DeepFakeAI/predictor.py

import threading
import numpy
import opennsfw2
from PIL import Image
from keras import Model

from DeepFakeAI.typing import Frame

PREDICTOR = None
THREAD_LOCK = threading.Lock()
MAX_PROBABILITY = 0.75


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)