使用python opencv跟踪白色 [英] Tracking white color using python opencv

问题描述

我想使用网络摄像头和python opencv跟踪白色.我已经有了跟踪蓝色的代码.

I would like to track white color using webcam and python opencv. I already have the code to track blue color.

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

# define range of blue color in HSV
lower_blue = np.array([110,100,100])
upper_blue = np.array([130,255,255])

#How to define this range for white color


# Threshold the HSV image to get only blue colors
mask = cv2.inRange(hsv, lower_blue, upper_blue)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame,frame, mask= mask)

cv2.imshow('frame',frame)
cv2.imshow('mask',mask)
cv2.imshow('res',res)

我应该给出什么值作为下限和上限 来跟踪白色 ！ 我尝试更改值，但得到其他颜色，但白色却没有运气！！！

what values should I give as lower bound and upper bound to track white color!!?? I tried changing values and I got other colors but no luck with the white color!!!

是将HSV值或BGR值指定为上下限吗?

is that HSV values or BGR values specified as lower and upper bounds???

PS:我必须以二进制图像的形式获得最后的结果，以便进行进一步处理！

PS : I must get the last result as a binary image for further processing!!

请帮助我！

推荐答案

我写这是为了跟踪白色:

I wrote this for tracking white color :

import cv2
import numpy as np

cap = cv2.VideoCapture(0)

while(1):

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

    # define range of white color in HSV
    # change it according to your need !
    lower_white = np.array([0,0,0], dtype=np.uint8)
    upper_white = np.array([0,0,255], dtype=np.uint8)

    # Threshold the HSV image to get only white colors
    mask = cv2.inRange(hsv, lower_white, upper_white)
    # Bitwise-AND mask and original image
    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()

我试图跟踪手机的白屏并得到了这个信息:

I tried to track the white screen of my phone and got this :

您可以尝试更改HSV值 您也可以尝试如Legat所说的HSL色彩空间，这样会更准确

You can try changing the HSV values You might also try HSL color space as Legat said, it would be more accurate

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