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import argparse
import os
os.environ["MKL_NUM_THREADS"] = "1"
os.environ["NUMEXPR_NUM_THREADS"] = "1"
os.environ["OMP_NUM_THREADS"] = "1"
# from skimage.measure import compare_ssim
from skimage.metrics import structural_similarity as ssim
from functools import partial
from multiprocessing.pool import Pool
from tqdm import tqdm
from utils import get_original_with_fakes
import cv2
cv2.ocl.setUseOpenCL(False)
cv2.setNumThreads(0)
import numpy as np
cache = {}
def save_diffs(pair, root_dir):
ori_id, fake_id = pair
ori_dir = os.path.join(root_dir, "crops", ori_id)
fake_dir = os.path.join(root_dir, "crops", fake_id)
diff_dir = os.path.join(root_dir, "diffs", fake_id)
os.makedirs(diff_dir, exist_ok=True)
for frame in range(320):
if frame % 10 != 0:
continue
for actor in range(2):
image_id = "{}_{}.png".format(frame, actor)
diff_image_id = "{}_{}_diff.png".format(frame, actor)
ori_path = os.path.join(ori_dir, image_id)
fake_path = os.path.join(fake_dir, image_id)
diff_path = os.path.join(diff_dir, diff_image_id)
if os.path.exists(ori_path) and os.path.exists(fake_path):
img1 = cv2.imread(ori_path, cv2.IMREAD_COLOR)
img2 = cv2.imread(fake_path, cv2.IMREAD_COLOR)
try:
d, a = ssim(img1, img2, multichannel=True, full=True)
a = 1 - a
diff = (a * 255).astype(np.uint8)
diff = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
cv2.imwrite(diff_path, diff)
except:
pass
def parse_args():
parser = argparse.ArgumentParser(
description="Extract image diffs")
parser.add_argument("--root-dir", help="root directory", default="/mnt/sota/datasets/deepfake")
args = parser.parse_args()
return args
def main():
args = parse_args()
pairs = get_original_with_fakes(args.root_dir)
os.makedirs(os.path.join(args.root_dir, "diffs"), exist_ok=True)
with Pool(processes=os.cpu_count() - 2) as p:
with tqdm(total=len(pairs)) as pbar:
func = partial(save_diffs, root_dir=args.root_dir)
for v in p.imap_unordered(func, pairs):
pbar.update()
if __name__ == '__main__':
main()
z=2
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