Masking ও Bitwise Operations

import cv2, numpy as np

img = cv2.imread("dhaka.jpg")
H, W = img.shape[:2]

mask = np.zeros((H, W), dtype=np.uint8)
cv2.circle(mask, (W//2, H//2), 150, 255, -1)   # white filled circle

result = cv2.bitwise_and(img, img, mask=mask)

import cv2, numpy as np

a = np.zeros((300,300), np.uint8); cv2.rectangle(a,(50,50),(250,250),255,-1)
b = np.zeros((300,300), np.uint8); cv2.circle(b,(200,200),100,255,-1)

and_ = cv2.bitwise_and(a, b)   # যে অংশ দুটোতেই
or_  = cv2.bitwise_or (a, b)   # যে অংশ যেকোনোটিতে
xor_ = cv2.bitwise_xor(a, b)   # দুটোতেই নয়, একটিতেই
not_ = cv2.bitwise_not(a)      # উল্টো

import cv2

bg   = cv2.imread("banner.jpg")
logo = cv2.imread("logo.png")           # সাদা background সহ
h, w = logo.shape[:2]

# ROI কাট
roi = bg[20:20+h, 20:20+w]

# Logo-র mask: gray → threshold
gray  = cv2.cvtColor(logo, cv2.COLOR_BGR2GRAY)
_, mask = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)
mask_inv = cv2.bitwise_not(mask)

bg_part   = cv2.bitwise_and(roi, roi, mask=mask_inv)   # background অক্ষুণ্ণ
logo_part = cv2.bitwise_and(logo, logo, mask=mask)     # শুধু logo

bg[20:20+h, 20:20+w] = cv2.add(bg_part, logo_part)
cv2.imwrite("branded.jpg", bg)

import cv2

a = cv2.imread("a.jpg"); b = cv2.imread("b.jpg")
b = cv2.resize(b, (a.shape[1], a.shape[0]))
blend = cv2.addWeighted(a, 0.6, b, 0.4, gamma=0)