# 對(duì)圖像進(jìn)行旋轉(zhuǎn)
# USAGE
# python opencv_rotate.py

# 導(dǎo)入必要的包
import argparse

import cv2
import imutils

# 構(gòu)建命令行參數(shù)及解析
# --image 圖像路徑
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", type=str, default="zly1.jpg",
                help="path to the input image")
args = vars(ap.parse_args())

# 從磁盤(pán)加載圖像并展示
image = cv2.imread(args["image"])
image = imutils.resize(image, width=300)
cv2.imshow("Original", image)

# 獲取圖像的維度，并計(jì)算中心
(h, w) = image.shape[:2]
(cX, cY) = (w // 2, h // 2)

# 逆時(shí)針以圖像中心旋轉(zhuǎn)45度
# - (cX,cY): 旋轉(zhuǎn)的中心點(diǎn)坐標(biāo)
# - 45: 旋轉(zhuǎn)的度數(shù)，正度數(shù)表示逆時(shí)針旋轉(zhuǎn)，而負(fù)度數(shù)表示順時(shí)針旋轉(zhuǎn)。
# - 1.0：旋轉(zhuǎn)后圖像的大小，1.0原圖，2.0變成原來(lái)的2倍，0.5變成原來(lái)的0.5倍
# OpenCV不會(huì)自動(dòng)為整個(gè)旋轉(zhuǎn)圖像分配空間，以適應(yīng)幀。旋轉(zhuǎn)完可能有部分丟失。如果您希望在旋轉(zhuǎn)后使整個(gè)圖像適合視圖，則需要進(jìn)行優(yōu)化，使用imutils.rotate_bound.
M = cv2.getRotationMatrix2D((cX, cY), 45, 1.0)
rotated = cv2.warpAffine(image, M, (w, h))
cv2.imshow("Rotated by 45 Degrees", rotated)

# 逆時(shí)針以圖像中心旋轉(zhuǎn)-90度圖像
M = cv2.getRotationMatrix2D((cX, cY), -90, 1.0)
rotated = cv2.warpAffine(image, M, (w, h))
cv2.imshow("Rotated by -90 Degrees", rotated)

# 以任意點(diǎn)作為中心旋轉(zhuǎn)圖像
M = cv2.getRotationMatrix2D((10, 10), 45, 1.0)
rotated = cv2.warpAffine(image, M, (w, h))
cv2.imshow("Rotated by Arbitrary Point", rotated)

# 使用imutils.rotata 一行代碼實(shí)現(xiàn)旋轉(zhuǎn)
rotated = imutils.rotate(image, 180)
cv2.imshow("Rotated by 180 Degrees", rotated)

# 順時(shí)針旋轉(zhuǎn)33度，并保證圖像旋轉(zhuǎn)后完整~,確保整個(gè)圖都在視野范圍
rotated = imutils.rotate_bound(image, -33)
cv2.imshow("Rotated Without Cropping", rotated)
cv2.waitKey(0)

cv2.destroyAllWindows()