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BirdIdentifier

A website to identify 20 most common UK birds using a CNN trained on a dataset of 3000 images. Data taken from https://www.kaggle.com/code/davemahony/2-20-uk-garden-bird-ds-prep-with-imagelabs.

In order to run, you need to run model.py and save it as model.h5. This allows for the weights to be pulled through to the application. I have also uploaded the model.py which gets updated to improve accuracy. Updated model using batch norm coming soon. On validation sets, I have reached ~83% and on real life data, i.e. videos from Youtube etc. it is lower which needs improving!

Video classification has also been added with the return a JSON output of a prediction per frame which needs object tracking added.

Once you have your model.h5 file, you need to cd to the file path, i.e. in my case, its WhatsInMyGarden. Then,

python app.py

or flask run

and it will run on a local server.

Recently, have added a way to register for a website and login. The log in info gets stored in a database. Currently no benefits of logining in but purely for my practice at working with live databases and querying it.

Warning: If, like me, you have an M1 chip device, you may encounter "Hardware problems" upon running. See https://stackoverflow.com/questions/65383338/zsh-illegal-hardware-instruction-python-when-installing-tensorflow-on-macbook or consider installing a Flask environment which worked for me.

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Home project. Flask app for CNN to identify 20 most common UK birds using Tensorflow. Being updated to store info in SQLLite database as practice with queries.

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