Create app.py
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app.py
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import tensorflow as tf
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from flask import Flask, request, jsonify
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app = Flask(__name__)
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# Load the model
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model = tf.keras.models.load_model('Erfan11/Neuracraft')
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@app.route('/predict', methods=['POST'])
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def predict():
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data = request.get_json()
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# Preprocess input data
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inputs = preprocess_data(data)
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# Make prediction
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predictions = model.predict(inputs)
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# Postprocess and return results
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results = postprocess_predictions(predictions)
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return jsonify(results)
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def preprocess_data(data):
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# Implement your data preprocessing here
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pass
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def postprocess_predictions(predictions):
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# Implement your result postprocessing here
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pass
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if __name__ == '__main__':
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app.run(debug=True)
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## API Endpoints
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- **POST /predict**: Receives JSON data, returns model predictions.
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