Question

我有对一个tiff文件执行OCR并在python窗口中打印结果的python代码。我的目录中的tiff文件数量更多，使用我的代码对所有图像进行OCR一次将花费更多的时间。

由于我是初学者，因此在代码中添加“ for”循环时遇到错误

import cv2
import numpy as np
import pytesseract
from PIL import Image

# Path of working folder on Disk
src_path = "D:/OpenCV and Tesseract/Image Split/Test 1/"

def get_string(img_path):
    # Read image with opencv
    img = cv2.imread(img_path)

    # Convert to gray
    img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # Apply dilation and erosion to remove some noise
    kernel = np.ones((1, 1), np.uint8)
    img = cv2.dilate(img, kernel, iterations=1)
    img = cv2.erode(img, kernel, iterations=1)

    # Write image after removed noise
    cv2.imwrite(src_path + "removed_noise.png", img)

    #  Apply threshold to get image with only black and white
    #img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)

    # Write the image after apply opencv to do some ...
    cv2.imwrite(src_path + "thres.png", img)

    # Recognize text with tesseract for python
    result = pytesseract.image_to_string(Image.open(src_path + "thres.png"))

    # Remove template file
    #os.remove(temp)

    return result


print '--- Start recognize text from image ---'
print get_string(src_path + "21.tif")

print "------ Done -------"

有人帮助我修改python代码以对目录中的所有图像进行OCR，并将所有文本逐行存储在单个.txt文件中

OCR目录中的所有.tif图像

0 个答案: