opencv-python：如何识别图像中的粉红色木材？

Question

How can I recognize pink wood in an image? I used this code but I did not find any pink small wood in the image.

I expect that if I give such an image as input, the output of pink wood will be recognized.

Other than this method, do you have a suggestion for recognizing pink wood????

input:

output expected (Manually marked)

Code:

import numpy as np


import cv2
from cv2 import *
im = cv2.imread(imagePath)

im = cv2.bilateralFilter(im,9,75,75)
im = cv2.fastNlMeansDenoisingColored(im,None,10,10,7,21)
hsv_img = cv2.cvtColor(im, cv2.COLOR_BGR2HSV)   # HSV image


COLOR_MIN = np.array([233, 88, 233],np.uint8)       # HSV color code lower and upper bounds
COLOR_MAX = np.array([241, 82, 240],np.uint8)       # color pink 

frame_threshed = cv2.inRange(hsv_img, COLOR_MIN, COLOR_MAX)     # Thresholding image
imgray = frame_threshed
ret,thresh = cv2.threshold(frame_threshed,127,255,0)
contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
print(contours)
for cnt in contours:
    x,y,w,h = cv2.boundingRect(cnt)
    print(x,y)
    cv2.rectangle(im,(x,y),(x+w,y+h),(0,255,0),2)
cv2.imwrite("extracted.jpg", im)

output Code:

print(contours)
()

The problem is that pink wood is not recognized

Answer 1

Change your HSV lower and upper bounds as below:

COLOR_MIN = np.array([130,0,220],np.uint8)    
COLOR_MAX = np.array([170,255,255],np.uint8)  

Answer 2

@nishani-kasineshan Thank you for your answer. That was the answer. One question, why did you choose this color?

[170,255,255]