import os
import argparse
import progressbar
from shutil import copy
from Utils import inception_score as ins
from Utils import image_processing as ip
def prepare_inception_data(o_dir, i_dir):
if not os.path.exists(o_dir):
os.makedirs(o_dir)
cnt = 0
bar = progressbar.ProgressBar(redirect_stdout=True,
max_value=progressbar.UnknownLength)
for root, subFolders, files in os.walk(i_dir):
if files:
for f in files:
if 'jpg' in f:
f_name = str(cnt) + '_ins.' + f.split('.')[-1]
cnt += 1
file_dir = os.path.join(root, f)
dest_path = os.path.join(o_dir, f)
dest_new_name = os.path.join(o_dir, f_name)
copy(file_dir, o_dir)
os.rename(dest_path, dest_new_name)
bar.update(cnt)
bar.finish()
print('Total number of files: {}'.format(cnt))
def load_images(o_dir, i_dir, n_images=3000, size=128):
prepare_inception_data(o_dir, i_dir)
image_list = []
done = False
cnt = 0
bar = progressbar.ProgressBar(redirect_stdout=True,
max_value=progressbar.UnknownLength)
for root, dirs, files in os.walk(o_dir):
if files:
for f in files:
cnt += 1
file_dir = os.path.join(root, f)
image_list.append(ip.load_image_inception(file_dir, 0))
bar.update(cnt)
if len(image_list) == n_images:
done = True
break
if done:
break
bar.finish()
print('Finished Loading Files')
return image_list
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--output_dir', type=str, default="Data/ds_inception",
help='directory to dump all the images for '
'calculating the inception score')
parser.add_argument('--data_dir', type=str,
default="Data/synthetic_dataset/ds",
help='The root directory of the synthetic dataset')
parser.add_argument('--n_images', type=int, default=30000,
help='Number of images to consider for calculating '
'inception score')
parser.add_argument('--image_size', type=int, default=128,
help='Size of the image to consider for calculating '
'inception score')
args = parser.parse_args()
imgs_list = load_images(args.output_dir, args.data_dir,
n_images=args.n_images, size=args.image_size)
print('Extracting Inception Score')
mean, std = ins.get_inception_score(imgs_list)
print('Mean Inception Score: {}\nStandard Deviation: {}'.format(mean, std))
