对图像pad+resize

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import cv2
import numpy as np

def pad_resize_image(image, width, height):
# 获取原始图像的尺寸
original_height, original_width = image.shape[:2]

# 计算缩放比例
scale = min(width / original_width, height / original_height)

# 计算缩放后的新尺寸
new_width = int(original_width * scale)
new_height = int(original_height * scale)

# 缩放图像
resized_image = cv2.resize(image, (new_width, new_height))

# 创建新的画布，并将缩放后的图像放置在其中心
if len(resized_image.shape) == 3:
padded_image = np.zeros((height, width, resized_image.shape[2]), dtype=np.uint8)
else:
padded_image = np.zeros((height, width), dtype=np.uint8)
start_x = (width - new_width) // 2
start_y = (height - new_height) // 2
padded_image[start_y:start_y + new_height, start_x:start_x + new_width] = resized_image

# 计算从目标坐标系到原始坐标系的变换矩阵
scale_matrix = np.eye(3)
scale_matrix[0, 0] = scale
scale_matrix[1, 1] = scale
translation_matrix = np.eye(3)
translation_matrix[0, 2] = start_x
translation_matrix[1, 2] = start_y
transformation_matrix = translation_matrix.dot(scale_matrix)

return padded_image, transformation_matrix

if __name__ == "__main__":
image = cv2.imread("test.png")
new_image, _ = pad_resize_image(image, 256, 256)
cv2.imshow("image", new_image)
cv2.waitKey(0)
pass