Color Masking

import cv2
import numpy as np

image = cv2.imread("photo.jpg")
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

# cv2.inRange() creates a binary mask:
# Pixels WITHIN the range → 255 (white)
# Pixels OUTSIDE the range → 0 (black)

# Detect blue colour
lower_blue = np.array([100, 100, 100])
upper_blue = np.array([130, 255, 255])
blue_mask = cv2.inRange(hsv, lower_blue, upper_blue)

# Clean the mask: remove noise with morphological operations
kernel = np.ones((5, 5), np.uint8)
blue_mask = cv2.morphologyEx(blue_mask, cv2.MORPH_OPEN, kernel)   # Remove small noise
blue_mask = cv2.morphologyEx(blue_mask, cv2.MORPH_CLOSE, kernel)  # Fill small holes

# Apply mask to extract only blue pixels
blue_only = cv2.bitwise_and(image, image, mask=blue_mask)

# Create inverted mask (everything EXCEPT blue)
inverse_mask = cv2.bitwise_not(blue_mask)
non_blue = cv2.bitwise_and(image, image, mask=inverse_mask)

print(f"Mask shape: {blue_mask.shape}")
print(f"Blue pixels: {cv2.countNonZero(blue_mask):,}")

cv2.imwrite("blue_only.jpg", blue_only)
cv2.imwrite("non_blue.jpg", non_blue)