Mac 上使用 Tesseract OCR 识别图片文本
短信预约 -IT技能 免费直播动态提醒
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 pytesseractfrom 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_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])
来源地址:https://blog.csdn.net/qq_31362767/article/details/131943091
免责声明:
① 本站未注明“稿件来源”的信息均来自网络整理。其文字、图片和音视频稿件的所属权归原作者所有。本站收集整理出于非商业性的教育和科研之目的,并不意味着本站赞同其观点或证实其内容的真实性。仅作为临时的测试数据,供内部测试之用。本站并未授权任何人以任何方式主动获取本站任何信息。
② 本站未注明“稿件来源”的临时测试数据将在测试完成后最终做删除处理。有问题或投稿请发送至: 邮箱/279061341@qq.com QQ/279061341