使用 Tesseract OCR 正确从图像中提取文本

Question

我一直在尝试从该图像中提取粗体白色文本，但无法使其正常工作，似乎 9 被读作 3，而 I 被读作 1。

一直在查看各种网站，这些网站都有代码可以提高图像质量，但无法使其正常工作，任何人都可以帮助我解决这个问题吗？所需的输出应该是“I6M-9U”

def get_text_from_image(image: cv2.Mat) -> str:
    pytesseract.pytesseract.tesseract_cmd = r'C:\Tesseract-OCR\tesseract.exe'
    
    # Crop image to only get the piece I am interested in
    top, left, height, width = 25, 170, 40, 250

    try:
        crop_img = image[top:top + height, left:left + width]
        
        # Make it bigger
        resize_scaling = 1500
        resize_width = int(crop_img.shape[1] * resize_scaling / 100)
        resize_height = int(crop_img.shape[0] * resize_scaling / 100)
        resized_dimensions = (resize_width, resize_height)
    
        # Resize it
        crop_img = cv2.resize(crop_img, resized_dimensions, interpolation=cv2.INTER_CUBIC)
        
        return str(pytesseract.image_to_string(crop_img, config="--psm 6"))

更新代码

ret, thresh1 = cv.threshold(image, 120, 255, cv.THRESH_BINARY +
                                            cv.THRESH_OTSU)

cv.imshow("image", thresh1)

现在已删除所有背景伪影，但现在将第一个字母 I 读取为 1，将 9 读取为 3

Answer 1

对于我来说，I 看起来像是 1。如果您不喜欢 1，请将其从过滤器中删除：

import cv2
import pytesseract
 
img = cv2.imread('16M.png',cv2.IMREAD_UNCHANGED)

(thresh, blackAndWhiteImage) = cv2.threshold(img, 63, 255, cv2.THRESH_BINARY) 

# resize image
scale_percent = 4 # percent of original size
width = int(blackAndWhiteImage.shape[1] * scale_percent / 100)
height = int(blackAndWhiteImage.shape[0] * scale_percent / 100)
dim = (width, height)
resized = cv2.resize(blackAndWhiteImage, dim, interpolation = cv2.INTER_AREA)

# OCR resized Black & White image
pytesseract.pytesseract.tesseract_cmd=r'C:\Program Files\Tesseract-OCR\tesseract.exe'
# Remove 1 from filter, than you will get I instead
custom_config = r'--psm 6 --oem 3 -c tessedit_char_whitelist=-.ABCDEFTGHIJKLMNOPQRSTUVWXYZ0123456789' 

tex = pytesseract.image_to_string(resized, config=custom_config)
print(tex)

# Display cropped image
cv2.imshow("Image", resized)
 
cv2.waitKey(0)
cv2.destroyAllWindows()

输出：

16M-9U-0.0

从过滤器中删除“1”：

I6M-9U-0.0