hsv-filter.py

img_path = 'image/G2/6.jpg'# Detect and remove unrelevant regions (batch). 
import cv2 
import numpy as np
import pandas as pd 

# Parameters. 
group_lst = ['G1', 'G2', 'G3', 'G4']
group_dct = {'G1': 19, 'G2': 13, 'G3': 15, 'G4': 16}
kernel = np.ones((5,5), np.uint8)
img_path = 'image/G2/6.jpg'
img = cv2.imread(img_path)
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# Lower bound and upper bound for Green color.  

for i in range(0, 255, 10):
    lower_bound = np.array([36, i, 25])     
    upper_bound = np.array([86, 255, 255])


#     Find the colors within the boundaries. 
    mask = cv2.inRange(hsv, lower_bound, upper_bound)

# # Remove unnecessary noise from mask
# mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
# mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)

# # Segment only the detected region
    segmented_img = cv2.bitwise_and(img, img, mask=mask)

# # Save the segmented image. 
# img_path_to_store = 'image/p' + group + '/' + str(j) + '.jpg'
    cv2.imwrite('hsv_{}.jpg'.format(str(i)), segmented_img)