深度学习训练样本扩增同时修改标签名称

之前的是在不同文件夹，自己手动修改

# -*- coding:utf-8 -*-
import sys
# sys.path.append('E:\\Anaconda\\libs')
import os  # os：操作系统相关的信息模块
import shutil
from os.path import join
import cv2
import numpy as np
import random  # 导入随机函数

os.environ["CUDA_VISIBLE_DEVICES"] = "0"
# 存放原始图片地址
data_base_dir = '../switch/images/train2017'
label_path = '../switch/labels/train2017'
file_dir = '../switch/images/train2017'
dest_dir = "./VINS"
# dest_dir1 = r"E:\VINS\train01"
# dest_dir2 = r"E:\VINS\train02"
# dest_dir3 = r"E:\VINS\train03"
# dest_dir4 = r"E:\VINS\train04"
# dest_dir5 = r"E:\VINS\train05"
# dest_dir6 = r"E:\VINS\train06"
# dest_dir7 = r"E:\VINS\train07"
# dest_dir8 = r"E:\VINS\train08"
# dest_dir9 = r"E:\VINS\train09"
# dest_dir10 = r"E:\VINS\train10"
# dest_dir11 = r"E:\VINS\train11"
# dest_dir12 = r"E:\VINS\train12"

if not os.path.exists(dest_dir): #判断所在目录下是否有该文件名的文件夹
    os.mkdir(dest_dir)

file_list = []  # 建立列表，用于保存图片信息


# 读取图片文件，并将图片地址、图片名和标签写到txt文件中

def imgBrightness(img1, c, b):
    rows, cols, channels = img1.shape
    blank = np.zeros([rows, cols, channels], img1.dtype)
    rst = cv2.addWeighted(img1, c, blank, 1 - c, b)
    return rst


def noise(img, snr):
    h = img.shape[0]
    w = img.shape[1]
    img1 = img.copy()
    sp = h * w  # 计算图像像素点个数
    NP = int(sp * (1 - snr))  # 计算图像椒盐噪声点个数
    for i in range(NP):
        randx = np.random.randint(1, h - 1)  # 生成一个 1 至 h-1 之间的随机整数
        randy = np.random.randint(1, w - 1)  # 生成一个 1 至 w-1 之间的随机整数
        if np.random.random() <= 0.5:  # np.random.random()生成一个 0 至 1 之间的浮点数
            img1[randx, randy] = 0
        else:
            img1[randx, randy] = 255
    return img1


for file in os.listdir(data_base_dir):  # file为current_dir当前目录下图片名
    if file.endswith(".jpg"):  # 如果file以jpg结尾
        for item in range(13):
            # print(file)
            imageName = "VIN" + str(item) + file[:-4] + '.jpg'
            labelName = "VIN" + str(item) + file[:-4] + '.txt'

            if item == 0:
                # 原图不复制了
                scr_dir = join(file_dir, file)
                shutil.copyfile(scr_dir, os.path.join(dest_dir, imageName))
                # shutil.copyfile(scr_dir, det)

            # 增强图片
            if item == 1:
                img = cv2.imread(scr_dir, cv2.IMREAD_GRAYSCALE)

                gaussianBlur = cv2.GaussianBlur(img, (3, 3), 3)
                blur = cv2.blur(gaussianBlur, (5, 5))       # 模糊图片

                # cv2.imshow("img1", blur)
                # cv2.waitKey()
                det = join(dest_dir, imageName)
                cv2.imwrite(det, blur)

            if item == 2:
                img = cv2.imread(scr_dir)
                boxblur = cv2.boxFilter(img, -1, (9, 9))     # 模糊图片*2
                # cv2.imshow("img2", boxblur)
                # cv2.waitKey()
                det = join(dest_dir, imageName)
                cv2.imwrite(det, boxblur)

            # 加椒盐噪声小
            if item == 3:
                img = cv2.imread(scr_dir, cv2.IMREAD_GRAYSCALE)
                noiseimage = noise(img, 0.98)  # 将信噪比设定为0.6
                # cv2.imshow("img3", noiseimage)
                # cv2.waitKey()
                det = join(dest_dir, imageName)
                cv2.imwrite(det, noiseimage)

