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Running
on
Zero
Running
on
Zero
from transformers import pipeline | |
from PIL import Image | |
import logging | |
import os | |
from reactor_utils import download | |
from scripts.reactor_logger import logger | |
def ensure_nsfw_model(nsfwdet_model_path): | |
"""Download NSFW detection model if it doesn't exist""" | |
if not os.path.exists(nsfwdet_model_path): | |
os.makedirs(nsfwdet_model_path) | |
nd_urls = [ | |
"https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/config.json", | |
"https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/model.safetensors", | |
"https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/preprocessor_config.json", | |
] | |
for model_url in nd_urls: | |
model_name = os.path.basename(model_url) | |
model_path = os.path.join(nsfwdet_model_path, model_name) | |
download(model_url, model_path, model_name) | |
SCORE = 0.96 | |
logging.getLogger("transformers").setLevel(logging.ERROR) | |
def nsfw_image(img_path: str, model_path: str): | |
ensure_nsfw_model(model_path) | |
with Image.open(img_path) as img: | |
predict = pipeline("image-classification", model=model_path) | |
result = predict(img) | |
if result[0]["label"] == "nsfw" and result[0]["score"] > SCORE: | |
logger.status(f"NSFW content detected, skipping...") | |
return True | |
return False | |