This app exhibits the high accuracy and reliability of the Sequential Model CNN deployed as a web app with Flask and Python

Dependencies:
keras==2.3.1
tensorflow==1.14.0
scikit-image==0.17.2
h5py==2.10.0

Directions:
Create an empty directory called uploads in mlweb3.
Current Labels are: 'airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship'
Place images of these kinds into mlweb3/uploads.

In Linux Bash:

cd Flask-ML-Web-App export FLASK_APP=path_to/Flask-ML-Web-App/mlweb3/__init__.py export FLASK_ENV=development flask run 

Output will direct you to localhost http://127.0.0.1:5000/

Browse to mlweb3/uploads and upload your image.
The algorithm will classify the image as one of the labels with ~90% confidence.

Trained via Sequential Model CNN with CIFAR-10 dataset.