CODEWITHSUNDEEP
pythonopencv
eSquirel
eSquirel

Reputation: 51

What color space are the lower/upper arguments for cv2.inRange?

I'm trying to create a mask for a color range. I know that I need to convert the image to HSV before passing that into inRange. The next two arguments for inRange are the lower value and upper value for the color we're creating a mask for.

What color space are the lower and upper in?

I've seen HSV and BGR according to answers on here. The documentation does not call out the specific color space to use. For example, this answer (How to define a threshold value to detect only green colour objects in an image :Opencv) says the values should be in HSV but passes in values that seem like BGR (e.g. 255). PS - any tips on tools/tricks to pick a specific range? I've been using Google's color picker

Upvotes: 1

Views: 1917

Answers (2)

Rômulo Férrer Filho
Rômulo Férrer Filho

Reputation: 129

The cv2.inRange() function only checks if array elements lie between the elements of two other arrays.

So if your src array is shaped as BGR or RGB or HSV your Upper and Lower boundaries should be in the same colorspace. Usually for color segmentation the HSV colorspace is more used, but you can try other colorspaces too.

Upvotes: 3

sourab maity
sourab maity

Reputation: 1045

use the following code to find a specific object HSV color value. And set this HSV value in cv2.inRange lower and upper value. It is a opencv program using your device camera and track-bar you can find HSV upper and lower value:

import cv2
import numpy as np


def nothing(x):
    pass


cap = cv2.VideoCapture(0)
cv2.namedWindow("Trackbars")

cv2.createTrackbar("L - H", "Trackbars", 0, 255, nothing)
cv2.createTrackbar("L - S", "Trackbars", 0, 255, nothing)
cv2.createTrackbar("L - V", "Trackbars", 0, 255, nothing)
cv2.createTrackbar("U - H", "Trackbars", 255, 255, nothing)
cv2.createTrackbar("U - S", "Trackbars", 255, 255, nothing)
cv2.createTrackbar("U - V", "Trackbars", 255, 255, nothing)

while True:
    _, frame = cap.read()
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    l_h = cv2.getTrackbarPos("L - H", "Trackbars")
    l_s = cv2.getTrackbarPos("L - S", "Trackbars")
    l_v = cv2.getTrackbarPos("L - V", "Trackbars")
    u_h = cv2.getTrackbarPos("U - H", "Trackbars")
    u_s = cv2.getTrackbarPos("U - S", "Trackbars")
    u_v = cv2.getTrackbarPos("U - V", "Trackbars")

    lower_blue = np.array([l_h, l_s, l_v])
    upper_blue = np.array([u_h, u_s, u_v])
    mask = cv2.inRange(hsv, lower_blue, upper_blue)
    mask2 = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
    result = cv2.bitwise_and(frame, frame, mask=mask)

    cv2.imshow("frame", frame)
    cv2.imshow("mask", mask)
    cv2.imshow("result", result)

    key = cv2.waitKey(1)
    if key == 27:
        break

cap.release()
cv2.destroyAllWindows()

Output: enter image description here for my object red HSV upper value-[193,188,186], lower value-[135,127,95]

Upvotes: 3

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