hsvcalib.py

import cv2
import numpy as np


cap = cv2.VideoCapture(0)


def adjust_gamma(image, gamma=1.0):

    invGamma = 1.0 / gamma
    table = np.array([((i / 255.0) ** invGamma) * 255
                      for i in np.arange(0, 256)]).astype("uint8")

    return cv2.LUT(image, table)

def nothing(x):
    pass
cv2.namedWindow('result', cv2.WINDOW_NORMAL)
h,s,v = 100,100,100



# Creating track bar
cv2.createTrackbar('h', 'result',0,179,nothing)
cv2.createTrackbar('s', 'result',0,255,nothing)
cv2.createTrackbar('v', 'result',0,255,nothing)



while(1):
    ar = []
    _, frame = cap.read()
    # frame = adjust_gamma(frame, gamma=1.2)
    #converting to HSV
    hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)

    # get info from track bar and appy to result
    h = cv2.getTrackbarPos('h','result')
    s = cv2.getTrackbarPos('s','result')
    v = cv2.getTrackbarPos('v','result')

    # Normal masking algorithm
    lower_blue = np.array([h,s,v])
    upper_blue = np.array([180,255,255])

    mask = cv2.inRange(hsv,lower_blue, upper_blue)

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

    cv2.imshow('result',result)

    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break

ar.append(h)
ar.append(s)
ar.append(v)


cap.release()
cv2.destroyAllWindows()