explore_hsv_masks.py

"""
Identifying red regions/masks in image

Source:  https://stackoverflow.com/questions/30331944/finding-red-color-in-image-using-python-opencv
"""
import cv2
import numpy as np


#blurring and smoothin
img1=cv2.imread('data/test5.jpg', 1)

hsv = cv2.cvtColor(img1,cv2.COLOR_BGR2HSV)

#lower red
lower_red = np.array([0,50,50])
upper_red = np.array([10,255,255])


#upper red
lower_red2 = np.array([170,50,50])
upper_red2 = np.array([180,255,255])

while(1):
    mask = cv2.inRange(hsv, lower_red, upper_red)
    res = cv2.bitwise_and(img1,img1, mask= mask)


    mask2 = cv2.inRange(hsv, lower_red2, upper_red2)
    res2 = cv2.bitwise_and(img1,img1, mask= mask2)

    img3 = res+res2
    img4 = cv2.add(res,res2)
    img5 = cv2.addWeighted(res,0.5,res2,0.5,0)


    kernel = np.ones((15,15),np.float32)/225
    smoothed = cv2.filter2D(res,-1,kernel)
    smoothed2 = cv2.filter2D(img3,-1,kernel)

    cv2.imshow('Original',img1)
    cv2.imshow('Averaging',smoothed)
    cv2.imshow('mask',mask)
    cv2.imshow('res',res)
    cv2.imshow('mask2',mask2)
    cv2.imshow('res2',res2)
    cv2.imshow('res3',img3)
    cv2.imshow('res4',img4)
    cv2.imshow('res5',img5)
    cv2.imshow('smooth2',smoothed2)

    # Wait longer to prevent freeze for videos.
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()