I have images of identity cards (manually taken so not of same size) and I need to extract the text in it.I used tesseract to predict bounding boxes for each letter and am successful to some extent but some letters are not bounded.  So, I have around 5000 bounding boxes in all images combined.I want to train it so as to predict bounding boxes for remaining letters.After predicting the bounding boxes I will try to classify the image into characters.This is different from conventional machine learning problem where I donot have training and testing data separately.
How to predict on part of image after training on other part of image?
neural network;deep learning;image classification;convnet;computer vision