DEEP LEARNING in QGIS: Image Segmentation (Aerial and Satellite) with the DEEPNESS Plugin

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The QGIS Deepness Plugin allows you to perform deep neural remote sensing directly in QGIS with pre-trained models. This tutorial demonstrates how to install the Deepness plugin, download pre-trained deep-learning models, and apply existing models to aerial and satellite images. This is one way you can apply Geo AI directly in QGIS.
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21 фев 2024

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Комментарии : 28

@geospatialschool 5 месяцев назад

FREE GIS Courses: geospatialschool.com

@GEORGE.M.M 5 месяцев назад

This is a massive time saver, thank you!

@geospatialschool 5 месяцев назад

You're welcome. Glad it's helpful!

@lc4468 2 месяца назад

Daaaaaaaang. It worked surprisingly well on .45m imagery. Thanks for sharing!

@geospatialschool 2 месяца назад

Great to hear!

@amritanshuraj1 5 месяцев назад

thank you, this is very helpful

@geospatialschool 5 месяцев назад

You're welcome!

@BongaLovesJesus 5 месяцев назад

This is great thanks.

@geospatialschool 5 месяцев назад

You're welcome!

@jupita3000 10 дней назад

What if I only wanted a 2 class output? Ex. pervious and impervious. How would I specify that? Is it possible with this plugin?

@taufiqhidayat628 4 месяца назад

can i get the error value?

@axeLeonhardt 4 месяца назад

Are there any pre-trained models available for high-resolution drone images, or does it require training? thanks for sharing

@geospatialschool 4 месяца назад

There aren't any with this plug-in. You you may be able to find some elsewhere

@coolsamuel4354 5 месяцев назад

Massive massive massive

@mohamedelgamal6333 5 месяцев назад

Dear Sir, Many thanks for this greate video. I followed the stepa you mentioned and I installed the deepness plugin successfully and test it then when I triedd to apply it on a rater image it gives python error and a message " This plugin is incompatible with this version of QGIS Plugin designed for QGIS 3.22 - 3.99" despite I am using QGIS 3.18. Any help will be appreciated.

@mohamedelgamal6333 5 месяцев назад

Many thanks Sir, I figured out that it seems I need to reinstall some of the other python package couple of times and it is now working. Thank you again

@geospatialschool 5 месяцев назад

You need to update we qgis so that your version is at least 3.22

@lorenzoconti7372 3 месяца назад

there are any object based classification model for Landsat ?

@geospatialschool 3 месяца назад

Object-based classification is usually implemented with high res data where objects (like trees or buildings) are composed of many pixels. Landsat is coarse enough that pixel-based methods are generally used, though I'm sure there are some object based approaches if you look around

@sridharan19 4 месяца назад

Sir can we map demolition and construction waste using this?

@kyawnaingwin8300 4 месяца назад

To my understanding, you have to train your detection model first with sample images with lable boxes of your object of interest. Then you get a model and use on QGIS here.

@desireespindler3958 3 месяца назад

Thank you for this great video. I have a problem, when I wannt to load the model deeplabv3_landcover_4c.onnx on Deepnes, I get this error "Error! Failed to load the model! Model may be not usable." Why could it be? From already thank you very much

@geospatialschool 3 месяца назад

To be honest, I'm not sure. You'll have to look into the deepness documentation and ask their team

@nadezhda_belyaeva_ 2 месяца назад

I had the same error when using Qgis version 3.34, and with version Qgis 3.28 model loaded without any problems

@dauletkairatov4620 19 дней назад

I’ve got same problem, if u have a chance can u gimme some tips how to resolve this problem

@coolsamuel4354 5 месяцев назад

Can the first model work on images from Google? Thanks for the video

@geospatialschool 5 месяцев назад

Maybe. You'll have to give it a try and perform some accuracy analysis. As with any model, it's going to be wrong sometimes. You'll have to determine if it will work for you specific application.

@coolsamuel4354 5 месяцев назад

@@geospatialschool thanks I tried it but I guess it was designed for Poland and a bit of Europe. The result accuracy was very poor