Jetson Nano and OpenCV: Masking an image

So here we’ll learn about the concept of masking through this project.

Demo:

Things Required:

  1. Jetson Nano
  2. Keyboard
  3. Mouse
  4. HDMI Screen
  5. Raspberry Pi Camera
  6. External Power Supply

Reference Material:

  1. You can check out this video for the project: (LINK)

Code:

Note that code below is in python

View on/Download from Github: (LINK)

import cv2
dispW=320
dispH=240
flip=2

cvLogo= cv2.imread('/home/aarushi/Desktop/pyPro/cv.jpg')
cvLogo=cv2.resize(cvLogo, (320,240))
cv2.imshow('Original', cvLogo)
cv2.moveWindow('Original', 0,300)

cvLogoGray= cv2.cvtColor(cvLogo, cv2.COLOR_BGR2GRAY)
cv2.imshow('GrayLogo', cvLogoGray)
cv2.moveWindow('GrayLogo', 380, 0)

_,BGMask= cv2.threshold(cvLogoGray, 180, 255, cv2.THRESH_BINARY)
cv2.imshow('BGMask', BGMask)
cv2.moveWindow('BGMask', 380, 300)

FGMask= cv2.bitwise_not(BGMask)
cv2.imshow('FGMask', FGMask)
cv2.moveWindow('FGMask', 760, 0)

FG= cv2.bitwise_and(cvLogo, cvLogo, mask=FGMask)
cv2.imshow('FG', FG)
cv2.moveWindow('FG', 760, 300)

camSet='nvarguscamerasrc !  video/x-raw(memory:NVMM), width=3264, height=2464, format=NV12, framerate=21/1 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(dispW)+', height='+str(dispH)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! appsink'
cam=cv2.VideoCapture(camSet)
while True:
    ret, frame= cam.read()
    cv2.imshow('nanCam', frame)
    cv2.moveWindow('nanCam', 0,0)
    if cv2.waitKey(1) == ord('q'):
        break
cam.release()
cv2.destroyAllWindows()

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Happy Learning!!

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