Resize, Crop, Rotate

import cv2

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

# পদ্ধতি ১ — fixed size
out1 = cv2.resize(img, (640, 480), interpolation=cv2.INTER_LINEAR)

# পদ্ধতি ২ — scale factor
out2 = cv2.resize(img, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_AREA)

# পদ্ধতি ৩ — aspect ratio বজায় রেখে width fix
new_w = 800
new_h = int(H * new_w / W)
out3 = cv2.resize(img, (new_w, new_h))

import cv2

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

# মাঝখানের 300x300
cy, cx = H // 2, W // 2
roi = img[cy-150:cy+150, cx-150:cx+150]

cv2.imwrite("face_crop.jpg", roi)

import cv2

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

# Quick — multiples of 90°
r90  = cv2.rotate(img, cv2.ROTATE_90_CLOCKWISE)
r180 = cv2.rotate(img, cv2.ROTATE_180)

# Arbitrary angle via affine transform
angle = 30
M = cv2.getRotationMatrix2D((W/2, H/2), angle, scale=1.0)
rotated = cv2.warpAffine(img, M, (W, H),
                         borderValue=(0, 0, 0))

import cv2, numpy as np

img = cv2.imread("dhaka.jpg")

flip_h = cv2.flip(img, 1)   # mirror (data augmentation-এ কমন)
flip_v = cv2.flip(img, 0)

# Translate — ৫০ px ডানে, ৩০ px নিচে
M = np.float32([[1, 0, 50], [0, 1, 30]])
shifted = cv2.warpAffine(img, M, (img.shape[1], img.shape[0]))