transforms.Pad边界填充

transforms.Pad边界填充

@Data 2022/12/9
代码：

import os
import torch
import torchvision.transforms as transform
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
 
if __name__ == '__main__':
    imgPath = 'a.jpg'
 
    img = Image.open(imgPath)
    # PIL库读取图片的size 形式是 w, h
    w, h = img.size
    # 计算需要补充的padding像素数
    padh = 600 - h
    padw = 600 - w
    # left-right, top\bottom,
    pad_params = (padw//2, padh//2)
    # Pad函数可以传入1，2，4个参数，1：四周填充，2：左右、上下填充，4：左上右下填充
    # fill参数只有在mode为constant时才有效
    const_pad = transform.Pad(pad_params, fill=(125, 125, 256), padding_mode='constant')
    # edge：用图像边缘像素点进行填充
    edge_pad = transform.Pad(pad_params, padding_mode='edge')
    # reflect：利用反射的方式进行填充
    reflect_pad = transform.Pad(pad_params, padding_mode='reflect')
    # symmetric：对称填充
    symmetric_pad = transform.Pad(pad_params, padding_mode='symmetric')
 
    img1 = const_pad(img)
    img2 = edge_pad(img)
    img3 = reflect_pad(img)
    img4 = symmetric_pad(img)
 
    print(f'size:\nimg {img.size}, const {img1.size}, edge {img2.size}, reflect {img3.size}, symmetric {img4.size}')
    axs = plt.figure().subplots(1, 5)
    axs[0].imshow(img);axs[0].set_title('src');axs[0].axis('off')
    axs[1].imshow(img1);axs[1].set_title('constant');axs[1].axis('off')
    axs[2].imshow(img2);axs[2].set_title('edge');axs[2].axis('off')
    axs[3].imshow(img3);axs[3].set_title('reflect');axs[3].axis('off')
    axs[4].imshow(img4);axs[4].set_title('symmetric');axs[4].axis('off')
    plt.show()

输出：

>>size:
img (334, 500), const (600, 600), edge (600, 600), reflect (600, 600), symmetric (600, 600)

在这里插入图片描述
参考链接