Aylin Öztürk

import matplotlib.pyplot as plt import numpy as np def rgbToGrayLevel ( img ): img3 = np.zeros((img.shape[ 0 ], img.shape[ 1 ])) for i in range (img.shape[ 0 ]): for j in range (img.shape[ 1 ]): img3[i,j] = sum (img[i,j,:]) / 3 return img3 def redIntensity ( img ): # rgb - 012 img2 = np.zeros((img.shape[ 0 ], img.shape[ 1 ], 3 ), dtype = np.uint8) for i in range (img.shape[ 0 ]): for j in range (img.shape[ 1 ]): if (img[i,j, 0 ] + 50 > 255 ): img2[i,j, 0 ] = 255 else : img2[i,j, 0 ] = img[i,j, 0 ] + 50 img2[i,j, 1 ] = img[i,j, 1 ] img2[i,j, 2 ] = img[i,j, 2 ] return img2 def grayLevelIntensity ( img ): # 255'e yaklaştıkça beyazlaşır img4 = np.zeros((img.shape[ 0 ], img.shape[ 1 ])) for i in range (img.shape[ 0 ]): for j in range (img.shape[ 1 ]): if (img[i,j] - 75 < 0 ): img4[i,j] = 0 else : img4[i,j] = img[i,j] - 75 return img4 img1 = plt.imread( ' test4.jpg ' ) redIntensityImg = redIntensity(i...

import matplotlib.pyplot as plt import numpy as np class MyMatrix (): def __init__ ( self , _d , _f ): self .D = _d self .f = _f def rgbToBW ( img , threshold = 120 ): bw = np.zeros((img.shape[ 0 ], img.shape[ 1 ])) for i in range (img.shape[ 0 ]): for j in range (img.shape[ 1 ]): if ( sum (img[i,j,:]) / 3 > threshold): bw[i,j] = 1 else : bw[i,j] = 0 return bw def createDF ( img ): d = set () for i in range (img.shape[ 0 ]): for j in range (img.shape[ 1 ]): if img[i,j] == 1 : d.add((i,j)) f = {} for i,j in d: f[(i,j)] = 1 return MyMatrix(d,f) img1 = plt.imread( ' test3.jpg ' ) bwImg = rgbToBW(img1) sparseImg = createDF(bwImg) plt.subplot( 1 , 2 , 1 ), plt.imshow(img1) plt.subplot( 1 , 2 , 2 ), plt.imshow(bwImg, plt.cm.binary) plt.show() ...

import   matplotlib.pyplot   as   plt import   numpy   as   np def   convert_RGB_to_monochrome_BW (image_1,threshold =100 ):     img_1 = plt . imread(image_1)     img_2 = np . zeros((img_1 . shape[ 0 ],img_1 . shape[ 1 ]))      for  i  in   range (img_2 . shape[ 0 ]):          for  j  in   range (img_2 . shape[ 1 ]):              if (img_1[i,j, 0 ] /3+ img_1[i,j, 1 ] /3+ img_1[i,j, 1 ] /3 ) > threshold:                 img_2[i,j] =0              else :                 img_2[i,j] =1      return  img_2 def   define_mask_1 (...