PyOpenNSFWDetector

PyOpenNSFWDetector is a project that uses machine learning to detect NSFW (Not Safe For Work) content in photos. It can be useful for content filtering on social media, online stores, and other platforms where content control is required.

The result has binary values:

• 0 if there is no NSFW content in the photo
• 1 if NSFW content is detected.

Quick start

git clone https://github.com/imitatehappiness/PyOpenNSFWDetector.git
cd PyOpenNSFWDetector
pip install -r requirements.txt
python example.py 

Examples

1. Example Usage

from detector.detector import NSFWDetector

model_path = 'model/nude_detector_model.h5'
NSFW_detector = NSFWDetector(model_path)

# url path
path = 'https://s.pfst.net/2024.02/8081984667080bec99cc7d12e65a5c11aa8a70ef9cefc_b.jpg'
print("predict:", NSFW_detector.predict(path))

path = 'https://s.pfst.net/2022.08/6971621667080909e89391f886395410b385c888ab881_b.jpg'
print("predict:", NSFW_detector.predict(path))

# local path
path = "resources\\local_image_adult.jpg"
print("predict:", NSFW_detector.predict(path))

path = "resources\\local_image_adult.jpg"
print("predict:", NSFW_detector.predict(path))

Execution time

Execution time for 1 image: 1.008302927017212 seconds

Execution time for 10 images: 2.7786076068878174 seconds

Execution time for 100 images: 28.80970525741577 seconds

Execution time for 1000 images: 287.2076916694641 seconds

2. Example Usage (API)

from detector.detector import NSFWDetector
from flask import Flask, jsonify, request

model_path = 'model/nude_detector_model.h5'
NSFW_detector = NSFWDetector(model_path)

app = Flask(__name__)

@app.route('/predict', methods=['POST'])
def predict():
	url = request.json.get('url')
	prediction = NSFW_detector.predict(url)
	return jsonify({'prediction': prediction})

if __name__ == '__main__':
	app.run(debug=True)

API

/predict (POST)

curl -X POST -H "Content-Type: application/json" -d '{"url": "https://example.com/image.jpg"}' http://127.0.0.1:5000/predict

Model

Model from NSFWGuard