43 lines
1.1 KiB
Python
43 lines
1.1 KiB
Python
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import easyocr
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import cv2 as cv
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import keras_ocr
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import pytesseract
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def keras_ocr_func():
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pipeline = keras_ocr.pipeline.Pipeline()
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images = [
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keras_ocr.tools.read(img) for img in ['img0.png', ]
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]
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prediction_groups = pipeline.recognize(images)
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car_numbers = ''
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try:
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for i in prediction_groups[0]:
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car_numbers += i[0]
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except:
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print('no detection')
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return car_numbers
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def tesseract_ocr():
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img = cv.imread('img0.png')
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res = pytesseract.image_to_string(img,
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lang='eng',
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config='--oem 3 --psm 6 -c tessedit_char_whitelist=ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789')
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return res
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def get_text_from_image(img_path, cut=7):
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text = ''
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image = cv.imread(img_path)
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reader = easyocr.Reader(['en'])
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ocr_result = reader.readtext((image), paragraph="True", min_size=120, #180 for rgb
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allowlist='0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ')
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try:
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text=ocr_result[0][1].replace(' ', '')[:cut] # cut to 7 symbols
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except:
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print('too few symbols')
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return text
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