I'm trying to extract phone number from the following image (after resize:)
my code :
from PIL import Image
from pyocr import pyocr
import pyocr.builders
import cStringIO
import os
os.putenv("TESSDATA_PREFIX", "/usr/share/tesseract-ocr/")
tools = pyocr.get_available_tools()
tool = tools[0]
langs = tool.get_available_languages()
lang = langs[0]
file = "test.png"
txt = tool.image_to_string(Image.open(file),
lang=lang,
builder=pyocr.builders.TextBuilder())
print txt
it returns Empty string. When there is no (-) in the phone number, it returns it correctly. What should I do ? Thanks !
Okay, when I ran your code with tesseract and the image you provided it perfectly returned the text (dashes and spaces included). At that point you could obviously just use txt = txt.replace("-", "").replace(" ", "")
to get rid of the dashes and whitespace.
Buuuuuut I know that OCR (even with us both using tesseract) is going to be different across platforms, so I've included an example of my comment suggestion.
# I changed your imports a bit
from PIL import Image
from pyocr import pyocr
from pyocr import builders
import cStringIO
import os
# set up all your OCR stuff
os.putenv("TESSDATA_PREFIX", "/usr/share/tesseract-ocr/")
tools = pyocr.get_available_tools()
tool = tools[0]
langs = tool.get_available_languages()
lang = "eng" #set language to english to simplify things
# definte a function to return the text of a given image
def doOCR( fName ):
txt = tool.image_to_string(Image.open(fName), lang=lang, builder=builders.TextBuilder())
return txt
# define the path of the image we are going to read
path = "test.png"
# get the image dimensions
im = Image.open(path)
width, height = im.size
# define the points we want to split the image at
# these are the points where the dashes are
split_points = [119, 158]
# define the file names for the image parts
split_names = ["split-1.png", "split-2.png", "split-3.png"]
# define a function to crop the image and remove the dashes
def doCrop(imagePath, cropPath, x, y, x2, y2):
im = Image.open(imagePath)
box = (x, y, x2, y2)
region = im.crop(box) # extract the box region
region.save(cropPath) # save it as a separate image
# in the image you provided each "-" is ~10 pixels long
lenpix = 10
# crop the image at the split points
doCrop(path, split_names[0], 0, 0, split_points[0], height) # get the first section
doCrop(path, split_names[1], split_points[0] + lenpix, 0, split_points[1], height) # get the middle section
doCrop(path, split_names[2], split_points[1] + lenpix, 0, width, height) # get the final section
# define a variable for our final value
finalValue = ""
# finally iterate through split files
# and add the OCR results from each split together
for f in split_names:
finalValue += doOCR(f) # concatenate the ocr value with the final
os.remove(f) # remove the split file now that we've used it
# display the final value
print finalValue
Worked like a charm for me:
Hope this helped!
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