Spaces:
Running
Running
File size: 1,208 Bytes
deb4e3b b91cbda deb4e3b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
import numpy
import opennsfw2
from PIL import Image
import cv2 # Add OpenCV import
import modules.globals # Import globals to access the color correction toggle
from modules.typing import Frame
MAX_PROBABILITY = 1.00
# Preload the model once for efficiency
model = None
def predict_frame(target_frame: Frame) -> bool:
# Convert the frame to RGB before processing if color correction is enabled
if modules.globals.color_correction:
target_frame = cv2.cvtColor(target_frame, cv2.COLOR_BGR2RGB)
image = Image.fromarray(target_frame)
image = opennsfw2.preprocess_image(image, opennsfw2.Preprocessing.YAHOO)
global model
if model is None:
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)
|