Exudates.py

import numpy as np
import cv2
#from matplotlib import pyplot as plt



class ExtractExudates:
    
    jpegImg = 0
    grayImg = 0
    curImg = 0

    def setImage(self, img):
        self.jpegImg = img
        self.curImg = np.array(img)    ##Convert jpegFile to numpy array (Required for CV2)

    def getImage(self):
        return self.curImg
        
    def greenComp(self):
    ###Extracting Green Component
        gcImg = self.curImg[:,:,1]
        self.curImg = gcImg

    def applyCLAHE(self):
    #Applying Contrast Limited Adaptive Histogram Equalization (CLAHE)
        clahe = cv2.createCLAHE()
        clImg = clahe.apply(self.curImg)
        self.curImg = clImg
        
# create a CLAHE object (Arguments are optional).
#clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
#claheImg = clahe.apply(clImg)
#cv2.imwrite('clahe_2.jpg',claheImg)

    def applyDilation(self):
        #Creating Structurig Element
        strEl = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(6,6))
        #Dilation
        dilateImg = cv2.dilate(self.curImg, strEl)
        self.curImg = dilateImg

    def applyThreshold(self):
        #Thresholding with Complement/Inverse
        retValue, threshImg = cv2.threshold(self.curImg, 220, 220, cv2.THRESH_BINARY)
        self.curImg = threshImg

    def applyMedianFilter(self):
        #Median Filtering
        medianImg = cv2.medianBlur(self.curImg,5)
        self.curImg = medianImg