对图像pad+resize

Nov 7, 202394

AI-generated summary

This code is for resizing and padding an image using the OpenCV library in Python. It calculates the scale ratio based on the desired width and height, resizes the image accordingly, and then creates a new canvas to place the resized image in the center. It also calculates the transformation matrix for converting coordinates between the original and target coordinate systems. The code then reads an image file, applies the resizing and padding function, and displays the result.

code#

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