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.env

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+API_KEY="mysecretapikey123456"

app.py

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+from flask import Flask, request, jsonify
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing import image
+import numpy as np
+import requests
+from io import BytesIO
+from PIL import Image
+
+# Ambil api key dari .env
+import os
+from dotenv import load_dotenv
+load_dotenv()
+
+API_KEY = os.getenv('API_KEY')
+
+app = Flask(__name__)
+
+# Definisikan ukuran gambar
+img_width, img_height = 150, 150
+
+# Memuat model
+model = load_model('inceptionv3_nsfw_model.h5')
+
+def classify_image(img):
+    img = img.resize((img_width, img_height))
+    img_array = image.img_to_array(img)
+    img_array = np.expand_dims(img_array, axis=0) / 255.0
+
+    predictions = model.predict(img_array)
+    class_names = ['sexy', 'hentai', 'porn', 'neutral', 'drawings']
+    result = dict(zip(class_names, predictions[0].astype(float)))
+
+    return result
+
+def check_api_key(request):
+    api_key = request.headers.get('x-api-key')
+    return api_key == API_KEY
+
+@app.route('/classify', methods=['POST'])
+def classify():
+    if not check_api_key(request):
+        return jsonify({'error': 'Invalid or missing API key'}), 403
+    
+    data = request.json
+    img_url = data.get('image_url')
+    
+    if not img_url:
+        return jsonify({'error': 'No image URL provided'}), 400
+    
+    try:
+        response = requests.get(img_url)
+        img = Image.open(BytesIO(response.content))
+    except Exception as e:
+        return jsonify({'error': str(e)}), 400
+    
+    result = classify_image(img)
+    return jsonify(result)
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=5000)

requirements.txt

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+tensorflow
+keras
+numpy
+python-dotenv