- If it's any possible kind of building (wood, glass, steel, masonry, etc.) and any possible kind of masonry (brick, blocks, marble, limestone, stucco, cement, tile, different colors, etc.) then I think it could be difficult. You'd probably have to use SegNet to train a deep learning model with thousands of images.
- If you have a more limited set of images, like houses made of only red brick, you could possibly get by with traditional methods like a texture filter like stdfilt() or entropyfilt().
Detect masonry from an image
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Hi
I'm trying to create a file which detects masonry from walls (eg. facade of a building). So basically this code should detect masonry from an image and isolate it into a 2D model. What's the best way to do this?
Thanks in advance.
-Ax
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Image Analyst
2020 年 11 月 22 日
Depends on how varied your images are.
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