如何在 OpenCV 中定义 HSV 颜色的边界
How to define boundaries for HSV color in OpenCV
我正在尝试使用颜色 space 执行图像分割。例如,乡村地区。我不确定如何 select cv2.inRange()
的边界。
img = cv2.imread(file)
img_hsv=cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
lower_bound = np.array([0,70,70])
upper_bound = np.array([20,200,150])
mask0 = cv2.inRange(img_hsv, lower_bound, upper_bound)
lower_bound = np.array([170,70,70])
upper_bound = np.array([180,200,150])
mask1 = cv2.inRange(img_hsv, lower_bound, upper_bound)
# add both masks
mask = mask0+mask1
output_img = cv2.bitwise_and(img,img,mask=mask)
如果您只想分割生锈的部分而不是其他部分,我尝试了一些代码如下。
import cv2
import numpy as np
img = cv2.imread("rust1.png",1)
img_hsv=cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
lower_bound = np.array([120, 80, 0],dtype="uint8")
upper_bound = np.array([255, 255, 80],dtype="uint8")
mask0 = cv2.inRange(img_hsv, lower_bound, upper_bound)
cv2.imshow("mask",mask0)
output_img1 = cv2.bitwise_and(img,img,mask=mask0)
lower_bound = np.array([100,50,50])
upper_bound = np.array([205,205,88])
mask1 = cv2.inRange(img_hsv, lower_bound, upper_bound)
output_img2 = cv2.bitwise_and(img,img,mask=mask1)
cv2.imshow("mask1",mask1)
final = cv2.bitwise_or(output_img1, output_img2)
cv2.imshow("rust",np.hstack([img,final]))[![enter image description here][1]][1]
我正在尝试使用颜色 space 执行图像分割。例如,乡村地区。我不确定如何 select cv2.inRange()
的边界。
img = cv2.imread(file)
img_hsv=cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
lower_bound = np.array([0,70,70])
upper_bound = np.array([20,200,150])
mask0 = cv2.inRange(img_hsv, lower_bound, upper_bound)
lower_bound = np.array([170,70,70])
upper_bound = np.array([180,200,150])
mask1 = cv2.inRange(img_hsv, lower_bound, upper_bound)
# add both masks
mask = mask0+mask1
output_img = cv2.bitwise_and(img,img,mask=mask)
如果您只想分割生锈的部分而不是其他部分,我尝试了一些代码如下。
import cv2
import numpy as np
img = cv2.imread("rust1.png",1)
img_hsv=cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
lower_bound = np.array([120, 80, 0],dtype="uint8")
upper_bound = np.array([255, 255, 80],dtype="uint8")
mask0 = cv2.inRange(img_hsv, lower_bound, upper_bound)
cv2.imshow("mask",mask0)
output_img1 = cv2.bitwise_and(img,img,mask=mask0)
lower_bound = np.array([100,50,50])
upper_bound = np.array([205,205,88])
mask1 = cv2.inRange(img_hsv, lower_bound, upper_bound)
output_img2 = cv2.bitwise_and(img,img,mask=mask1)
cv2.imshow("mask1",mask1)
final = cv2.bitwise_or(output_img1, output_img2)
cv2.imshow("rust",np.hstack([img,final]))[![enter image description here][1]][1]