import easyocr
import cv2 as cv
import keras_ocr
import pytesseract

def keras_ocr_func():
    pipeline = keras_ocr.pipeline.Pipeline()
    images = [
        keras_ocr.tools.read(img) for img in ['img0.png', ]
    ]
    prediction_groups = pipeline.recognize(images)
    car_numbers = ''

    try:
        for i in prediction_groups[0]:
            car_numbers += i[0]
    except:
        print('no detection')

    return car_numbers

def tesseract_ocr():
    img = cv.imread('img0.png')
    res = pytesseract.image_to_string(img,
                                      lang='eng',
                                      config='--oem 3 --psm 6 -c tessedit_char_whitelist=ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789')
    return res

def get_text_from_image(img_path, cut=7):
    text = ''
    image = cv.imread(img_path)


    reader = easyocr.Reader(['en'])
    ocr_result = reader.readtext((image), paragraph="True", min_size=120, #180 for rgb
                             allowlist='0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ')
    try:
        text=ocr_result[0][1].replace(' ', '')[:cut] # cut to 7 symbols
    except:
        print('too few symbols')

    return text