我们将介绍如何用PIL库实现一些简单的图像增强方法。

[!NOTE] 初始化配置

import numpy as np  
from PIL import Image, ImageOps, ImageEnhance  
import warnings

warnings.filterwarnings('ignore')
IMAGE_SIZE = 640

[!important] 辅助函数
主要用于控制增强幅度

def int_parameter(level, maxval):  
	return int(level * maxval / 10)  
  
  
def float_parameter(level, maxval):  
	return float(level) * maxval / 10.

def sample_level(n):  
    return np.random.uniform(low=0.1, high=n)

level用于控制增强方法的数值强度，maxval一般取值为4，level是一个从均匀分布中采样的数值，这样让每次增强都具有随机性。

[!example] 增强方法

色彩反转

def invert(pil_img, _):  
    return ImageOps.invert(pil_img)

镜像

def mirror(pil_img, _):  
    return ImageOps.mirror(pil_img)

均衡化

def equalize(pil_img, _):  
    return ImageOps.equalize(pil_img)

色彩分离

def posterize(pil_img, level):  
    level = int_parameter(sample_level(level), 4)  
    return ImageOps.posterize(pil_img, 4 - level)

旋转

def rotate(pil_img, level):  
    degrees = int_parameter(sample_level(level), 30)  
    if np.random.uniform() > 0.5:  
        degrees = -degrees  
    return pil_img.rotate(degrees, resample=Image.BILINEAR)

Solarize

def solarize(pil_img, level):  
    level = int_parameter(sample_level(level), 256)  
    return ImageOps.solarize(pil_img, 256 - level)

Shear_x

def shear_x(pil_img, level):  
    level = float_parameter(sample_level(level), 0.3)  
    if np.random.uniform() > 0.5:  
        level = -level  
    return pil_img.transform((IMAGE_SIZE, IMAGE_SIZE),  
                             Image.AFFINE, (1, level, 0, 0, 1, 0),  
                             resample=Image.BILINEAR)

Shear_y

def shear_y(pil_img, level):  
    level = float_parameter(sample_level(level), 0.3)  
    if np.random.uniform() > 0.5:  
        level = -level  
    return pil_img.transform((IMAGE_SIZE, IMAGE_SIZE),  
                             Image.AFFINE, (1, 0, 0, level, 1, 0),  
                             resample=Image.BILINEAR)

Translate_x

def translate_x(pil_img, level):  
    level = int_parameter(sample_level(level), IMAGE_SIZE / 3)  
    if np.random.random() > 0.5:  
        level = -level  
    return pil_img.transform((IMAGE_SIZE, IMAGE_SIZE),  
                             Image.AFFINE, (1, 0, level, 0, 1, 0),  
                             resample=Image.BILINEAR)  

Translate_y

def translate_y(pil_img, level):  
    level = int_parameter(sample_level(level), IMAGE_SIZE / 3)  
    if np.random.random() > 0.5:  
        level = -level  
    return pil_img.transform((IMAGE_SIZE, IMAGE_SIZE),  
                             Image.AFFINE, (1, 0, 0, 0, 1, level),  
                             resample=Image.BILINEAR)  

Color

def color(pil_img, level):  
    level = float_parameter(sample_level(level), 1.8) + 0.1  
    return ImageEnhance.Color(pil_img).enhance(level)  

Contrast

def contrast(pil_img, level):  
    level = float_parameter(sample_level(level), 1.8) + 0.1  
    return ImageEnhance.Contrast(pil_img).enhance(level)  

AutoContrast

def autocontrast(pil_img, level):  
    level = float_parameter(sample_level(level), 10)  
    return ImageOps.autocontrast(pil_img, 10 - level)  

Brightness

def brightness(pil_img, level):  
    level = float_parameter(sample_level(level), 1.8) + 0.1  
    return ImageEnhance.Brightness(pil_img).enhance(level)  

Sharpness

def sharpness(pil_img, level):  
    level = float_parameter(sample_level(level), 1.8) + 0.1  
    return ImageEnhance.Sharpness(pil_img).enhance(level)

[!success] 使用案例

对于这样一张原图：

augmentations_all = {  
    "autocontrast":autocontrast,  
    "equalize":equalize,  
    "posterize":posterize,  
    "rotate":rotate,  
    "solarize":solarize,  
    "shear_x":shear_x,  
    "shear_y":shear_y,  
    "translate_x":translate_x,  
    "translate_y":translate_y,  
    "color":color,  
    "contrast":contrast,  
    "brightness":brightness,  
    "sharpness":sharpness,  
    "mirror":mirror,  
    "invert":invert  
    }  
  
import matplotlib.pyplot as plt  
  
img=Image.open(r"C:\Users\Administrator\Downloads\result1.5\result\original_resized\class0\0.jpg")  

def draw(plt,idx,img,title):  
    plt.subplot(int("24"+str(idx)))  
    plt.imshow(img)  
    plt.xticks([])  
    plt.yticks([])  
    plt.title(title)  
  
plt.figure(figsize=(20,16))  
for idx,(k,v) in enumerate(augmentations_all.items()):  
    draw(plt,(idx)%8+1,v(img.copy(),1),k)  
    if idx!=0 and idx % 7 == 0:  
        plt.show()  
        plt.figure(figsize=(20,16))