In the Semantic Segmentation Using Deep Learning tutorial how can I create my own datasets

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Hi,
As the title suggests, I want to replicate the work done here: https://uk.mathworks.com/help/vision/examples/semantic-segmentation-using-deep-learning.html
I am unsure of the best way to make my own dataset to fit this model. I have all of the input images I need, but I don't know the best way to quickly label (color) them in the same fashion.
Is there an efficient way to do this for several hundred files?

Réponses (2)

Asanka Perera
Asanka Perera le 16 Mai 2018
Modifié(e) : Asanka Perera le 16 Mai 2018
1. Use Matlab image labeler and label all your input images.
2. Export the pixel labels using "to file" option. Then, you can see "PixelLabelData" folder with blank .png images. They are not blank and you can use imagesc to view them.
3. Convert all the images in PixelLabelData folder to RGB images using label2rgb command, now you have a dataset similar to this example.
  1 commentaire
nacerdine larbi
nacerdine larbi le 1 Juin 2018
plzz can you explain me how can i do a semantic segmentation if you have a example to show me plz

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Aishwary Jagetia
Aishwary Jagetia le 13 Sep 2018
Modifié(e) : Aishwary Jagetia le 13 Sep 2018

Manually tagging the data is not more a hurdle. Check this out,

https://www.youtube.com/watch?v=tYqnsp-OcLQ

https://www.youtube.com/watch?v=xkSEnDIlvhI

you can quickly create your own image and video segmentation data in no time!!

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