
Ask HN: Machine learning options for binary image classification - flashman
I have collected a set of several thousand photos from social media, all taken in the same area, some of which contain an image of a particular building. I&#x27;d like to use a classifier to determine whether or not an image contains the building - a simple yes&#x2F;no label.<p>This seems like a job for machine learning, and I&#x27;m happy to manually train a model with up to a few hundred items, but I don&#x27;t know where I should start. I have some experience with text classification (e.g. TF-IDF, Levenshtein distance) but nothing in computer vision.<p>I&#x27;m happy to explore paid services for this, or to dive into something like scikit-learn if it&#x27;s appropriate. I would like to avoid Mechanical Turk if possible because I want to push my knowledge as well as solve a problem.
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dennybritz
It's true that you could train a typical ML model to do this, but depending
what your pictures look like, the easiest solution may be to use Image Feature
Detection and Matching from OpenCV:

[http://opencv-python-
tutroals.readthedocs.org/en/latest/py_t...](http://opencv-python-
tutroals.readthedocs.org/en/latest/py_tutorials/py_feature2d/py_matcher/py_matcher.html#matcher)

