lromul / gramtion Goto Github PK

I saw this tweet: https://twitter.com/GramtionBot/status/1394429729529270274?s=19

This is the first time I've seen this bot - and it's brilliant! Nice work.

I don't have experience with image recognition so this question may be naive.

I'm wondering if there's a way of using bounded box detection to distribute OCR results into contextual regions. If possible, this may have some interesting outcomes for various common image layouts (such as a comic or as a side-by-side comparison).

It may be possible to limit this process to images with specific properties to reduce false positives, such as predefined lists of image descriptions (e.g. This example, which outputs "Two signs that are sitting next to each other"), images with limited colour palettes (which may be comic strips).

The result of this would be seeing the current output:

Image 1
May show: Two signs that are sitting next to each other.
Сontains text:
working
AT THE OFFICE
AT HOME
SITTING
IN TRAFFIC
WORKING
WORKING
GETTING
LUNCH
CHATTING
WITH
COWOR- / GETTING
KERS/ COFFEE
Irina Blok
Tags: Rectangle, font, parallel, circle, diagram.

Transformed into:

Image 1
May show: Two signs that are sitting next to each other.
3 text regions detected
Region 1 contains text:
working
Irina Blok
Region 2 contains text:
AT THE OFFICE
SITTING
IN TRAFFIC
WORKING
GETTING
LUNCH
CHATTING
WITH
COWOR- / GETTING
KERS/ COFFEE
Region 3 contains the text:
AT HOME
WORKING
Tags: Rectangle, font, parallel, circle, diagram.