# This file contains metadata for your plugin. Since 
# version 2.0 of QGIS this is the proper way to supply 
# information about a plugin. The old method of 
# embedding metadata in __init__.py will 
# is no longer supported since version 2.0.

# This file should be included when you package your plugin.# Mandatory items:

[general]
name=Produce Training Data For Deep Learning
qgisMinimumVersion=3.0
description=The plugin fragments the remote sensing image, to be used as deep learning training datasets.
version=0.4
author=Pratyush Tripathy
email=pratkrt@gmail.com

about=Deep learning has achieved unprecedented accuracy in a variety of fields, including remote sensing. But not every remote sensing professional has a strong programming background, which is the required skill for practising deep learning. While enough material and sample code for deep learning applications are available in online repositories, pre-processing the remote sensing datasets to reach the training stage is still a tedious task and requires programming knowledge. Proprietary options to pre-process the data only on mouse clicks are available. However, access to such licensed software is often expensive and hence limited for a large population of researchers and practitioners. The plugin bridges the gap by enabling users to generate training samples in the form of image chips for deep learning application.

tracker=https://github.com/PratyushTripathy/QGIS-Plugin-Produce-Training-Samples-For-Deep-Learning/issues
repository=https://github.com/PratyushTripathy/QGIS-Plugin-Produce-Training-Samples-For-Deep-Learning
# End of mandatory metadata

# Recommended items:

# Uncomment the following line and add your changelog:
 changelog= Masked pairs in JPEG format now export 0 and 255 values, earlier it was 0 and 1.

# Tags are comma separated with spaces allowed
tags=Python, Deep Learning

homepage=https://github.com/PratyushTripathy/QGIS-Plugin-Produce-Training-Samples-For-Deep-Learning
category=Raster
icon=icon.png
# experimental flag
experimental=True

# deprecated flag (applies to the whole plugin, not just a single version)
deprecated=False

