在 PIL 中，我將一個矩形旋轉了一個角度并將其粘貼回背景影像。我想知道特定角落的新坐標是什么。
函式（舊坐標）=> 新坐標
我在檔案中讀到它提到旋轉中心默認是影像的中心。
這是我的代碼：
import PIL
from PIL import Image, ImageDraw
import os
background = Image.open('background.jpg')
rectangle = Image.open("rectangle.png")
my_angle = 30
rectangle_rotate = Image.Image.rotate(rectangle, angle=my_angle, resample=Image.BICUBIC, expand=True)
# box: 2-tuple giving the upper left corner
px = int(background.size[0] / 2)
py = int(background.size[1] / 2)
background.paste(im=rectangle_rotate,
box=(px, py),
mask=rectangle_rotate)
# The new position I'm getting is wrong, how come?????
pos_xNew = px * math.cos(math.radians(my_angle)) py * math.sin(math.radians(my_angle))
pos_yNew = -px * math.sin(math.radians(my_angle)) py * math.cos(math.radians(my_angle))
print('pos_xNew:', pos_xNew)
print('pos_yNew:', pos_yNew)
draw_img_pts = ImageDraw.Draw(background)
r = 10
# Drawing a simple small circle circle for visualization
draw_img_pts.ellipse((pos_xNew - r, pos_yNew - r, pos_xNew r, pos_yNew r), fill='red')
background.save('example_with_roatation.png')
我怎樣才能找到新的坐標值？我不斷得到錯誤的價值。
背景影像（輸入）：
矩形影像（輸入）：
我按預期獲得的輸出為零旋轉：
旋轉 30 度后得到的輸出：
uj5u.com熱心網友回復：
行內評論
import math
import os
import numpy as np # many operations are more concise in matrix form
import PIL
from PIL import Image, ImageDraw
def get_rotation_matrix(angle):
""" For background, https://en.wikipedia.org/wiki/Rotation_matrix
rotation is clockwise in traditional descartes, and counterclockwise,
if y goes down (as in picture coordinates)
"""
return np.array([
[np.cos(angle), -np.sin(angle)],
[np.sin(angle), np.cos(angle)]])
def rotate(points, pivot, angle):
""" Get coordinates of points rotated by a given angle counterclocwise
Args:
points (np.array): point coordinates shaped (n, 2)
pivot (np.array): [x, y] coordinates of rotation center
angle (float): counterclockwise rotation angle in radians
Returns:
np.array of new coordinates shaped (n, 2)
"""
relative_points = points - pivot
return relative_points.dot(get_rotation_matrix(angle)) pivot
background = Image.open('background.jpg')
rectangle = Image.open("rectangle.png")
my_angle_deg = 30
my_angle = math.radians(my_angle_deg)
rsize_x, rsize_y = rectangle.size
# to get shift introduced by rotation clipping we'll need to rotate all four corners
# starting from top-right corners, counter-clockwise
rectangle_corners = np.array([
[rsize_x, 0], # top-right
[0, 0], # top-left
[0, rsize_y], # bottom-left
[rsize_x, rsize_y] # bottom-right
])
# rectangle_corners now are:
# array([[262, 0],
# [ 0, 0],
# [ 0, 67],
# [262, 67]])
rotated_corners = rotate(rectangle_corners, rectangle_corners[0], my_angle)
# as a result of rotation, one of the corners might end up left from 0,
# e.g. if the rectangle is really tall and rotated 90 degrees right
# or, leftmost corner is no longer at 0, so part of the canvas is clipped
shift_introduced_by_rotation_clip = rotated_corners.min(axis=0)
rotated_shifted_corners = rotated_corners - shift_introduced_by_rotation_clip
# finally, demo
# this part is just copied from the question
rectangle_rotate = Image.Image.rotate(rectangle, angle=my_angle_deg, resample=Image.BICUBIC, expand=True)
# box: 2-tuple giving the upper left corner
px = int(background.size[0] / 2)
py = int(background.size[1] / 2)
background.paste(im=rectangle_rotate,
box=(px, py),
mask=rectangle_rotate)
# let's see if dots land right after these translations:
draw_img_pts = ImageDraw.Draw(background)
r = 10
for point in rotated_shifted_corners:
pos_xNew, pos_yNew = point [px, py]
draw_img_pts.ellipse((pos_xNew - r, pos_yNew - r, pos_xNew r, pos_yNew r), fill='red')
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