Supervised learning for image segmentation Hello I am new to Applied ML and trying to solve a problem where I have given several images with few patches in it and masked images where these patches are classified/extracted as training data.Given that i need to use ML to train network such that It can generate those masked images for test data set.
I would like to know which technique will be best suitable in Both the cases where I want to use Python extended libraries like Scikit or Using just Numpy and Scipy.
Thanks in advance
I would suggest you use Python with Ski-Image for Image Related operation. For Machine Learning typically for Deep Learning, you should use Keras with theano/Tensorflow backend with GPU capabilities whichever suits you.

In order to generate masked images, you should use data augmentation.Data Augmentation Documentation for Keras