answer_30.py

import cv2
import numpy as np
import matplotlib.pyplot as plt


# affine
def affine(img, a, b, c, d, tx, ty):
	H, W, C = _img.shape

	# temporary image
	img = np.zeros((H+2, W+2, C), dtype=np.float32)
	img[1:H+1, 1:W+1] = _img

	# get shape of new image
	H_new = np.round(H).astype(np.int)
	W_new = np.round(W).astype(np.int)
	out = np.zeros((H_new, W_new, C), dtype=np.float32)

	# get position of new image
	x_new = np.tile(np.arange(W_new), (H_new, 1))
	y_new = np.arange(H_new).repeat(W_new).reshape(H_new, -1)

	# get position of original image by affine
	adbc = a * d - b * c
	x = np.round((d * x_new  - b * y_new) / adbc).astype(np.int) - tx + 1
	y = np.round((-c * x_new + a * y_new) / adbc).astype(np.int) - ty + 1

	# adjust center by affine
	dcx = (x.max() + x.min()) // 2 - W // 2
	dcy = (y.max() + y.min()) // 2 - H // 2

	x -= dcx
	y -= dcy

	x = np.clip(x, 0, W + 1)
	y = np.clip(y, 0, H + 1)

	# assign pixcel
	out[y_new, x_new] = img[y, x]
	out = out.astype(np.uint8)

	return out

# Read image
_img = cv2.imread("imori.jpg").astype(np.float32)


# Affine
A = 30.
theta = - np.pi * A / 180.

out = affine(img, a=np.cos(theta), b=-np.sin(theta), c=np.sin(theta), d=np.cos(theta),
 tx=0, ty=0)


# Save result
cv2.imshow("result", out)
cv2.waitKey(0)
cv2.imwrite("out.jpg", out)