2022-04-02 03:41:55 +02:00

34 lines
1.1 KiB
Python

import logging
from waitress import serve
from image_prediction.config import CONFIG
from image_prediction.flask import make_prediction_server
from image_prediction.pipeline import load_pipeline
from image_prediction.utils import get_logger
from image_prediction.utils.banner import show_banner
logger = get_logger()
def main():
def predict(pdf):
# Keras service_estimator.predict stalls when service_estimator was loaded in different process;
# therefore, we re-load the model (part of the pipeline) every time we process a new document.
# https://stackoverflow.com/questions/42504669/keras-tensorflow-and-multiprocessing-in-python
logger.debug("Loading pipeline...")
pipeline = load_pipeline(verbose=CONFIG.service.verbose)
logger.debug("Running pipeline...")
return list(pipeline(pdf))
prediction_server = make_prediction_server(predict)
serve(prediction_server, host=CONFIG.webserver.host, port=CONFIG.webserver.port, _quiet=False)
if __name__ == "__main__":
logging.basicConfig(level=CONFIG.service.logging_level)
show_banner()
main()