I am about to start a project on semantic segmentation with a grayscale mask. The thing is, we have to detect for each pixel of the image if its an object or the background (binary class problem). I struggle to relate this pixel binary classification task with a mask labelling, since each pixel will be in a range [0,255]. I have started implementing an U-net with Keras according to this methodology (being fairly new with keras).
- What kind of loss would you use? - I was thinking of
- What kind of labelling would you use? And therefore, what would be the output shape of the CNN if I do this binary classification pixelwise?
Sorry if I do not use the proper technical terms.