This is the implementation of an API for handling data from a Deep Learning validation pipeline.
After starting the server, Tensorflow analyses the test batches and models.
The metadata and results of this operation can be accessed via GET requests at the API endpoints specified in the .yaml file.
The app uses the Connexion library on top of Flask.
Python 3.5.2+ (Tested only on Python 3.10)
To run the server, please execute the following from the root directory:
pip3 install -r requirements.txt
python3 -m openapi_server
and open your browser to here:
http://localhost:8080/ui/
The OpenAPI definition lives here:
http://localhost:8080/openapi.json
To run the server on a Docker container, please execute the following from the root directory:
# building the image
docker build -t openapi_server .
# starting up a container
docker run -p 8080:8080 openapi_server