Is it possible to give text format hints in google vision api? - ocr

Question

I'm trying to detect handwritten dates isolated in images.
In the cloud vision api, is there a way to give hints about type?
example: the only text present will be dd/mm/yy, d,m and y being digits
The only thing I found is language hints in the documentation.
Sometimes I get results that include letters like O instead of 0.

Answer 1

There is not a way to give hints about type but you can filter the output using client libraries. I downloaded detect.py and requirements.txt from here and modified detect.py (in def detect_text, after line 283):
response = client.text_detection(image=image)
texts = response.text_annotations
#Import regular expressions
import re
print('Date:')
dateStr=texts[0].description
# Test case for letters replacement
#dateStr="Z3 OZ/l7"
#print(dateStr)
dateStr=dateStr.replace("O","0")
dateStr=dateStr.replace("Z","2")
dateStr=dateStr.replace("l","1")
dateList=re.split(' |;|,|/|\n',dateStr)
dd=dateList[0]
mm=dateList[1]
yy=dateList[2]
date=dd+'/'+mm+'/'+yy
print(date)
#for text in texts:
#print('\n"{}"'.format(text.description))
#print('Hello you!')
#vertices = (['({},{})'.format(vertex.x, vertex.y)
# for vertex in text.bounding_poly.vertices])
#print('bounds: {}'.format(','.join(vertices)))
# [END migration_text_detection]
# [END def_detect_text]
Then I launched detect.py inside the virtual environment using this command line:
python detect_dates.py text qAkiq.png
And I got this:
23/02/17
There are few letters that can be mistaken for numbers, so using str.replace(“letter”,”number”) should solve the wrong identifications. I added the most common cases for this example.