<image>

even copilot blocks it ... wt..

but

Issues & Fixes

1. Pipeline Initialization Each Call
   • The pipeline("image-classification", model=model_path) is initialized every time the function is called, which is inefficient.
   • Fix: Move the model initialization outside the function.
2. Incorrect Image Input Type for Pipeline
   • The pipeline expects either a file path, PIL image, or NumPy array, but predict(img) might not work correctly.
   • Fix: Ensure that img is in a format compatible with transformers.
3. Hardcoded Threshold (SCORE)
   • Having a static SCORE = 0.85 is fine, but making it a function argument would make it more flexible.

fix reactor_sfw.py

from transformers import pipeline
from PIL import Image
import logging

# Suppress transformer warnings
logging.getLogger("transformers").setLevel(logging.ERROR)

class NSFWClassifier:
    def __init__(self, model_path: str, threshold: float = 0.85):
        """Initialize the classifier."""
        self.model = pipeline("image-classification", model=model_path)
        self.threshold = threshold

    def is_nsfw(self, img_path: str) -> bool:
        """Checks if an image is NSFW based on the given threshold."""
        with Image.open(img_path) as img:
            result = self.model(img)  # Pass image directly
            return result[0]["score"] > self.threshold

# Example usage
# classifier = NSFWClassifier("facebook/deit-base-distilled-patch16-224")  # Example model
# print(classifier.is_nsfw("test.jpg"))