siglip2-large-patch16-384-nsfw-detect-v5

Установка

pip install -U gradio transformers pillow torch torchvision --index-url https://download.pytorch.org/whl/cu129

Использование

from transformers import AutoImageProcessor, SiglipForImageClassification
from transformers.image_utils import load_image
from PIL import Image
import torch

model_name = "bonndi/siglip2-large-patch16-384-nsfw-detect-v5"

device = ("cuda" if torch.cuda.is_available() else "cpu")

model = SiglipForImageClassification.from_pretrained(model_name).to(device)
processor = AutoImageProcessor.from_pretrained(model_name)

labels = {
    "0": "drawings",
    "1": "hentai",
    "2": "neutral",
    "3": "porn",
    "4": "sexy"
}

def detect_explicit_content(image):
    """Predicts content category in an uploaded image."""
    image = Image.fromarray(image).convert("RGB")
    inputs = processor(images=image, return_tensors="pt").to(device)

    with torch.no_grad():
        outputs = model(**inputs)
        logits = outputs.logits
        probs = torch.nn.functional.softmax(logits, dim=1).squeeze().tolist()

    predictions = {labels[str(i)]: round(probs[i], 3) for i in range(len(probs))}
    return predictions

iface = gr.Interface(
    fn=detect_explicit_content,
    inputs=gr.Image(type="numpy"),
    outputs=gr.Label(label="Prediction Scores"),
    title="siglip2-mini-explicit-content",
    description="Upload an image to classify it as Anime, Hentai, Sensual, Pornographic, or Safe for Work."
)

if __name__ == "__main__":
    iface.launch()```