Quantrium指南 (Quantrium Guides)

In this guide, I will take you through the steps that I followed in order to train Tesseract using the Qt Box Editor and improved its prediction on certain types of images in which it was performing poorly. Before we begin, these are some of the tools I had at my disposal, and if you want to execute everything in this tutorial without any error, I would suggest you to have the same:

在本指南中，我将带您逐步执行以下步骤，以使用Qt Box Editor训练Tesseract ，并改进其对某些表现不佳的图像的预测。 在开始之前，这些是我可以使用的一些工具，如果您想无误地执行本教程中的所有内容，建议您使用相同的工具：

• A Windows 10 PC with Tesseract installed安装了Tesseract的Windows 10 PC
• A Google cloud computing services account , with a Google compute engine instance with an Ubuntu 18.04.4 OS that you can SSH into一个Google云计算服务帐户，具有一个Google计算引擎实例和一个Ubuntu 18.04.4 OS，您可以通过SSH将该实例登录

If you haven’t already installed Tesseract on your windows 10 system, check out my other post on Medium titled “Installing and using Tesseract 4 on windows 10" where I help you with the process.

如果您尚未在Windows 10系统上安装Tesseract，请查看我在“ Medium ”上的另一篇文章“ 在Windows 10上安装和使用Tesseract 4 ” ，我将为您提供帮助。

在Windows 10上使用QT Box Editor编辑Tesseract Box文件 (Using QT Box Editor on Windows 10 to Edit Tesseract Box Files)

Now to train Tesseract on images in which it is doing poorly, we need to train it using something known as a box file. A box file is basically a type of file that Tesseract generates, where we can see how Tesseract made its predictions character by character and where it detected those characters.

现在要在Tesseract表现不佳的图像上进行训练，我们需要使用称为Box文件的东西对其进行训练。 盒子文件基本上是Tesseract生成的一种文件，在这里我们可以看到Tesseract如何逐个字符地进行预测以及在哪里检测到这些字符。

In these files, boxes are drawn around what Tesseract thinks are characters and tells us what it thinks is most likely the character inside that box. So we train Tesseract by editing these box files and telling where it has gone wrong. But before editing them, we need to generate these box files first. But before I tell you how to generate them, you need to do something. Make sure that the names of all the images that you are going to use for training your image follow the following format:

在这些文件中，在Tesseract认为是字符的位置周围绘制了框，并告诉我们它认为最有可能是该框中的字符的位置。 因此，我们通过编辑这些Box文件并告诉它出了问题的地方来训练Tesseract。 但是在编辑它们之前，我们需要先生成这些盒子文件。 但是在我告诉您如何生成它们之前，您需要做一些事情。 确保要用于训练图像的所有图像的名称遵循以下格式：

<language name>.<fontname>.exp<file number>

For example, if your images are all English in the Arial font, and you want to train tesseract using 5 images, make sure your files have the name format:

例如，如果您的图像全部是Arial字体的英语，并且您想使用5张图像来训练tesseract ，请确保文件具有名称格式：

eng.arial.exp0eng.arial.exp1eng.arial.exp2eng.arial.exp3eng.arial.exp4

Now, we are ready to generate the box file for each of your image. The box files for all your images can be obtained by using the following command for each image:

现在，我们准备为您的每个图像生成盒子文件。 可以通过对每个图像使用以下命令来获取所有图像的文件夹文件：

tesseract -l eng eng.arial.exp0.jpg eng.arial.exp0 batch.nochop makebox

Run this command for all your images. The only thing that will change in each image will be in the .exp0 part. For your second image the command will be:

对所有图像运行此命令。 每个图像中唯一会改变的是.exp0部分。 对于第二张图片，命令将为：

tesseract -l eng eng.arial.exp1.jpg eng.arial.exp1 batch.nochop makebox

For third image:

对于第三张图片：

tesseract -l eng eng.arial.exp2.jpg eng.arial.exp2 batch.nochop makebox

and so on.

等等。

Each box file will be generated in the present working directory. Make sure that all the images and the box file their corresponding box files are all in the same directory. This is important.

每个文件夹文件都将在当前工作目录中生成。 确保所有图像和文件夹文件及其对应的文件夹文件都在同一目录中。 这个很重要。

Now to edit these box files, we will need a new software called the Qt Box editor. Which can be downloaded from the following url:

现在要编辑这些Box文件，我们需要一个名为Qt Box Editor的新软件。 可以从以下网址下载：

I downloaded the “qt-box-editor-1.12rc1b-portable.zip” for my windows 64 system. After downloading the zip file, extract all the contents in the zip file to wherever you have storage space. The extracted contents will contain an exe file called “ qt-box-editor-1.12rc1.exe” and run it.

我为Windows 64系统下载了“ qt-box-editor-1.12rc1b-portable.zip”。 下载zip文件后，将zip文件中的所有内容提取到有存储空间的任何位置。 提取的内容将包含一个名为“ qt-box-editor-1.12rc1.exe”的exe文件并运行它。

Before opening any image, go to “edit”, click on “settings”, then click on the tesseract section and make sure that the directory specified in “TESSDATA_PREFIX” is the original directory where you installed Tesseract-OCR. For me, it was C:/ProgramFiles/Tesseract-OCR/.

打开任何图像之前，请转到“编辑”，单击“设置”，然后单击tesseract部分，并确保“ TESSDATA_PREFIX”中指定的目录是您安装Tesseract-OCR的原始目录。 对我而言，它是C:/ProgramFiles/Tesseract-OCR/ 。

In the language section, select the language that your handwritten images are written in . For me it was English. Click OK after selecting the language. Now just for verification, close the application, open it again and check to see if the “TESSDATA_PREFIX” and “Language” section have changed to the appropriate results as mentioned above.

