Comments (6)
the function to display bboxes and label text is actually in the code, look for function vis().
I just called it from the main function loop to output the post processed images as well as the text files.
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I attach a slightly modified inference file named test_net_bboxes.py
, which calls the bounding box function and will output the text files as well as the images with bounding boxes with recognized text labels next to those.
Here is a video example of the result.
Hope this helps. Ciao
test_net_bboxes.zip
from research-charnet.
I attach a slightly modified inference file named
test_net_bboxes.py
, which calls the bounding box function and will output the text files as well as the images with bounding boxes with recognized text labels next to those.
Here is a video example of the result.Hope this helps. Ciao
test_net_bboxes.zip
ok,thank!
from research-charnet.
I realise I read this issue a bit too quickly, I guess you meant to draw boxes for each character of a given word instead of a box for the full word.
That is not of interest to me but I guess you can tweak a bit the code, e.g. do a loop for a given word and divide the word box size by the number or letters of the word for the longest of the dimension of the parallelogram, and draw a box for each of those smaller parallelogram. If you want to leave a little gap between each box you will have to make an assumption for the margin to use.
This is a bit of a geometric hack but I would be surprised that the model returns character level information but I did not check that.
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In case required, I have implemented it at here
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