의미 분할 데이터 집합 이미지 강화 코드

최근에 의미 분할 데이터 집합을 하고 있는데, 다음은 이미지 강화 코드입니다.

# coding=utf-8
import os
from PIL import Image
from skimage import transform
from numpy import *
import numpy as np
import cv2


#     
#     
#   180 
def Enhancement(file_path):
   for fileName in os.listdir(file_path):
       print(fileName)
       im = Image.open(file_path + "\\"+fileName)

       #     
       mirror_lr = im.transpose(Image.FLIP_LEFT_RIGHT)
       mirror_lr.save(file_path + "\\" + 'mirror_lr' + fileName)

       #     
       mirror_tb = im.transpose(Image.FLIP_TOP_BOTTOM)
       mirror_tb.save(file_path + "\\" + 'mirror_tb' + fileName)

       #   180 
       rotate = im.transpose(Image.ROTATE_180)
       rotate.save(file_path + "\\" + 'rotate' + fileName)


#   ：  cv2.imread               
def resize(file_path):
    for fileName in os.listdir(file_path):
       img = cv2.imread(file_path+"\\"+fileName)
       dst = cv2.resize(img, (256, 256), interpolation=cv2.INTER_CUBIC)
       cv2.imwrite(file_path + "\\" + fileName, dst)


def cropped(file_path):
    for fileName in os.listdir(file_path):
        img = cv2.imread(file_path + "\\" + fileName)
        #      [y0:y1, x0:x1]
        cropped = img[8:248, 0:200]
        cv2.imwrite(file_path + "\\" + fileName, cropped)


def gray(file_path):
    for fileName in os.listdir(file_path):
        img = Image.open(file_path + "\\" + fileName)
        rgb = img.convert("L")
        rgb.save(file_path + "\\" + 'gray' + fileName)

def main():
   file_path = './test'
   #resize(file_path)
   Enhancement(file_path)
   #gray(file_path)
   #file_list = os.listdir(file_path)
   # deleteImages(file_path, file_list)
   #cropped(file_path)

if __name__ == '__main__':
    main()