opencv-批量调整图片的曝光率

#--coding:utf-8--
import cv2
import numpy as np
import os
 
def gamma_trans(img,gamma):#gamma函数处理
    gamma_table=[np.power(x/255.0,gamma)*255.0 for x in range(256)]#建立映射表
    gamma_table=np.round(np.array(gamma_table)).astype(np.uint8)#颜色值为整数
    return cv2.LUT(img,gamma_table)#图片颜色查表。另外可以根据光强（颜色）均匀化原则设计自适应算法。
def nothing(x):
    pass
 
cv2.namedWindow("demo",0)#将显示窗口的大小适应于显示器的分辨率
cv2.createTrackbar('Value of Gamma','demo',100,1000,nothing)#使用滑动条动态调节参数gamma
 
data_base_dir="C:\\Users\\HUANG\\Desktop\\pict"#输入文件夹的路径
outfile_dir="C:\\Users\\HUANG\\Desktop\\pictout"#输出文件夹的路径
processed_number=0#统计处理图片的数量
print "press enter to make sure your operation and process the next picture"
 
for file in os.listdir(data_base_dir):#遍历目标文件夹图片
    read_img_name=data_base_dir+'//'+file.strip()#取图片完整路径
    image=cv2.imread(read_img_name)#读入图片
 
    while(1):
        value_of_gamma=cv2.getTrackbarPos('Value of Gamma','demo')#gamma取值
        value_of_gamma=value_of_gamma*0.01#压缩gamma范围，以进行精细调整
        image_gamma_correct=gamma_trans(image,value_of_gamma)#2.5为gamma函数的指数值，大于1曝光度下降，大于0小于1曝光度增强
        cv2.imshow("demo",image_gamma_correct)
        k=cv2.waitKey(1)
        if k==13:#按回车键确认处理、保存图片到输出文件夹和读取下一张图片
            processed_number+=1
            out_img_name=outfile_dir+'//'+file.strip()
            cv2.imwrite(out_img_name,image_gamma_correct)
            print "The number of photos which were processed is ",processed_number
            break