问题
We can define the range of red color in HSV as below. I want to detect that whether a certain pixel is red or not? How can I do that in Python? I spend whole day, but unable to find solution. Please resolve my problem. I'm very new to Python. Code that I'm using is:
img=cv2.imread("img.png")
img_hsv=cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# lower mask (0-10)
lower_red = np.array([0,50,50])
upper_red = np.array([10,255,255])
mask0 = cv2.inRange(img_hsv, lower_red, upper_red)
# upper mask (170-180)
lower_red = np.array([170,50,50])
upper_red = np.array([180,255,255])
mask1 = cv2.inRange(img_hsv, lower_red, upper_red)
image_height,image_width,_=img.shape
for i in range(image_height):
for j in range(image_width):
if img_hsv[i][j][1]>=lower_red and img_hsv[i][j][1]<=upper_red:
print("Found red")
回答1:
You are almost right. You can merge the masks of lower RED and higher RED together to a single mask.
For this ColorChecker.png:
My Steps to find the RED:
Read the image and convert to
hsv.I choose the red ranges (
lower 0~5, upper 175~180) using this colormap:
- Then merge the masks, you can judge whether the pixel is red or not by the mask. Or "crop" the region(s) for visualization:
#!/usr/bin/python3
# 2018.07.08 10:39:15 CST
# 2018.07.08 11:09:44 CST
import cv2
import numpy as np
## Read and merge
img = cv2.imread("ColorChecker.png")
img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
## Gen lower mask (0-5) and upper mask (175-180) of RED
mask1 = cv2.inRange(img_hsv, (0,50,20), (5,255,255))
mask2 = cv2.inRange(img_hsv, (175,50,20), (180,255,255))
## Merge the mask and crop the red regions
mask = cv2.bitwise_or(mask1, mask2 )
croped = cv2.bitwise_and(img, img, mask=mask)
## Display
cv2.imshow("mask", mask)
cv2.imshow("croped", croped)
cv2.waitKey()
Choosing the correct upper and lower HSV boundaries for color detection with`cv::inRange` (OpenCV)
How to detect two different colors using `cv2.inRange` in Python-OpenCV?
来源：https://stackoverflow.com/questions/51225657/detect-whether-a-pixel-is-red-or-not