使用 tesseract OCR、Python 从不同光照条件的图像中检测数字

发布于 2025-01-12 11:56:47 字数 1213 浏览 0 评论 0原文

该图像在不同光照条件下的问题：- Img_1

适用于今天早上的图片：- Img_2

我正在尝试使用 Tesseract OCR & 从视频中提取数字。 Python 。在该视频中，每列火车上都有一个可用的火车，并且有一个车牌号，我将使用 YOLO 检测到该车牌号。一旦我拿到盘子，我就会对其进行预处理&从板中提取 no。我能够提取它，但如果存在不同的光照条件或视频中有夜晚，那么我的预处理将无法正常工作。所以我想要一个通用逻辑来预处理图像，使其适用于所有图像，而不是某些图像。我附上了一些试用图片。在代码中，我仅手动提取了板的一部分，然后将其传递给 getText(image) 来执行预处理和处理。吗？

def getText(img):

    # color threshold
    thresh = otsu_thresholding(img)
    gray = get_grayscale(thresh)
    gray[gray != 0] = 255

    # second way
    thresh_2 = adaptive_thresholding(get_grayscale(img), method=1)
 
    cv2.imshow("img", img)
    cv2.imshow("Thresh", thresh)
    cv2.imshow("Thresh_2", thresh_2)
    cv2.imshow("Gray", gray)

    data = pytesseract.image_to_string(gray, lang='eng', config='--psm 6 -c tessedit_char_whitelist=0123456789')
    data_2 = pytesseract.image_to_string(thresh_2, lang='eng', config='--psm 6 -c tessedit_char_whitelist=0123456789')
    return data, data_2

任何人都可以帮我在将图像输入超立方体之前对其进行预处理

原文

the problem for this image with different light condition:-
Img_1

worked for this morning image:-
Img_2

I am trying to extract numbers from the video by using Tesseract OCR & Python . in that video, there is a train available on each train there is a number plate that I will be detected by using YOLO. once I got the plate I'm preprocessing it & extract no from the plate.
I am able to extract it but if there is a different light condition or there is night in the video then my preprocessing will not work properly. so I wanted a Genral purpose Logic to preprocess images in a such way that it'll work for all images, not for some.
I have attached some images for the trial.
in the CODE I have extracted only part of the plate manually then pass it to getText(image) to perform preprocessing & extract no

def getText(img):

    # color threshold
    thresh = otsu_thresholding(img)
    gray = get_grayscale(thresh)
    gray[gray != 0] = 255

    # second way
    thresh_2 = adaptive_thresholding(get_grayscale(img), method=1)
 
    cv2.imshow("img", img)
    cv2.imshow("Thresh", thresh)
    cv2.imshow("Thresh_2", thresh_2)
    cv2.imshow("Gray", gray)

    data = pytesseract.image_to_string(gray, lang='eng', config='--psm 6 -c tessedit_char_whitelist=0123456789')
    data_2 = pytesseract.image_to_string(thresh_2, lang='eng', config='--psm 6 -c tessedit_char_whitelist=0123456789')
    return data, data_2

Can anyone help me in pre-processing the images before feeding them to tesseract?

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