Cats Vs Dogs Web App
This is the back-end service that provides the core ML logic for my web application to predict whether an image is a cat or a dog. It's a Dockerized Flask application that runs a pre-trained Tensorflow model at inference time. The model is trained in a notebook in this repository called "notebooks/cats_vs_dogs.ipynb". Specifically, this uses a MobileNetV2 model that was originally trained on ImageNet and is fine-tuned on a TensorFlow cats-and-dogs dataset.
It uses https://github.com/jjbuck/CatsVsDogsInfrastructure as a starting point, which is generated from a generic template I created (https://github.com/jjbuck/FargateServiceInfrastructure).
The front end of this web app is http://jonathanjbuck.com/cats-vs-dogs/index.html.
Possibilities for Improvement
Because this was only a personal exercise, there's a lot of room for improvement here, including but not limited to
- Using a production web server instead of the Flask dev server
- Infrastructure auto scaling
- A fancier front end design
- More user configuration of the back-end ML model
- ...PRs welcome!
Credits
This web app is inspired by (and sometimes uses code snippets directly from) the following.