Imagesmani.py

import os
from random import choice
import shutil

#arrays to store file names
imgs =[]
xmls =[]

#setup dir names
trainPath = 'C:/tensorflow1/models/research/object_detection/images/train/'
testPath = 'C:/tensorflow1/models/research/object_detection/images/test/'
crsPath = 'D:/copies/' #dir where images and annotations stored

#setup ratio (val ratio = rest of the files in origin dir after splitting into train and test)
train_ratio = 0.8
test_ratio = 0.2


#total count of imgs
totalImgCount = len(os.listdir(crsPath))

#soring files to corresponding arrays
for (dirname, dirs, files) in os.walk(crsPath):
    for filename in files:
        if filename.endswith('.xml'):
            xmls.append(filename)
        else:
            imgs.append(filename)


#counting range for cycles
countForTrain = int(len(imgs)*train_ratio)
countForTest = int(len(imgs)*test_ratio)

#cycle for train dir
for x in range(countForTrain):

    fileJpg = choice(imgs) # get name of random image from origin dir
    fileXml = fileJpg[:-4] +'.xml' # get name of corresponding annotation file

    #move both files into train dir
    shutil.move(os.path.join(crsPath, fileJpg), os.path.join(trainPath, fileJpg))
    shutil.move(os.path.join(crsPath, fileXml), os.path.join(trainPath, fileXml))

    #remove files from arrays
    imgs.remove(fileJpg)
    xmls.remove(fileXml)



#cycle for test dir   
for x in range(countForTest):

    fileJpg = choice(imgs) # get name of random image from origin dir
    fileXml = fileJpg[:-4] +'.xml' # get name of corresponding annotation file

    #move both files into train dir
    shutil.move(os.path.join(crsPath, fileJpg), os.path.join(testPath, fileJpg))
    shutil.move(os.path.join(crsPath, fileXml), os.path.join(testPath, fileXml))

    #remove files from arrays
    imgs.remove(fileJpg)
    xmls.remove(fileXml)


#summary information after splitting
print('Total images: ', totalImgCount)
print('Images in train dir:', len(os.listdir(trainPath)))
print('Images in test dir:', len(os.listdir(testPath)))