CODEWITHSUNDEEP
pythontesseract
c.Parsi
c.Parsi

Reputation: 771

How to get Tesseract confidence levels in python or command window?

How can we get the confidence levels after OCR of an image using tesseract 3.05 in windows? I am calling tesseract from python using subprocess commands:

retcode = subprocess.call("tesseract -l eng myImage.png txt -psm 6" , stdin=None, stdout=False, stderr=None, shell=False)

Upvotes: 4

Views: 18990

Answers (3)

Stef
Stef

Reputation: 30589

You may use tsv output:

tesseract testing/eurotext.png testing/eurotext-eng -l eng tsv

The confidence level is in the last but one column.

Upvotes: 1

Ayanava Sarkar
Ayanava Sarkar

Reputation: 381

Adding to Stef's answer, here is a sample command to check the confidence value in 'output.tsv' file.

tesseract Ancestry1.jpg output --oem 1 -l eng tsv

Here, 'Ancestry1.jpg' is the image file to be input to tesseract. oem 1 is for using the LSTM in 4.0. The confidence is stored in 'output.tsv' file

The link to the official Tesseract webpage for confidence levels: Tesseract Wiki

Upvotes: 3

Vu Gia Truong
Vu Gia Truong

Reputation: 1032

This is the wrapper that you need: https://pypi.python.org/pypi/tesserocr/2.0.0 . Also there are tons of python wrapper out there, but this library is the closest wrapper that nearly cover all of C++ API.

Example: 

from PIL import Image
from tesserocr import PyTessBaseAPI

image = Image.open('/usr/src/tesseract/testing/phototest.tif')
with PyTessBaseAPI() as api:
    api.SetImage(image)
    boxes = api.GetComponentImages(RIL.TEXTLINE, True)
    print 'Found {} textline image components.'.format(len(boxes))
    for i, (im, box, _, _) in enumerate(boxes):
        # im is a PIL image object
        # box is a dict with x, y, w and h keys
        api.SetRectangle(box['x'], box['y'], box['w'], box['h'])
        ocrResult = api.GetUTF8Text()
        conf = api.MeanTextConf()
        print (u"Box[{0}]: x={x}, y={y}, w={w}, h={h}, "
               "confidence: {1}, text: {2}").format(i, conf, ocrResult, **box)

Upvotes: 3

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