sobel_kernel_top_bottom=True,
sobel_kernel_bottom_top=True,
sobel_kernel_diagonal_top_left=False,
sobel_kernel_diagonal_bottom_left=False,
sobel_kernel_diagonal_top_right=False,
sobel_kernel_diagonal_bottom_right=False)
sobel = cv2.convertScaleAbs(sobel)
if debug:
showimage("sobel", sobel)
gaus = cv2.GaussianBlur(sobel, (15, 15), -1)
if debug:
showimage("Gaussian", gaus)
_, thresh = cv2.threshold(gaus, 200, 255, cv2.THRESH_BINARY)
if debug:
showimage("thresh", thresh)
stack_img = cv2.bitwise_or(stack_img, thresh)
if debug:
showimage("stack image", stack_img)