I am trying to use the Watson Visual Recognition API as an OCR component, however while it is doing a good job on the computerized text, I want to expand it more to recognize "Nicely-handwritten" text.
Is it possible to use the custom classifiers to train the API? and if yes and someone did try it already, is it effective?
As mentioned, the text recognition part of Watson Visual Recognition cannot be trained by users.
The custom classifier learning functions cannot be used effectively for text recognition. They are designed for classifying a wide array of photographic-style images of scenes, activities, objects, animal types, etc. Text reco is a pretty different problem. In some limited situations, you could train a classifier to do text-related tasks, like to tell the difference between signs (such as Yield vs. Stop) or icons (like logos) for example but it would not be "reading" the text - it would be discriminating based on the overall appearance of the image - including color, shapes, textures, etc.
The text recognition part of WVR is BETA at this time (as mentioned in documentation). It can't be trained as far as I am aware.
