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Commit 1f5c442

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blob detection with dfs
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‎Blob Detection/BlobDetection.py‎

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import cv2
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from tkinter.filedialog import *
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# we will find number of blobs with pixel value 255 in the following image
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# finding binary image
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print("\nImage should preferably be white (lighter) blobs on black (darker) background ")
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photo = askopenfilename()
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img = cv2.imread(photo,cv2.IMREAD_GRAYSCALE)
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img = cv2.resize(img,(300,300))
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n,l = img.shape
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count = 0
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# blur the image
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ksize = (5,5) # kernel size
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img = cv2.blur(img,ksize)
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# thresholding the image
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for i in range(n):
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for j in range(l):
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if(img[i,j]<=127):
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img[i,j]=0
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else:
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img[i,j]=255
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def dfs(i,j):
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img[i,j]=127 # implying that we have visited this pixel for further reference
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if (i-1>=0):
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if(img[i-1,j]==255):
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dfs(i-1,j)
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if (j-1>=0):
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if(img[i,j-1]==255):
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dfs(i,j-1)
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if (j+1<l):
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if(img[i,j+1]==255):
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dfs(i,j+1)
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if (i+1<n):
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if(img[i+1,j]==255):
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dfs(i+1,j)
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if((i-1>=0) and (j-1>=0)):
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if(img[i-1,j-1]==255):
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dfs(i-1,j-1)
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if((i-1>=0) and (j+1<l)):
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if(img[i-1,j+1]==255):
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dfs(i-1,j+1)
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if((i+1<n) and (j-1>=0)):
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if(img[i+1,j-1]==255):
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dfs(i+1,j-1)
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if((i+1<n) and (j+1<l)):
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if(img[i+1,j+1]==255):
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dfs(i+1,j+1)
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cv2.namedWindow('image',cv2.WINDOW_NORMAL)
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cv2.imshow("image",img)
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cv2.waitKey(1000)
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for i in range(n):
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for j in range(l):
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if(img[i,j]==255):
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count += 1 #to count number of white blobs
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dfs(i,j)
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print("count is",count)

‎Blob Detection/ReadMe.md‎

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# Blob detection
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This python script finds blobs in an image using DFS algorithm.
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## Setup Instructions
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### Install python3
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sudo apt-get install python3
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### Install pip (package installer for python)
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sudo apt-get install python3-pip
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### Install OpenCV library with pip
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pip3 install opencv-python
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### Install tkinter library
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sudo apt-get install python3-tk
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## Details/Output
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The program asks user to select an image to count the number of blobs.
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The image should preferably have **lighter blobs on a darker background**.
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Eg. white blobs on a black background
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The output is the count of blobs in the image.
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## Author
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Github: invigorzz313

‎Blob Detection/blobImg.png‎

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