How to represent:
Why?
The following results are presented for Tesseract: the original set of samples achieves a precision of 0.907 and 0.901 recall rate, while the preprocessed set leads to a precision of 0.929 and a recall of 0.928. Thompson et al.
Tesserocr is a Python wrapper around the Tesseract C++ API. Whereas Pytesseract is a wrapper for the tesseract-ocr CLI. Therefore with Tesserocr you can load the model at the beginning or your program, and run the model separately (for example in loops to process videos).
Optical Character Recognition (OCR) is a technology that is used to recognize text from images. It can be used to convert tight handwritten or printed texts into machine-readable texts. To use OCR, you need to install and configure tesseract on your computer. First, download the Tesseract OCR executables here.
The OSD mode provides us with meta-data of the text in the image, including both estimated text orientation and script/writing system detection. The text orientation refers to the angle (in degrees) of the text in the image.
You must set the "page segmentation mode" to "single char".
For example, in Android you do the following:
api.setPageSegMode(TessBaseAPI.pageSegMode.PSM_SINGLE_CHAR);
python code to do that configuration is like this:
import pytesseract
import cv2
img = cv2.imread("path to some image")
pytesseract.image_to_string(
img, config=("-c tessedit"
"_char_whitelist=abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
" --psm 10"
" -l osd"
" "))
the --psm
flag defines the page segmentation mode.
according to documentaion of tesseract, 10
means :
Treat the image as a single character.
so to recognize a single character you just need to use : --psm 10
flag.
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