Author Topic: Feature Request(?): Module For Counting Number of Streets Along a Building  (Read 7921 times)

SethReis

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Hello,

I am working on using the SoftstoryClassifier module to classify multi-story multi-family apartments. However, I am running into an issue with my training data where known soft-story buildings don't appear as soft-stories in the Google Streetview scraped images because the Streetview perspective associated with the address is from the front, but the soft-story parking is down an alleyway around the back.

Because of this, I've found that whether or not a multi-story multi-family apartment building of a certain age has a back alley is a good indicator of whether or not it is a soft story. And so, what I mean to request is a module meant to identify the number of streets along a building, and in particular if a building has a set of parallel streets running alongside it.

I'll admit that I am relatively inexperienced with BRAILS, and so I do not know whether or not BRAILS or even an AI model would be necessary for this type of classification. Alternatively, if anyone has experience with using Google Streetview API to scan all sides of a building from every adjacent street/alleyway meant for cars, that would also solve my issue.

fmk

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Seth,

getting an image from all angles to better determine if there is a soft-story or not is problematic. StreetView will not provide all images necessary as for a majority of houses in urban areas one image from streetview is all that will be avail as neighbouring houses and not streets will be on the other 3 sides. An alternative we discussed briefly was to use drone imagery,  using drones that the NHERI Rapid facility provides for example, to capture all sides of the house. We just did not get far with that effort as the programmer looking after that effort left and nobody expressed much interest in that particular module.

SethReis

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It's no problem at all, I understand. I believe my group and I might have figured out another way to do what we desired, but thank you for the insight.