I try this with my 7 ports hub. And it has blue led power supply.
#!/usr/bin/env python3.4
import cv2
import numpy as np
camera_feed = cv2.VideoCapture(0)
while True:
_,frame = camera_feed.read()
#Convert the current frame to HSV
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
#Define the threshold for finding a blue object with hsv
lower_blue = np.array([110,50,50])
upper_blue = np.array([130,255,255])
#Create a binary image, where anything blue appears white and everything else is black
mask = cv2.inRange(hsv, lower_blue, upper_blue)
#Get rid of background noise using erosion and fill in the holes using dilation and erode the final image on last time
element = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))
mask = cv2.erode(mask,element, iterations=2)
mask = cv2.dilate(mask,element,iterations=2)
mask = cv2.erode(mask,element)
#Create Contours for all blue objects
_, contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
maximumArea = 0
bestContour = None
for contour in contours:
currentArea = cv2.contourArea(contour)
if currentArea > maximumArea:
bestContour = contour
maximumArea = currentArea
#Create a bounding box around the biggest blue object
if bestContour is not None:
x,y,w,h = cv2.boundingRect(bestContour)
cv2.rectangle(frame, (x,y),(x+w,y+h), (0,0,255), 3)
cv2.circle(frame,(x, y), 2,(0, 255, 0), 20)
#Show the original camera feed with a bounding box overlayed
cv2.imshow('frame',frame)
#Show the contours in a seperate window
cv2.imshow('mask',mask)
#Use this command to prevent freezes in the feed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()
With an infrared camera, the LED should be the brightest object in the image. You can try blob detection with
SimpleBlobDetector
class maybe.@Eduardo thanks for replying, but the problem is filtering the background in such a manner that it only detects my LED, and nothing else. By using an ir camera i could be getting other ir noise in the backgorund. Please let me know if you could help me out with that.