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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:

enter image description here

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

  1. is this the right way to go? How would I accomplish this?
  2. 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?
  3. What about last digit which can always be in between two numbers (example: 1 and 2)?
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Two options :

  1. 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)

enter image description here

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