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.
- 0 if there is no NSFW content in the photo
- 1 if NSFW content is detected.
git clone https://github.com/imitatehappiness/PyOpenNSFWDetector.git
cd PyOpenNSFWDetector
pip install -r requirements.txt
python example.py 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 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
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)curl -X POST -H "Content-Type: application/json" -d '{"url": "https://example.com/image.jpg"}' http://127.0.0.1:5000/predict
Model from NSFWGuard
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent