是否可以使用Tesseract OCR识别iPhone屏幕上绘制的角色?

时间:2023-02-02 09:02:27

From the past 2 weeks i am trying to implement "Recognize the character drawn on iPhone screen".
i Search for this and i found Tesseract OCR.

从过去2周开始,我正在努力实现“识别iPhone屏幕上绘制的角色”。我搜索这个,我找到了Tesseract OCR。

By using Tesseract OCR we are able to recognize characters from a picture.
Now my question is Is it possible to recognize the character drawn on iPhone screen using Tesseract OCR?

通过使用Tesseract OCR,我们能够识别图片中的字符。现在我的问题是,是否可以使用Tesseract OCR识别iPhone屏幕上绘制的角色?

if it Possible give me some initial steps to achieve this task.

如果可能,请给我一些初步步骤来完成这项任务。

1 个解决方案

#1


6  

Computer Vision is all about training. You need to create several hundred (maybe thousand) sample shots of what you might be trying to parse in order to train Tesseract to detect it. Once you think you have it trained enough, train more with new images. Then again withe even newer images. The more sample data the better. Once you have a trained AI, taking a screenshot of the users input is trivial, then pass it to Tesseract to parse. Be sure to include a "Help us train with this image" feature in your app in case you get it wrong, so you can train on real-time data from users.

计算机视觉就是培训。您需要创建几百个(可能是数千个)样本镜头来解析您可能要解析的内容,以便训练Tesseract检测它。一旦你认为你有足够的训练,就可以用新的图像训练更多。然后再用更新的图像。样本数据越多越好。一旦你有一个训练有素的人工智能,截取用户输入的屏幕截图是微不足道的,然后将其传递给Tesseract进行解析。请确保在您的应用中包含“帮助我们使用此图片进行培训”功能,以防您出错,这样您就可以使用来自用户的实时数据进行培训。

#1


6  

Computer Vision is all about training. You need to create several hundred (maybe thousand) sample shots of what you might be trying to parse in order to train Tesseract to detect it. Once you think you have it trained enough, train more with new images. Then again withe even newer images. The more sample data the better. Once you have a trained AI, taking a screenshot of the users input is trivial, then pass it to Tesseract to parse. Be sure to include a "Help us train with this image" feature in your app in case you get it wrong, so you can train on real-time data from users.

计算机视觉就是培训。您需要创建几百个(可能是数千个)样本镜头来解析您可能要解析的内容,以便训练Tesseract检测它。一旦你认为你有足够的训练,就可以用新的图像训练更多。然后再用更新的图像。样本数据越多越好。一旦你有一个训练有素的人工智能,截取用户输入的屏幕截图是微不足道的,然后将其传递给Tesseract进行解析。请确保在您的应用中包含“帮助我们使用此图片进行培训”功能,以防您出错,这样您就可以使用来自用户的实时数据进行培训。