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
CodePudding user response:
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)