def myHMin(image, intensiteRelative, struct):
gamma8 = strel.build("square", 1, None)
for i in range(0, image.shape[0]):
for j in range(0, image.shape[1]):
if (image[i][j] + intensiteRelative <= 255):
image[i][j] = image[i][j] + intensiteRelative
else:
image[i][j] = 255
return myReconClose(image, struct, gamma8)
def myHMax(image, intensiteRelative, struct):
gamma8 = strel.build("square", 1, None)
for i in range(0, image.shape[0]):
for j in range(0, image.shape[1]):
if (image[i][j] - intensiteRelative >= 0):
image[i][j] = image[i][j] - intensiteRelative
else:
image[i][j] = 0
return myReconOpen(image, struct, gamma8)
def filterElementsOnEdge(image):
gamma8 = strel.build("square", 1, None)
imagePix = np.zeros(image.shape, image.dtype)
for i in range(0, image.shape[0]):
for j in range(0, image.shape[1]):
if image[i, j] == 255 and (i == 0 or i == image.shape[0] - 1
or j == 0 or j == image.shape[1] - 1):
imagePix[i, j] = 255
recInf = myReconInf(imagePix, image, gamma8)
image = image - recInf
return image
def countElements(image):
gamma8 = strel.build("square", 1, None)
imagePix = np.zeros(image.shape, image.dtype)
count = 0
for i in range(0, image.shape[0]):
for j in range(0, image.shape[1]):
if image[i, j] == 255:
imagePix[i, j] = 255
recInf = myReconInf(imagePix, image, gamma8)
count += 1
image = image - recInf
return count
import cv2
import numpy as np
from src.main.python.myLibs.ImageProcessing.MorphologicalImageProcessing import structElement as strel, morpho, myimage
imagename = '../../../../resources/images/feuille1.png'
image = cv2.imread(imagename)
disc = strel.build("disc", 5, None)
gamma8 = strel.build("square", 5, None)
gamma4 = strel.build("diamond", 1, None)
gamma8list = strel.build_as_list("square", 1, None)
morpho.displayImage("Original Image", image)
# Unify background
image = 255 - image[:, :, 0]
image = image - morpho.myOpen(image, gamma8)
image = morpho.myThreshold(image, 60)
morpho.displayImage("Image threshold", image)
# Seeking orientation
sums = []
imageGrad = np.zeros(image.shape, image.dtype)
for angle in range(0, 90):
line = strel.build("line", 100, angle)
imageGrad = morpho.myOpen(image, line)
sums.append((sum(map(sum, image - imageGrad)), angle))
orient = min(sums[:])[1] - 90
print("orientation : " + str(orient))
import cv2
from src.main.python.myLibs.ImageProcessing.MorphologicalImageProcessing import structElement as strel, morpho
#imagePath = '../../../../resources/images/papier_60.png'
#imagePath = '../../../../resources/images/papier_15.png'
imagePath = '../../../../resources/images/papier_35.png'
image = cv2.imread(imagePath)
morpho.displayImage("Image", image)
# Keep only the red color (better for these images)
image = image[:, :, 2]
# Test for various different angles
sums = []
for angle in range(-90, 90, 1):
structLigne = strel.build("line", 40, angle)
gradImage = morpho.myGrad(image, structLigne)
sums.append((sum(map(sum, gradImage)), angle))
orient = min(sums[:])[1]
print("Orientation of the object : " + str(orient) + " degree")
key = cv2.waitKey(0)
cv2.destroyAllWindows()
import cv2
from src.main.python.myLibs.ImageProcessing.MorphologicalImageProcessing import structElement as strel, morpho
imagePath = '../../../../resources/images/numbers.png'
image = cv2.imread(imagePath)
morpho.displayImage("Original", image)
struct = strel.build("disc", 5, None)
open = morpho.myOpen(image, struct)
morpho.displayImage("Open", open)
image = image - open
image = morpho.myThreshold(image, 50)
morpho.displayImage("Final Image", image)
key = cv2.waitKey(0)
cv2.destroyAllWindows()
while 1:
print('Select object')
pointMarks = myimage.display_and_click_image(image, colorMarks)
if len(pointMarks) > 0:
marks = np.zeros([image.shape[0], image.shape[1]], np.dtype)
for mark in pointMarks:
marks[mark[0], mark[1]] = 255
marksList.append(marks)
else:
print('End of Selection')
break
image = image[:, :, 0]
gamma8 = strel.build("square", 1, None)
gamma8list = strel.build_as_list("square", 1, None)
gradient = morpho.myGrad(image, gamma8)
watershed = morpho.watersheds(gradient, marksList, gamma8list)
numberObjects = len(marksList)
watershed = watershed * (255 / (numberObjects + 1))
image = cv2.imread(imagename)
morpho.displayImage("Original image", image)
morpho.displayImage("After Watersheds", watershed)
key = cv2.waitKey(0)