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@bertcarremans
Last active November 5, 2021 09:49
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Split images randomly over train or validation folder
# Copyright 2014-2017 Bert Carremans
# Author: Bert Carremans <bertcarremans.be>
#
# License: BSD 3 clause
import os
import random
from shutil import copyfile
def img_train_test_split(img_source_dir, train_size):
"""
Randomly splits images over a train and validation folder, while preserving the folder structure
Parameters
----------
img_source_dir : string
Path to the folder with the images to be split. Can be absolute or relative path
train_size : float
Proportion of the original images that need to be copied in the subdirectory in the train folder
"""
if not (isinstance(img_source_dir, str)):
raise AttributeError('img_source_dir must be a string')
if not os.path.exists(img_source_dir):
raise OSError('img_source_dir does not exist')
if not (isinstance(train_size, float)):
raise AttributeError('train_size must be a float')
# Set up empty folder structure if not exists
if not os.path.exists('data'):
os.makedirs('data')
else:
if not os.path.exists('data/train'):
os.makedirs('data/train')
if not os.path.exists('data/validation'):
os.makedirs('data/validation')
# Get the subdirectories in the main image folder
subdirs = [subdir for subdir in os.listdir(img_source_dir) if os.path.isdir(os.path.join(img_source_dir, subdir))]
for subdir in subdirs:
subdir_fullpath = os.path.join(img_source_dir, subdir)
if len(os.listdir(subdir_fullpath)) == 0:
print(subdir_fullpath + ' is empty')
break
train_subdir = os.path.join('data/train', subdir)
validation_subdir = os.path.join('data/validation', subdir)
# Create subdirectories in train and validation folders
if not os.path.exists(train_subdir):
os.makedirs(train_subdir)
if not os.path.exists(validation_subdir):
os.makedirs(validation_subdir)
train_counter = 0
validation_counter = 0
# Randomly assign an image to train or validation folder
for filename in os.listdir(subdir_fullpath):
if filename.endswith(".jpg") or filename.endswith(".png"):
fileparts = filename.split('.')
if random.uniform(0, 1) <= train_size:
copyfile(os.path.join(subdir_fullpath, filename), os.path.join(train_subdir, str(train_counter) + '.' + fileparts[1]))
train_counter += 1
else:
copyfile(os.path.join(subdir_fullpath, filename), os.path.join(validation_subdir, str(validation_counter) + '.' + fileparts[1]))
validation_counter += 1
print('Copied ' + str(train_counter) + ' images to data/train/' + subdir)
print('Copied ' + str(validation_counter) + ' images to data/validation/' + subdir)
@parikshit14
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saved a lot of time
thanks

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