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

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.

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.