Hi, Can scikit-image be used for supervised learning?
I have training data, where each sample is composed of a raw RGB image, a black-and-white image mask showing the laser projection onto the image, and the laser range finder distance measurements in millimetres. Is there any algorithm in scikit-image that I could use to train a predictor that could estimate the distance at each pixel in an image? I've gone through all the examples, and none of them seemed to directly apply. The image segmentation example seemed to be the closest, but that didn't use supervised learning, so I wasn't sure how I could adapt it's code. Can this goal be accomplished with sckit-image? If not, is there another library and algorithm you could recommend? Regards, Chris -- You received this message because you are subscribed to the Google Groups "scikit-image" group. To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscr...@googlegroups.com. To post to this group, send an email to scikit-image@googlegroups.com. To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/ae5a4626-ce3f-4e9c-8598-14d35aaba2b9%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
