228 - Semantic segmentation of aerial (satellite) imagery using U-net

This video demonstrates the process of pre-processing aerial imagery (satellite) data, including RGB labels to get them ready for U-net. The video also demonstrates the process of training a U-net and making predictions.

Code generated in the video can be downloaded from here:

My Github repo link:

The dataset consists of aerial imagery of Dubai obtained by MBRSC satellites and annotated with pixel-wise semantic segmentation in 6 classes. The total volume of the dataset is 72 images grouped into 6 larger tiles. The classes are:

Building: #3C1098
Land (unpaved area): #8429F6
Road: #6EC1E4
Vegetation: #FEDD3A
Water: #E2A929
Unlabeled: #9B9B9B

Images come in many sizes: 797x644, 509x544, 682x658, 1099x846, 1126x1058, 859x838, 1817x2061, 2149x1479​

Need to preprocess so we can capture all images into numpy arrays. ​
Crop to a size divisible by 256 and extract patches.​

​Masks are RGB and information provided as HEX color code.​

Need to convert HEX to RGB values and then convert RGB labels to integer values and then to one hot encoded. ​

​Predicted (segmented) images need to converted back into original RGB colors. ​

​Predicted tiles need to be merged into a large image by minimizing blending artefacts (smooth blending). ​(Next video)

[jacobusstrydom]

Thanks for this. I work with aerial/satellite images everyday and it's the reason I started to watch your videos. Great work as always!!!

[luzluz]

wow!! THANK YOU SO MUCH!! I wish all youtubers (and professors!!!) explain things with this level of detail! this is the true democratization of education

[jschlesinger]

You are the first CS and one of the first data sci teachers I have ever had that is thorough and clear. Thank you!

[ausialfrai]

Great point about resizing the labels, I used to resize and never paid attention to the interpolation that may be happening!! Thank you

[Sebastian-zk]

Thank you very much for this and also thank you for your 'painfully slow pace' ;-)

[paulikhane]

I must say your videos have really taught a lot in the last weeks I have watched them. You have become my favorite teacher. Thanks a lot and God bless. I am currently working on a startup idea and wish I can reach out to ask some questions or get directions if that is okay?

[prisaysyo]

Hey, I have been trying to get into Semantic Segmentation for a while now, and really your videos have helped me a tons lot. Thank you so much!!

[xedasxedas]

Another great video. If your viewership is growing keep explaining it with details and/or add some link to one of your other videos if the detail is to much of a detour.

[jhongomez]

I will be eternally grateful for your explanation 👍🏾

[abdulla]

Thanks Sreeni, since my job is about cities for sure I will make sure to follow this video carefully. Keep growing, big fan of you : )

[anshumanmandal]

amazing work such a extensive tutorial see ur entire playlist for more

[gugu]

really impressed how you explain... even a small bit of code. Thanks! please keep up the good work.

[chaitanyasundaresh]

Thank you so much for this channel sir...it is a one stop channel for learning ML image processing from scratch...I am recomending this to all my friends

[tanugupta]

Thank you for such a detailed explanation. I learned a lot from your videos.

[rbhambriiit]

Thanks for the video. Wondering why/how you decided to make patches for images with different sizes. Did you try resizing all images to a common size by any chance?

[alinebarrocamarra]

Thank you for the videos. They are amazing and very helpful. I saw some other people with the same problem as me. Could you make a video considering more than 3 channels (RGB)? Like for 7, 8… It would be very helpful for my research. Best regards.

[henkenssymine]

thanks so much for all your videos! my satellite images however are also all different sizes, but I wouldn't be able to crop them into all similar sizes as that would eliminate important context. Is it really necessary? are there other ways to feed these images to the UNet, not using 1 single numpy array?

[debabratagogoi]

Great explanation, really help me to understand how to proceed with such related work, thank you for that. I just need to ask, whether georeference information will be available after the processing?

[leothomas]

Joining other people's comment, it would be wonderful if you can provide us with some tutorials for segmenting satellite images with more than 3 channels. 🙏🙏

[nayo]

I am loving your content. I am wondering if you would consider doing a tutorial on urban scene segmentation e.g. using something like the Cityscapes dataset? I’m looking at urban scene semantic segmentation at the moment for a project but there are no good, clear end to end tutorials out there so I’m having to piece it together using your tutorials for other applications.