[models] Add text recognition module

[fg-mindee]

Design a model subpart that is responsible to identify text strings inside the regions of interest of an image

Input

• images: Numpy-style encoded (cropped) images (already read), expected to hold a single character sequence

Output

• text: list of N strings, where N = number of cropped input images

The following components would be required:

• Preprocessor (Detection module : Preprocessor #20, feat: Added function to crop images from bounding boxes #33)
• RecognitionModel (CRNN Module (implemented with VGG16) #35)
• RecognitionProcessor (feat: Added recognition postprocessor with CTC decoder #37)
• RecognitionPredictor (feat: Added high-level predictors #39)

[fg-mindee]

EDIT: as discussed, the recognition module actually expects (cropped) images that are supposed to have a single character sequence. The higher-level object will take care of using localization information from DetectionPredictor to crop the images and pass it to the RecognitionPredictor