User 2266 | 9/29/2015, 2:21:30 AM
Hi, I came across an idea or predicting number of levels in a house in google street view.
just to prove my theory, I started with Pesadena home http://www.vision.caltech.edu/html-files/archive.html
Looked great and worked well with Dato's NN classifier
I developed a routine where it will capture the house within street view.
So far I have created about 20,000 houses with meta data (manually) each picture has floors = 1, 2, 1.5 etc
used dato to determine the Nueral Net based on the data.
Result however is not as good as the result from the exercise of Pesadena home example data.
applied the same technique, yet, result was significantly lower (Pesadena home was only about 150 examples where as G street view has over 20k!)
as of next step, I am thinking, if there is a way to >>> recognize the house as an object in street view picture and focus on house,
possibly I will have a higher change of predicting a house level?
so far, I have only used grey scale, 400x600 resized images. trainsf['image'] = gl.imageanalysis.resize(train_sf['image'], 580, 389, channels=1)~~~~~~~~
at this point any idea is appreciated. I will try images in different color spaces this week ( thank god, I have Titan X)