app.py

# app.py

from flask import Flask, request, jsonify
from flask_cors import CORS
from transformers import ViTImageProcessor, AutoModelForImageClassification
from PIL import Image
import requests


# Initialize Flask app
app = Flask(__name__)
CORS(app)  # Enable CORS for all routes

# Load model and processor
processor = ViTImageProcessor.from_pretrained('AdamCodd/vit-base-nsfw-detector')
model = AutoModelForImageClassification.from_pretrained('AdamCodd/vit-base-nsfw-detector')

# Classification function
def classify_image(image_url):
    try:
        image = Image.open(requests.get(image_url, stream=True).raw)
        inputs = processor(images=image, return_tensors="pt")
        outputs = model(**inputs)
        logits = outputs.logits

        predicted_class_idx = logits.argmax(-1).item()
        return model.config.id2label[predicted_class_idx]
    except Exception as e:
        return str(e)

# API route to classify the image
@app.route('/api/classify', methods=['GET'])
def classify():
    print('ran')
    image_url = request.args.get('url')
    print(image_url)

    if not image_url:
        return jsonify({'error': 'No image URL provided'}), 400

    classification = classify_image(image_url)
    return jsonify({'classification': classification})

# Run the Flask server
if __name__ == '__main__':
    app.run(debug=True, host='0.0.0.0')