July 2019
Intermediate to advanced
365 pages
8h 13m
Chinese
Content preview from Python机器学习手册：从数据预处理到深度学习
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132
｜
第
8
章
图像处理
讨论
调整图像大小是图像预处理中常见的任务，原因有两点。首先，原始图像的形状和大小
各异，但是被用作特征的图像必须有相同的大小（像素数）。然而图像大小（像素数）
的标准化也会带来一些信息上的损失。图像是包含信息的矩阵，当减小图像的像素时，
矩阵的尺寸也会缩小，而其中包含的信息也随之减少。其次，机器学习算法可能需要成
百上千张图像，甚至更多。如果这些图像非常大，就会占用大量内存，通过调整图像的
大小（像素数）可以大大减少内存使用量。在机器学习中常见的图像规格有 ：
32
×
32
、
64
×
64
、
96
×
96
和
256
×
256
。
8.4
裁剪图像
问题描述
通过裁剪图像边缘来更改其尺寸。
解决方案
图像被编码为二维
NumPy
数组，因此通过对数组切片可以方便地裁剪图像 ：
#
加载库
import cv2
import numpy as np
from matplotlib import pyplot as plt
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