            # # 加椒盐噪声中
            # if item == 4:
            #     img = cv2.imread(scr_dir)
            #     noiseimage4 = noise(img, 0.90)  # 将信噪比设定为0.6
            #     # cv2.imshow("img4", noiseimage4)
            #     # cv2.waitKey()
            #     det = join(dest_dir, imageName)
            #     cv2.imwrite(det, noiseimage4)
            #
            # # 加椒盐噪声多
            # if item == 5:
            #     img = cv2.imread(scr_dir, cv2.IMREAD_GRAYSCALE)
            #     noiseimage5 = noise(img, 0.86)  # 将信噪比设定为0.6
            #     cv2.imshow("img5", noiseimage5)
            #     cv2.waitKey()
            #     det = join(dest_dir, imageName)
            #     cv2.imwrite(det, noiseimage5)

            # 加椒盐噪声加高斯模糊
            if item == 6:
                img = cv2.imread(scr_dir)
                noiseimage = noise(img, 0.98)  # 将信噪比设定为0.6
                gaussianBlur6 = cv2.GaussianBlur(noiseimage, (3, 3), 3)

                # cv2.imshow("img3", gaussianBlur6)
                # cv2.waitKey()
                det = join(dest_dir, imageName)
                cv2.imwrite(det, gaussianBlur6)

            # 加椒盐噪声加高斯模糊
            if item == 7:
                img = cv2.imread(scr_dir, cv2.IMREAD_GRAYSCALE)
                noiseimage = noise(img, 0.98)  # 将信噪比设定为0.6
                boxblur7 = cv2.boxFilter(noiseimage, -1, (9, 9))

                # cv2.imshow("img7", boxblur7)
                # cv2.waitKey()
                det = join(dest_dir, imageName)
                cv2.imwrite(det, boxblur7)

            # 高斯模糊加椒盐噪声
            if item == 8:
                img = cv2.imread(scr_dir)

                gaussianBlur = cv2.GaussianBlur(img, (5, 5), 3)
                noiseimage8 = noise(gaussianBlur, 0.98)  # 将信噪比设定为0.6

                # cv2.imshow("img8", noiseimage8)
                # cv2.waitKey()
                det = join(dest_dir, imageName)
                cv2.imwrite(det, noiseimage8)

            # # 双边模糊加椒盐噪声
            # if item == 9:
            #     img = cv2.imread(scr_dir, cv2.IMREAD_GRAYSCALE)
            #
            #     bilBlur = cv2.bilateralFilter(img, 1, 25, 10)
            #     noiseimage9 = noise(bilBlur, 0.92)  # 将信噪比设定为0.6
            #     cv2.imshow("img9", noiseimage9)
            #     cv2.waitKey()
            #     det = join(dest_dir, imageName)
            #     cv2.imwrite(det, noiseimage9)

            # 调亮
            if item == 10:
                img = cv2.imread(scr_dir)
                # 第二个参数调节亮度，越大越亮，越小越暗
                rst = imgBrightness(img, 1.6, 1)

                # cv2.imshow("img10", rst)
                # cv2.waitKey()
                det = join(dest_dir, imageName)
                cv2.imwrite(det, rst)

            # 调亮并模糊
            if item == 11:
                img = cv2.imread(scr_dir)
                # 第二个参数调节亮度，越大越亮，越小越暗
                rst = imgBrightness(img, 1.4, 4)
                boxblur11 = cv2.boxFilter(rst, -1, (3, 3))

                # cv2.imshow("img11", boxblur11)
                # cv2.waitKey()
                det = join(dest_dir, imageName)
                cv2.imwrite(det, boxblur11)

            # 调亮加椒盐噪声
            if item == 12:
                img = cv2.imread(scr_dir)
                # 第二个参数调节亮度，越大越亮，越小越暗
                rst = imgBrightness(img, 1.28, 4)
                noiseimage12 = noise(rst, 0.98)  # 将信噪比设定为0.6

                cv2.imshow("img12", noiseimage12)
                cv2.waitKey(3)
                det = join(dest_dir, imageName)
                cv2.imwrite(det, noiseimage12)

            shutil.copyfile(os.path.join(label_path, file[:-4] + '.txt'), os.path.join(dest_dir, labelName))

print("all down")