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import threading
import numpy
import opennsfw2
from PIL import Image
from keras import Model
from roop.typing import Frame
PREDICTOR = None
THREAD_LOCK = threading.Lock()
MAX_PROBABILITY = 999
def get_predictor() -> Model:
global PREDICTOR
with THREAD_LOCK:
if PREDICTOR is None:
PREDICTOR = opennsfw2.make_open_nsfw_model()
return PREDICTOR
def clear_predictor() -> None:
global PREDICTOR
PREDICTOR = None
def predict_frame(target_frame: Frame) -> bool:
image = Image.fromarray(target_frame)
image = opennsfw2.preprocess_image(image, opennsfw2.Preprocessing.YAHOO)
views = numpy.expand_dims(image, axis=0)
_, probability = get_predictor().predict(views)[0]
return probability > MAX_PROBABILITY
def predict_image(target_path: str) -> bool:
return opennsfw2.predict_image(target_path) > MAX_PROBABILITY
def predict_video(target_path: str) -> bool:
_, probabilities = opennsfw2.predict_video_frames(video_path=target_path, frame_interval=100)
return any(probability > MAX_PROBABILITY for probability in probabilities)
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