settings.ini

[DEFAULT]
lib_name = banet
user = mnpinto
description = A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images
keywords = burned areas, viirs, deep learning, computer vision, remote sensing
author = Miguel Pinto
author_email = mnpinto@fc.ul.pt
copyright = Miguel Pinto
branch = master
version = 0.5.5
min_python = 3.6
audience = Developers
language = English
custom_sidebar = True
license = apache2
status = 3
requirements = geoget fastcore nbdev fastai rasterio geopandas shapely netcdf4 pyhdf
console_scripts = 
	banet_viirs750_download=banet.cli:banet_viirs750_download
	banet_create_dataset=banet.cli:banet_create_dataset
	banet_dataset2tiles=banet.cli:banet_dataset2tiles
	banet_predict_monthly=banet.cli:banet_predict_monthly
	banet_predict_times=banet.cli:banet_predict_times
	banet_train_model=banet.cli:banet_train_model
	banet_nrt_run=banet.cli:banet_nrt_run
nbs_path = nbs
doc_path = docs
doc_host = https://mnpinto.github.io
doc_baseurl = /banet/
git_url = https://github.com/mnpinto/banet/tree/master/
lib_path = banet
title = banet
tst_flags = local
host = github