So this video was a play around with opencv. An image has 3 channels: blue, green an red. I’ve swapped the blue and red color channels and found some interesting stuff!
Demo:
Things Required:
- Jetson Nano
- Keyboard
- Mouse
- HDMI Screen
- Raspberry Pi Camera
- External Power Supply
Reference Material:
- You can check out this video for the project: (LINK)
Code:
View on/Download from Github: (LINK)
import cv2
import numpy as np
dispW= 320
dispH= 240
flip=2
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()
#gray= cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#b=cv2.split(frame)[0]
#g=cv2.split(frame)[1]
#r=cv2.split(frame)[2]
b,g,r= cv2.split(frame)
blank= np.zeros([240,320,1], np.uint8)
blue= cv2.merge((b, blank, blank))
green= cv2.merge((blank, g, blank))
red= cv2.merge((blank, blank, r))
r[:]= r[:]*0.1
merge= cv2.merge((r,g,b))
cv2.imshow('merge', merge)
cv2.moveWindow('merge', 800,0)
cv2.imshow('Blue', blue)
cv2.moveWindow('Blue', 0, 300)
cv2.imshow('Green', green)
cv2.moveWindow('Green', 400, 300)
cv2.imshow('Red', red)
cv2.moveWindow('Red', 400,0)
#cv2.imshow('Gray', gray)
#cv2.moveWindow('Gray', 400, 0)
cv2.imshow('nanoCam', frame)
cv2.moveWindow('nanoCam', 0,0)
#print(gray.shape)
if cv2.waitKey(1) == ord('q'):
break
cam.release()
cv2.destroyAllWindows()Stay Tuned for upcoming posts on Jetson Nano and AI Projects! Want to be the first to know when a new and amazing post comes up?? Then feel free to subscribe!
Happy Learning!!
