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process.py
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process.py
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"""
@credit to https://timebutt.github.io/static/how-to-train-yolov2-to-detect-custom-objects/
@author Nils Tijtgat
"""
"""
April 8th, 2018
modified by Dongjun Seung
"""
import glob, os
os.chdir("training")
# Current directory
current_dir = (os.path.dirname(os.path.abspath(__file__)))
# Directory where the data will reside, relative to 'darknet.exe'
path_data = 'data/obj/'
# Percentage of images to be used for the test set
percentage_test = 100;
# 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
counter = 1
index_test = round(100 / percentage_test)
print (index_test)
for pathAndFilename in glob.iglob(os.path.join(current_dir, "*.jpg")):
title, ext = os.path.splitext(os.path.basename(pathAndFilename))
print (title, ext)
if counter == index_test:
counter = 1
file_test.write(path_data + title + '.jpg' + "\n")
else:
file_train.write(path_data + title + '.jpg' + "\n")
counter = counter + 1
os.chdir("..")