下面的代码可以实现13种数据增强，出自 PIL库的 Image和 ImageEnhance,后续如果想增加扩充倍数，可直接添加。

目录

1.ImageEnhance库：

2.Image库：

二、注意的问题：

三、代码展示：

一、相关的库主要包括：

1.ImageEnhance库：

ImageEnhance.enhance(factor) 对选择属性的数值增强factor倍 
ImageEnhance.Color(im) 调整图像的颜色平衡 
ImageEnhance.Contrast(im) 调整图像的对比度 
ImageEnhance.Brightness(im) 调整图像的亮度 
ImageEnhance.Sharpness(im) 调整图像的锐度 

2.Image库：

image.rotate()方法进行旋转

image.transpose()方法进行翻转

二、注意的问题：

将图片的原来文件夹和增强后的文件夹填写正确。

三、代码展示：

###
#本代码共采用了13种数据增强，如采用其他数据增强方式，可以参考本代码，随意替换。
#imageDir 为原数据集的存放位置
#saveDir  为数据增强后数据的存放位置
###def flip(root_path,img_name):   #翻转图像img = Image.open(os.path.join(root_path, img_name))filp_img = img.transpose(Image.FLIP_LEFT_RIGHT)# filp_img.save(os.path.join(root_path,img_name.split('.')[0] + '_flip.jpg'))return filp_imgdef rotation(root_path, img_name):img = Image.open(os.path.join(root_path, img_name))rotation_img = img.rotate(20) #旋转角度20# rotation_img.save(os.path.join(root_path,img_name.split('.')[0] + '_rotation.jpg'))return rotation_imgdef rotation2(root_path, img_name):img = Image.open(os.path.join(root_path, img_name))rotation_img = img.rotate(10) #旋转角度10# rotation_img.save(os.path.join(root_path,img_name.split('.')[0] + '_rotation.jpg'))return rotation_imgdef rotation3(root_path, img_name):img = Image.open(os.path.join(root_path, img_name))rotation_img = img.rotate(90) #旋转角度90# rotation_img.save(os.path.join(root_path,img_name.split('.')[0] + '_rotation.jpg'))return rotation_imgdef rotation4(root_path, img_name):img = Image.open(os.path.join(root_path, img_name))rotation_img = img.rotate(180) #旋转角度180# rotation_img.save(os.path.join(root_path,img_name.split('.')[0] + '_rotation.jpg'))return rotation_imgdef rotation5(root_path, img_name):img = Image.open(os.path.join(root_path, img_name))rotation_img = img.rotate(45) #旋转角度45# rotation_img.save(os.path.join(root_path,img_name.split('.')[0] + '_rotation.jpg'))return rotation_imgdef randomColor(root_path, img_name): #随机颜色"""对图像进行颜色抖动:param image: PIL的图像image:return: 有颜色色差的图像image"""image = Image.open(os.path.join(root_path, img_name))random_factor = np.random.randint(0, 31) / 10.  # 随机因子color_image = ImageEnhance.Color(image).enhance(random_factor)  # 调整图像的饱和度random_factor = np.random.randint(10, 21) / 10.  # 随机因子brightness_image = ImageEnhance.Brightness(color_image).enhance(random_factor)  # 调整图像的亮度random_factor = np.random.randint(10, 21) / 10.  # 随机因子contrast_image = ImageEnhance.Contrast(brightness_image).enhance(random_factor)  # 调整图像对比度random_factor = np.random.randint(0, 31) / 10.  # 随机因子return ImageEnhance.Sharpness(contrast_image).enhance(random_factor)  # 调整图像锐度def contrastEnhancement(root_path, img_name):  # 对比度增强image = Image.open(os.path.join(root_path, img_name))enh_con = ImageEnhance.Contrast(image)contrast = 1.5image_contrasted = enh_con.enhance(contrast)return image_contrasteddef contrastEnhancement2(root_path, img_name):  # 对比度增强2image = Image.open(os.path.join(root_path, img_name))enh_con = ImageEnhance.Contrast(image)contrast = 1.75image_contrasted = enh_con.enhance(contrast)return image_contrasteddef brightnessEnhancement(root_path,img_name):#亮度增强image = Image.open(os.path.join(root_path, img_name))enh_bri = ImageEnhance.Brightness(image)brightness = 1.5image_brightened = enh_bri.enhance(brightness)return image_brighteneddef colorEnhancement(root_path,img_name):#颜色增强image = Image.open(os.path.join(root_path, img_name))enh_col = ImageEnhance.Color(image)color = 1.5image_colored = enh_col.enhance(color)return image_coloreddef colorEnhancement2(root_path,img_name):#颜色增强->黑白图image = Image.open(os.path.join(root_path, img_name))enh_col = ImageEnhance.Color(image)color = 2image_colored = enh_col.enhance(color)return image_colored#锐度增强
def colorSharpness(root_path,img_name):image = Image.open(os.path.join(root_path, img_name))enh_col = ImageEnhance.Sharpness(image)sharpness = 3.0image_colored = enh_col.enhance(sharpness)return image_coloredfrom PIL import Image
from PIL import ImageEnhance
import os
import cv2
import numpy as np#D:\images_background\22 (2)
imageDir="D:/学习/人工智能/孪生网络/数据集/原数据集 - 轮胎痕迹/trace.6L"     #要改变的图片的路径文件夹
saveDir="D:/学习/人工智能/孪生网络/数据集/原数据集 - 轮胎痕迹/trace.6L"   #要保存的图片的路径文件夹
#D:\trace_images01\.6LD:\学习\人工智能\孪生网络\数据集\原数据集 - 轮胎花纹\t (2)
for name in os.listdir(imageDir):saveName= name[:-4]+"bright.jpg"saveImage=brightnessEnhancement(imageDir,name)#2.亮度增强saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"flip.jpg"saveImage=flip(imageDir,name)#3.翻转图像saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"rotation.jpg"saveImage=rotation(imageDir,name)#4.旋转角度20度saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"randmcolor.jpg"saveImage=randomColor(imageDir,name)#5.随机颜色saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"color.jpg"saveImage=colorEnhancement(imageDir,name)#6.颜色增强saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"contrast.jpg"saveImage=contrastEnhancement(imageDir,name) #7.对比度增强saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"rotation3.jpg"saveImage=rotation3(imageDir,name)#8.旋转角度30度saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"rotation4.jpg"saveImage=rotation4(imageDir,name)#9.旋转角度45度saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"contrast2.jpg"saveImage=contrastEnhancement2(imageDir,name) #10.对比度增强saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"colorEnhancement2.jpg"saveImage=colorEnhancement2(imageDir,name) #11.黑白图saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"colorSharpness.jpg"saveImage=colorSharpness(imageDir,name) #12.增强因子为2.0表示锐化图像。值越大图像边界越多越清晰。saveImage.save(os.path.join(saveDir,saveName))saveName= name[:-4]+"rotate5.jpg"saveImage=rotation5(imageDir,name) #13.对比度增强saveImage.save(os.path.join(saveDir,saveName))