要检测红色,可以使用HSV颜色阈值脚本来确定较低/较高的阈值,然后使用cv2.bitwise_and()
来获取遮罩。使用此输入图像,
我们得到这个结果并掩盖
码
import numpy as np
import cv2
image = cv2.imread('1.jpg')
result = image.copy()
image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
lower = np.array([155,25,0])
upper = np.array([179,255,255])
mask = cv2.inRange(image, lower, upper)
result = cv2.bitwise_and(result, result, mask=mask)
cv2.imshow('mask', mask)
cv2.imshow('result', result)
cv2.waitKey()
带滑块的HSV颜色阈值脚本,记住要更改图像文件路径
import cv2
import sys
import numpy as np
def nothing(x):
pass
# Load in image
image = cv2.imread('1.jpg')
# Create a window
cv2.namedWindow('image')
# create trackbars for color change
cv2.createTrackbar('HMin','image',0,179,nothing) # Hue is from 0-179 for Opencv
cv2.createTrackbar('SMin','image',0,255,nothing)
cv2.createTrackbar('VMin','image',0,255,nothing)
cv2.createTrackbar('HMax','image',0,179,nothing)
cv2.createTrackbar('SMax','image',0,255,nothing)
cv2.createTrackbar('VMax','image',0,255,nothing)
# Set default value for MAX HSV trackbars.
cv2.setTrackbarPos('HMax', 'image', 179)
cv2.setTrackbarPos('SMax', 'image', 255)
cv2.setTrackbarPos('VMax', 'image', 255)
# Initialize to check if HSV min/max value changes
hMin = sMin = vMin = hMax = sMax = vMax = 0
phMin = psMin = pvMin = phMax = psMax = pvMax = 0
output = image
wait_time = 33
while(1):
# get current positions of all trackbars
hMin = cv2.getTrackbarPos('HMin','image')
sMin = cv2.getTrackbarPos('SMin','image')
vMin = cv2.getTrackbarPos('VMin','image')
hMax = cv2.getTrackbarPos('HMax','image')
sMax = cv2.getTrackbarPos('SMax','image')
vMax = cv2.getTrackbarPos('VMax','image')
# Set minimum and max HSV values to display
lower = np.array([hMin, sMin, vMin])
upper = np.array([hMax, sMax, vMax])
# Create HSV Image and threshold into a range.
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, lower, upper)
output = cv2.bitwise_and(image,image, mask= mask)
# Print if there is a change in HSV value
if( (phMin != hMin) | (psMin != sMin) | (pvMin != vMin) | (phMax != hMax) | (psMax != sMax) | (pvMax != vMax) ):
print("(hMin = %d , sMin = %d, vMin = %d), (hMax = %d , sMax = %d, vMax = %d)" % (hMin , sMin , vMin, hMax, sMax , vMax))
phMin = hMin
psMin = sMin
pvMin = vMin
phMax = hMax
psMax = sMax
pvMax = vMax
# Display output image
cv2.imshow('image',output)
# Wait longer to prevent freeze for videos.
if cv2.waitKey(wait_time) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()
0
我正在尝试从图像中提取红色。我有应用阈值的代码,仅保留指定范围内的值:
但是,正如我检查的那样,红色的色相值可以在0到10的范围内,也可以在170到180的范围内。因此,我想保留这两个范围中任何一个的色相值。我尝试将阈值从10设置为170,并使用
cv2.bitwise_not()
函数,但随后我也获得了所有白色。我认为最好的选择是为每个范围创建一个遮罩并同时使用它们,因此我必须以某种方式将它们合并在一起,然后再继续。有没有办法我可以使用OpenCV连接两个蒙版?还是有其他方法可以实现我的目标?
编辑。我带来的不是很多优雅的方法,但是可以解决的问题:
这几乎可以满足我的需求,并且OpenCV的功能可能几乎相同,但是如果有更好的方法(使用一些专用功能并编写更少的代码),请与我分享。 :)