butlerbt / FastMap

Flask deployment of deep learning model performing segmentation task on aerial imagery building footprints

FastMap.ai

Flask deployment of Image segmentation deep learning model

Directories and files to be aware of:

• Flask-env2 conda environment

This project relies on you using the environment.yml file to recreate the Flask-env2 conda environment. To do so, please run the following commands:

# create the zipcode conda environment
conda env create -f environment.yml

# activate the zipcode conda environment
conda activate Flask-env2

• .src source code:

This project contains several .py modules in the src/ directory. Please use the following bash command to install the .src module:

#install the .src modules
pip install -e .

• A static/' directory that contains the static files for the web deployment

• 'app.py'

The flask app script that utilizes the 'src/' modules to process images and make inferences

• templates directory

Contains the results.html page displaying model outputs

Running the Flask Application

To run in a development environment (on your local computer)

export FLASK_ENV=development
env FLASK_APP=app.py flask run

To run in a production environment (used for deployment, but test it out locally first):

export FLASK_ENV=production
python app.py