Question

The following code lines represent a simple expert system about a

cancer image detection under computer vision. You are required to

identify and explain the effect of the different command lines;

3import cv2

import numpy as np

cap = cv2.VideoCapture(0)

while(1):

_, frame = cap.read()

hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

lower_red = np.array([0,0,0])

upper_red = np.array([255,255,180])

mask = cv2.inRange(hsv, lower_red, upper_red)

res = cv2.bitwise_and(frame,frame, mask= mask)

cv2.imshow('frame',frame)

cv2.imshow('mask',mask)

cv2.imshow('res',res)

k = cv2.waitKey(5) & 0xFF

if k == 27:

break

cv2.destroyAllWindows()

cap.release()

Answer 1

# Importing a library OpenCV for working with images and videos
import cv2 
# Importing a library NumPy for working with numeric data
import numpy as np 
# Capture streaming video from camcorder 0
cap = cv2.VideoCapture(0) 
# Creating an endless loop
while(1):
# Receive video frame parameter size is ignored
    _, frame = cap.read() 
# Convert image frame from BGR to HSV
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
#  define range of color in HSV
    lower_red = np.array([0,0,0])
    upper_red = np.array([255,255,180])
# Threshold HSV image to get only the selected color
    mask = cv2.inRange(hsv, lower_red, upper_red) 
# Bitwise-AND mask and original image
    res = cv2.bitwise_and(frame,frame, mask= mask)
# Show the video frame of the mask used and the result of the mask overlay
    cv2.imshow('frame',frame)
    cv2.imshow('mask',mask)
    cv2.imshow('res',res) 
# Pause for 5 milliseconds if ESC is pressed, exit from endless cycle
    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break 
# Closing all windows created OpenCV
cv2.destroyAllWindows()
# Freeing up the resources of the involved video camera
cap.release()