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