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rotate training images #24

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andrewljohnson opened this issue May 10, 2016 · 0 comments

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andrewljohnson commented May 10, 2016

Benefits

produce more training data
make analysis more applicable using one data set to train, and another to set (less overfit locally and regionally/globally hopefully)

Notes

each rotation needs to be unique, so that the same image/label pair doesn't accidentally get put into both training and test data

andrewljohnson added the enhancement label

andrewljohnson mentioned this issue

import NAIP data into a postgres database #23

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