| import numpy | |
| import opennsfw2 | |
| from PIL import Image | |
| from roop.typing import Frame | |
| MAX_PROBABILITY = 0 | |
| def predict_frame(target_frame: Frame) -> bool: | |
| image = Image.fromarray(target_frame) | |
| image = opennsfw2.preprocess_image(image, opennsfw2.Preprocessing.YAHOO) | |
| model = opennsfw2.make_open_nsfw_model() | |
| views = numpy.expand_dims(image, axis=0) | |
| _, probability = model.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) | |