Mac 上使用 Tesseract OCR 识别图片文本-Toy模板网

这篇具有很好参考价值的文章主要介绍了Mac 上使用 Tesseract OCR 识别图片文本。希望对大家有所帮助。如果存在错误或未考虑完全的地方，请大家不吝赐教，您也可以点击"举报违法"按钮提交疑问。

Tesseract OCR 引擎：Tesseract是一个开源的OCR引擎，你需要先安装它。可以从Tesseract官方网站（https://github.com/tesseract-ocr/tesseract）下载适用于你的操作系统的安装程序或源代码，并按照官方文档进行安装。

Tesseract OCR 对于低分辨率或模糊的图片可能无法准确识别。尝试使用更高分辨率和清晰度的图片来提高识别结果的准确性。对于 Mac 上的截图，一般都是很清晰的，所以这个缺点影响不大。

在 Mac 上，使用官网推荐的方式安装：

brew install tesseract

The tesseract directory can then be found using brew info tesseract, e.g.

/usr/local/Cellar/tesseract/5.3.2/bin/tesseract

demo:文章来源地址https://www.toymoban.com/news/detail-608929.html

import pytesseract
from PIL import Image

# 可以写一个函数 crop_picture 将原图裁剪一下，只保留想要识别文本的部分，这样识别更加准确一些。
def crop_picture(picture_path, crop_box: list):
    """
    crap picture with crop_box
    :param picture_path: picture to be crapped
    :param crop_box: crop region, eg: [100, 200, 300, 350]
    :return: path of crapped picture
    """
    dirname = os.path.dirname(picture_path)
    basename = os.path.basename(picture_path)
    new_basename = ''.join([basename.split('.')[0], '_new.', basename.split('.')[1]])

    picture_origin = Image.open(picture_path)
    picture_origin_size = picture_origin.size
    if crop_box[2] is None:
        crop_box[2] = picture_origin_size[0]
    if crop_box[3] is None:
        crop_box[3] = picture_origin_size[1]
    picture_new = picture_origin.crop(tuple(crop_box))

    picture_new_path = os.path.join(dirname, new_basename)
    picture_new.save(picture_new_path)
    return picture_new_path

def get_text_from_picture(picture_path, crop_box: list):
    """
    get text from picture
    :param picture_path: picture to be crapped
    :param crop_box: crop region, eg: [100, 200, 300, 350]
    :return: text
    """
    pytesseract.pytesseract.tesseract_cmd = r'/usr/local/Cellar/tesseract/5.3.2/bin/tesseract'
    picture_new_path = crop_picture(picture_path, crop_box=crop_box)
    image = Image.open(picture_new_path)
    text = pytesseract.image_to_string(image, lang='eng')
    print(text)
    return text

if __name__ == '__main__':
    get_text_from_picture('my_picture_path', crop_box=[585, 360, None, 800])