Mac 上使用 Tesseract OCR 识别图片文本

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:

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.sizeif 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_pathdef 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 textif __name__ == '__main__':get_text_from_picture('my_picture_path', crop_box=[585, 360, None, 800])