Cats-Vs-Dogs-Flask-webapp

This project is a part of Coursera's Guided Project - Deploy Models with TensorFlow Serving and Flask

It serves as a very basic introduction for deploying TF models using TensorFlow Serving, Docker and creating a simple web app with FLASK.

Steps to follow

1. Create a directory named static. This is required as the input image for the model will be saved here when you run app.py. By default FLASK will read the image from static directory.

2. Install the python packages required:

   pip3 install tensorflow==2.1.0 flask flask-bootstrap requests

3. Launch the docker instance which will serve the TensorFlow SavedModel (in the pets folder):

   sudo docker run -p PORT_NUMBER:8501 --name=pets -v "YOUR_SAVED_MODEL_PATH:/models/pets/1" -e MODEL_NAME=pets tensorflow/serving

   In the project, we used 8502 for the PORT_NUMBER , and YOUR_SAVED_MODEL_PATH needs to be the absolute path of the pets folder in your local machine. So, if you extracted the downloaded zip file in, say, /home/example/ , and want to use 8502 for the server port, the above command will become:

   sudo docker run -p 8502:8501 --name=pets -v "/home/example/pets/:/models/pets/1" -e MODEL_NAME=pets tensorflow/serving

   Please note if you use any other port, you will have to change the MODEL_URL in the app.py file accordingly

4. Now run python3 app.py and visit the link shown in Terminal/Command Prompt.