【数据增强】亮度/对比度增强

一、效果图

二、代码

import cv2
import math
import numpy as np
import os
import glob
import json
import shutil
import xml.etree.ElementTree as ET
from xml.etree.ElementTree import ElementTree, Element

def getColorImg(alpha,beta,img_path,img_write_path):
    img = cv2.imread(img_path)
    colored_img = np.uint8(np.clip((alpha * img + beta), 0, 255))
    cv2.imwrite(img_write_path,colored_img)

def getColorAnno(anno_path,anno_write_path):
    tree = ET.parse(anno_path)
    tree.write(anno_write_path)  # 保存修改后的XML文件

def color(alpha,beta,img_dir,anno_dir,img_write_dir,anno_write_dir):
    if not os.path.exists(img_write_dir):
        os.makedirs(img_write_dir)

    if not os.path.exists(anno_write_dir):
        os.makedirs(anno_write_dir)
    img_names=os.listdir(img_dir)
    for img_name in img_names:
        img_path=os.path.join(img_dir,img_name)
        img_write_path=os.path.join(img_write_dir,img_name[:-4]+'color'+str(int(alpha*10))+'.jpg')
        #
        anno_path=os.path.join(anno_dir,img_name[:-4]+'.xml')
        anno_write_path = os.path.join(anno_write_dir, img_name[:-4]+'color'+str(int(alpha*10))+'.xml')
        #
        getColorImg(alpha,beta,img_path,img_write_path)
        getColorAnno(anno_path,anno_write_path)

alphas = [0.3, 0.5, 1.2]
beta = 10
# 原始图片地址
img_dir = r'J:\hive-master\datasets\1\images'
# 原始标签地址
anno_dir = r'J:\hive-master\datasets\1\annotations'
# 对比增强后图片地址
img_write_dir = r'J:\hive-master\datasets\1\color\color_imgs'
# 对比增强后标签地址
anno_write_dir = r'J:\hive-master\datasets\1\color\color_annotations'
for alpha in alphas:
    color(alpha, beta, img_dir, anno_dir, img_write_dir, anno_write_dir)