The idea of this project is a simple web application for the dog breed classifier developed in my dog-project. Caveat: This is very rudimentary code and its not heavily tested. This is also my first web development project, so there will be a lot of things to improve and I am also happy to receive suggestions. But I am not sure how strongly I am going to develop this project in future.
These instructions will get you a copy of the project up and running on your local machine.
- Clone the repository and navigate to the project folder:
git clone https://github.com/gro1m/dogbreed_flask
cd dogbreed_flask
- Set up a virtual environment (called
test-envhere as an example):
conda create --name test-env python=3.6 anaconda
- Install the project requirements located in the bash script requirements.sh:
./requirements/requirements.sh
- Execute setup.py:
pip install --editable .
- Set environment variables:
export FLASK_APP=dogbreed_flask
export FLASK_DEBUG=0
- Run the flask application:
flask run
- Navigate to
http://localhost:5000/in a web-browser. - Choose an image file on your computer by pressing the first button and then press the
Upload!button. - Wait and then see the classification of the image by the dog breed classifier.
NOTE: FLASK_DEBUG=0 has to be set, as otherwise issues with loading a keras model occur, which is discussed and observed by spearsem on keras-team/keras#5640.
This project is licensed under the MIT License - see the LICENSE.txt file for details
I acknowledge that the html code is mainly from Ibrahim Mokdad's repository https://github.com/ibrahimokdadov/upload_file_python and has been minorly adapted to my use case. The dogbreed_detector.py is the main function and uses the model from https://github.com/gro1m/dog-project.