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 = morpho.myReconInf(imagePix, image, gamma8)
image = image - recInf
(width, length) = firstGrainSizes(recInf)
outputImage = outputImage + (recInf / 255 * (255 - width * 10))
mesures.append((i, j, width, length))
return (outputImage, mesures)
image = cv2.imread('Images/rice.png')
morpho.displayImage("Original Image", image)
image = image[:, :, 0]
gamma8 = strel.build("square", 1, None)
struct = strel.build("disc", 5, None)
open = morpho.myOpen(image, struct)
image = image - open
image = morpho.myThreshold(image, 50)
morpho.displayImage("Image filtered", image)
import cv2
import numpy as np
from myLibs.ImageProcessing.MorphologicalImageProcessing import structElement as strel, morpho, myimage
imagename = 'Images/chromosomes.tif'
image = cv2.imread(imagename)[:, :, 0]
disc = strel.build("disc", 5, None)
gamma8 = strel.build("square", 1, None)
morpho.displayImage("Original Image", image)
count = morpho.countElements(image)
while count > 4:
image = morpho.myDilat(image, disc)
count = morpho.countElements(image)
print("Clusters identified")
imagePix = np.zeros(image.shape, image.dtype)
imageFin = np.zeros(image.shape, image.dtype)
idcluster = 0
for i in range(0, image.shape[0]):
for j in range(0, image.shape[1]):
if image[i, j] == 255:
color = (idcluster + 1) * 50
imagePix[i, j] = 255
recInf = morpho.myReconInf(imagePix, image, gamma8)
idcluster += 1
import cv2
import numpy
from myLibs.ImageProcessing.MorphologicalImageProcessing import structElement as strel, morpho
image = cv2.imread('Images/aeroport2.png')
image = image[:, :, 0]
morpho.displayImage("Original", image)
gamma8 = strel.build("square", 1, None)
imageFiltered = numpy.ones(image.shape, image.dtype)
imageFiltered = imageFiltered * 255
for angle in range(-90, 90, 1):
structLigne = strel.build("line", 50, angle)
closeImage = morpho.myClose(image, structLigne)
imageFiltered = numpy.minimum(imageFiltered, closeImage)
morpho.displayImage("After filter", imageFiltered)
imageFiltered = morpho.myThreshold(imageFiltered, 40)
morpho.displayImage("After threshold", imageFiltered)
structLigne = strel.build("square", 2, None)
imageFiltered = morpho.myClose(imageFiltered, structLigne)
morpho.displayImage("After close", imageFiltered)
image = morpho.myGrad(imageFiltered, gamma8)
morpho.displayImage("After gradient", image)
import cv2
import numpy
from myLibs.ImageProcessing.MorphologicalImageProcessing import structElement as strel, morpho
image = cv2.imread('Images/comete.jpg')
image = image[:, :, 0]
morpho.displayImage("Original Image", image)
gamma8 = strel.build("square", 1, None)
disc = strel.build("disc", 3, None)
relativeIntensity = 50
image = image - morpho.myHMax(image, relativeIntensity, disc)
#morpho.displayImage("Filtrage Faible Intensite", image)
threshold = 50
for i in range(0, image.shape[0]):
for j in range(0, image.shape[1]):
if image[i][j] < 50:
image[i][j] = 0
else:
image[i][j] = 255
morpho.displayImage("After threshold", image)
print("press a key to start counting stars")
key = cv2.waitKey(0)
print("counting started. It will take some time. Image size is " +
str(image.shape[0]) + " x " + str(image.shape[1]))
import cv2
import numpy as np
from myLibs.ImageProcessing.MorphologicalImageProcessing import structElement as strel, morpho, myimage
image = cv2.imread('Images/bloodcells.png')
disc = strel.build("disc", 5, None)
gamma8 = strel.build("square", 1, None)
gamma4 = strel.build("diamond", 1, None)
square2 = strel.build("square", 2, None)
gamma8list = strel.build_as_list("square", 1, None)
morpho.displayImage("Original Image", image)
image = image[:,:,0]
relativeIntensity = 50
couleurMarqueur = (20,20,200)
image2 = image-morpho.myHMax(image,relativeIntensity,disc)
image2 = morpho.myThreshold(image,relativeIntensity)
border = np.zeros(image.shape, image.dtype)
border[0,:]=255
border[border.shape[0]-1,:]=255
border[:,0]=255
border[:,border.shape[1]-1]=255
image3=morpho.myReconInf(border,image,gamma8)