Reading meters with tensorflow I'm new to ML world and been reading about ML and TensorFlow.
My goal is to read the following example in real time with Android phone:



So I tried firebase ML OCR and it works really good, it reads the complete value but it does not read the decimal point and also reads a lot of the surrounding text.
So my idea is that I should first detect black and red bounding boxes and then detect individual numbers inside


is this the right way to go? How would I accomplish this? 
Also how do you use two kinds of a model, one to extract a part of the image (black and red bounding areas) and then pass them to OCR model?
What about last digit which can always be in between two numbers (example: 1 and 2)?
Two options :


Use pre-built libraries for OCR + Bounding Box detection   (E.g.: https://www.pyimagesearch.com/2018/08/20/opencv-text-detection-east-text-detector/ for Bouding Box detection and then OpenCV / Tessract for OCR)





Train a Deep learning model for Text Detection in scene . Examples : https://github.com/qjadud1994/CRNN-Keras  and https://github.com/mvoelk/ssd_detectors