第二个参数:
Image.NEAREST :低质量
Image.BILINEAR:双线性
Image.BICUBIC :三次样条插值
Image.ANTIALIAS:高质量
from PIL import Image
'''
filein: 输入图片
fileout: 输出图片
width: 输出图片宽度
height:输出图片高度
type:输出图片类型(png, gif, jpeg...)
'''
def ResizeImage(filein, fileout, width, height, type):
img = Image.open(filein)
out = img.resize((width, height),Image.ANTIALIAS) #resize image with high-quality
out.save(fileout, type)
if __name__ == "__main__":
filein = r'0.jpg'
fileout = r'testout.png'
width = 6000
height = 6000
type = 'png'
ResizeImage(filein, fileout, width, height, type)
上面是单张图片尺寸的改变,针对大量数据集图片,如何批量操作,记录一下,为以后数据集预处理提供一点参考:
from PIL import Image
import os.path
import glob
def convertjpg(jpgfile,outdir,width=1280,height=720):
img=Image.open(jpgfile)
new_img=img.resize((width,height),Image.BILINEAR)
new_img.save(os.path.join(outdir,os.path.basename(jpgfile)))
for jpgfile in glob.glob("E:/test/picture/12/*.jpg"):
convertjpg(jpgfile,"E:/test/picture/111/")
返回12文件夹下所有的jpg路径:
glob.glob(“E:/test/picture/12/*.jpg”)
返回的是111文件夹下下个文件的所有路径:
glob.glob(“E:/test/picture/111//“)
转载地址:https://blog.csdn.net/xjp_xujiping/article/details/81607964