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split.py
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split.py
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#
# Yolo Data Splitter
# Developed by Scott Uneberg, https://github.com/robotwhispering
# Under MIT License
# Updated 09/04/2020
#
from pathlib import Path
# set path to /darknet/data directory (subfolders will be recursively included)
img_path = "./data"
# percentage of images to be used for the test set
pcnt_test = 0
r = range(10,30+1)
while not pcnt_test:
try:
pcnt_test = int(input("Enter the percentage for testing (10-30): "))
if pcnt_test not in r:
raise ValueError
except ValueError:
pcnt_test = 0
print("Please enter an integer between 10 and 30!")
# create and/or truncate train.txt and test.txt
file_train = open("train.txt", "w")
file_test = open("test.txt", "w")
# populate train.txt and test.txt
iterator = 1
test_cnt = 0
train_cnt = 0
index_test = round(100 / pcnt_test)
for path in Path(img_path).rglob("*.jpg"):
if iterator == index_test:
iterator = 1
file_test.write(str(path.resolve()) + "\n")
test_cnt += 1
else:
file_train.write(str(path.resolve()) + "\n")
iterator += 1
train_cnt += 1
# display image path on screen
print("Image directory: " + str(Path(img_path).resolve()))
# display results to console
print("Training/Testing percentage split: " + str(pcnt_test))
print("Training set: " + str(train_cnt) + " files")
print("Testing set: " + str(test_cnt) + " files")
print("Dataset splitting complete!")