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Add stripped inference-only model code mirror
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import cv2
from glob import glob
from tqdm import tqdm
from multiprocessing import Pool
# VIDEO_DIR = "/scratch1/users/od/CelebDF/Real/videos/*.mp4"
VIDEO_DIR = "/scratch1/users/od/FaceForensicC23/videos/*/*.mp4"
ROB_DIR = "robustness"
videos = glob(VIDEO_DIR)
print("Total videos:", len(videos))
type_list = ['CS', 'CC', 'BW', 'GNC', 'GB', 'JPEG', 'VC']
level_list = [1, 2, 3, 4, 5]
def runner(video):
unmatch = []
cap = cv2.VideoCapture(video)
frames = cap.get(cv2.CAP_PROP_FRAME_COUNT)
cap.release()
for t in type_list:
for l in level_list:
rob_video = video.replace("videos", f"robustness/{t}/{l}")
cap = cv2.VideoCapture(rob_video)
if (not frames == cap.get(cv2.CAP_PROP_FRAME_COUNT)):
unmatch.append(rob_video)
cap.release()
return unmatch
results = []
with Pool(10) as p:
for result in tqdm(
p.imap_unordered(
runner,
videos
),
total=len(videos)
):
results.extend(result)
for i in results:
print(i)