ENVI® POCKET GUIDE
Deep Learning

L3HarrisGeospatial.com/deep-learning

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Authored as a derivative from ENVI Deep Learning Tutorials & ENVI Documentation Center by:
CW3 Daniel Ruepong, 125D EN
In association with the U.S. Army Training with Industry (TWI) Program.
©2020 Harris Geospatial Solutions, Inc. All rights reserved. ENVI® is a registered trademarkof L3Harris Technologies. All other marks are the property of their respective owners.
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The ENVI Pocket Guide is a quick reference booklet not intended to beread from cover to cover although it can be. The intent is to provide users
with succinct steps on how to accomplish common tasks in ENVI.
If you need or desire comprehensive explanations of tasks from this guiderefer to the following resources:
ENVI Documentation Center
L3HarrisGeospatial.com/docs

ENVI Tutorials
L3HarrisGeospatial.com/docs/tutorials.html

ENVI Help Articles and Tech Support
L3HarrisGeospatial.com/Support

ENVI Videos
L3HarrisGeospatial.com/Learn/Videos

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CONTENTS¢ Getting Started……………….………..……...............................7-9¢ Deep Learning Single Class
Open and Display Data……………………..…….…..........................11Region of Interest (ROI)………………….……...….…...................12-16
Build a Label Raster…………………...….................................... 17-20
Train a Deep Learning Model………......................................... 21-29
TensorBoard……………...…......................................................... 30-34
Perform Classification………..…...….........................................35-41
Convert Classification Values to ROIs......................................42-45
Training a Deep Learning Model Using the ENVI Modeler......46-51
Generate and Run Code from ENVI Modeler............................52-55
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¢ Deep Learning Multi ClassLabel Training Rasters with ROIs………........................................ 57- Set Up a Deep Learning Project….................................58-59- Define Classes….............................................................60-61- Add Training Rasters…..................................................62-66- Draw ROIs…...................................................................67-70- Restore ROIs…...............................................................71- 72- View Project and Labeling Statistics…...............................73
Train a Deep Learning Model…………………............................74-79
TensorBoard…………………...…......................................................80
Perform Classification………..................................................... 81-88
Export Classes to Shapefiles……………...….............................. 89-96
View Class Activation Rasters………..…...…...........................97-101
Training a Deep Learning Model Using the ENVI Modeler.........102
Generate and Run Code from ENVI Modeler...............................1025

6GETTING STARTEDHARDWARE AND SOFTWARE REQUIREMENTS
1. In addition to having ENVI Deep Learning properly licensed andinstalled on your system, you also must have the following:a. NVIDIA GPU driver version 410.x or higher
b. NVIDIA graphics card with CUDA® Compute Capability
version 3.5 to 7.5c. A minimum of 8GB of GPU memory to train the deeplearning models

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GETTING STARTEDTEST INSTALLATION AND CONFIGURATION
1. Launch ENVI (5.5.x (64-Bit)) to determine if your system meets therequirements and is properly configured to run ENVI Deep Learning.
2. In the ENVI Toolbox, select Deep Learning -> Deep Learning Guide
Map. In the Deep Learning Guide Map, click on Tools and select Test
Installation and Configuration. It may take a few minutes for yoursystem to perform its test.
3. The Test Results dialog opens when the test is complete. The following
message will appear at the top of the Test Results dialog if your system
is properly configured:

8GETTING STARTED

4. S croll to the bottom of the Test Results dialog to see the following
message, further indicating that your system is ready to run ENVI
Deep Learning:

5. If your system is not properly configured to run ENVI Deep Learning,
review the information in the Test Results dialog to identify the problem and to contact Technical Support for assistance.

9ENVI DEEP LEARNING: SINGLE CLASSDeep Learning Single Class
allows users to extract asingle feature by labelingthe feature of interest,
creating a training model ofwhat the feature looks like,and classifying data to findmore of the same featureelsewhere. When executed
properly, Deep Learning
saves time and reduces
margins of error.

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1. Before you begin, it is recommended
that you set up a Deep Learning
project directory to keep your data
and associated files organized.
2. Open your high-resolution image
in ENVI. To view the full image,right-click on the image in the Layer
Manager and select Zoom to Layer
Extent or press F12.

ENVI DEEP LEARNING: SINGLE CLASSOPEN AND DISPLAY DATA

3. Click the Data Manager buttonin the ENVI toolbar. Expand theimage to see the number of bands.
The image used in this guide has
4 bands: red, green, blue, andnear-infrared.
Images used throughout this guide obtained from the National Geodetic Survey:
https://storms.ngs.noaa.gov/storms/dorian/index.html#7/26.970/-80.740

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ENVI DEEP LEARNING: SINGLE CLASSREGION OF INTEREST (ROI)
1. If you are using an existing ROI, skip to BUILD A LABEL RASTER
on page 16.
N ote: You can convert features in other data formats such as *.shp
and *.csv into *.xml ROIs to be used in Deep Learning. Go to Helpin the ENVI main menu to learn more.
2. If you have an existing
ROI but need to update
or modify it before you
use it, right-click on
your image in the Layer
Manager and select
New Region of Interest(ROI). In the ROI Tool,
go to File -> Open andload your ROI.

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THANK YOU FOR YOUR INTERESTIN ENVI® DEEP LEARNING
To continue reading the remaining chapters of the ENVI
Deep Learning Pocket Guide please click the following button.

DOWNLOAD THE COMPLETE POCKET GUIDEFOR MORE INFORMATION:
L3HarrisGeospatial.com
Email: GeospatialInfo@L3Harris.com
Phone: 303.786.9900
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