在语言部分中，选择手写图像所用的语言。 对我来说是英语。 选择语言后，单击“确定”。 现在仅用于验证，请关闭应用程序，然后再次打开它，并检查“ TESSDATA_PREFIX”和“语言”部分是否已更改为如上所述的适当结果。

This software is a little buggy, so you might have to do the procedure specified above a few times before everything is in order.

该软件有点漏洞，因此您可能必须先完成上面指定的过程，然后才能进行所有操作。

Now, you want to open each image and edit it. Note that, here, you want to open the image and not the box files themselves. To open an image using the app, click on File in the top left and hit open. Now you can select the photo whose box file you have already generated and seen. You can see some boxes around each text and the predicted output in each box on the left side. You should see something like this:

现在，您要打开每个图像并进行编辑。 请注意，在这里，您要打开图像而不是框文件本身。 要使用该应用打开图片，请点击左上角的文件，然后点击打开。 现在，您可以选择已经生成并看到其框文件的照片。 您可以在每个文本周围看到一些方框，并在左侧的每个方框中看到预测的输出。 您应该会看到以下内容：

The red box highlighted here are the predictions made by Tesseract and the boxes corresponding to where tesseract thinks each of these characters appear. You can edit the boxes by clicking on each letter and extra boxes can be added by clicking on the plus button on the bottom left.

此处突出显示的红色框是Tesseract所作的预测，以及与tesseract认为每个字符出现的位置相对应的框。 您可以通过单击每个字母来编辑框，还可以通过单击左下方的加号按钮来添加其他框。

If you don’t see this highlighted box and only the image is opened, then you have made some mistake somewhere. Either your tesseract directory is not mentioned properly in the Qt box editor or your file name for each image is not specified like how I asked you too, or your box files haven’t been generated properly. See which one of these is wrong and fix it. Once you have edited the box files for all the images, you are now ready to start training.

如果您没有看到此突出显示的框，而仅打开了图像，则说明您在某个地方犯了一些错误。 Qt框编辑器中未正确提及您的tesseract目录，或者未按我的要求指定每个图像的文件名，或者框文件未正确生成。 看看其中哪一个是错误的，并加以解决。 编辑完所有图像的框文件后，就可以开始训练了。

在Ubuntu 18.04上的Box文件上训练Tesseract： (Training Tesseract on the Box Files on Ubuntu 18.04:)

We shall be using the script in the following tutorial to train our Tesseract:

我们将在以下教程中使用脚本来训练我们的Tesseract：

We are going to use a script in this article in a section called “Time to train Tesseract to recognize letters properly”, and modify it to our needs.

我们将在本文的“训练Tesseract正确识别字母的时间”部分中使用脚本，并根据需要进行修改。

Well you can write this script in your Ubuntu system in the cloud directly itself and then execute it, but I suggest you copy this script onto something like Notepad++ in your windows system, where you can write bash files in windows and try to modify it according to your needs. This will be easier to do since writing and editing scripts directly from the command line is a little difficult if you haven’t done it before but of course you can do so if you wish.

好吧，您可以直接在云中的Ubuntu系统中直接编写此脚本，然后执行它，但是我建议您将该脚本复制到Windows系统中的Notepad ++之类的文件中，在其中您可以在Windows中编写bash文件并尝试根据以下内容进行修改满足您的需求。 这将更容易实现，因为如果您以前从未这样做过，那么直接从命令行编写和编辑脚本会有些困难，但是当然您也可以这样做。

Once you paste this onto Notepad++, go to edit, then to “EOL Conversion” and click on Unix. If you don’t do this, then your Ubuntu system won’t understand the spaces and newlines in the script and won’t execute your file.

将其粘贴到Notepad ++上后，进行编辑，然后进行“ EOL Conversion”，然后单击Unix。 如果不这样做，那么您的Ubuntu系统将无法理解脚本中的空格和换行符，也不会执行文件。

Now before you hit save, modify this file according to your needs. First, change the N in the seventh line to your needs, if you are going to train tesseract on 7 images, make sure N is 6 or if you have 20 images make sure N is 19 and so on. Then in the 10th line, that is commented, just turn every pol. into eng. if your handwritten documents are in English, jpn, if they are in Japanese and so on.

现在，在单击保存之前，请根据需要修改此文件。 首先，根据需要更改第七行中的N，如果要在7张图像上训练tesseract，请确保N为6，或者如果您有20张图像，请确保N为19，依此类推。 然后在第10行，即已注释，只需转动每个pol。 进入英语。 如果您的手写文件是英文，jpn，如果是日文等等。

You don’t have to un-comment this line now, but if you rerun this script, you have to un-comment this line and then run the script.

您不必现在取消注释该行，但是如果您重新运行此脚本，则必须取消注释此行，然后运行脚本。

Now the Tesseract is trained on the images provided in png format in English language with the Vivaldi font so we have to change the line number 13 from pol.ocrb.exp$i.tif to eng.vivaldi.exp$i.png and similarly we have to changepol.ocrb.exp$i to eng.vivaldi.exp$i in the same line. You should change it according to your format/needs.

现在，Tesseract已接受使用Vivaldi字体以英语提供的以png格式提供的图像的训练，因此我们必须将行号13从pol.ocrb.exp$i.tif为eng.vivaldi.exp$i.png并进行类似的操作我们必须将pol.ocrb.exp$i更改为 eng.vivaldi.exp$i在同一行中。 您应该根据自己的格式/需求对其进行更改。

Similarly, pol.ocrb.exp on line 15th is required to be changed to eng.vivaldi.exp. In the 16th line, change the ocrb to the font your document and modify the numbers depending on your font.

同样， pol.ocrb.exp 需要将第15行的内容更改为eng.vivaldi.exp 。 在第16行中，将ocrb更改为文档的字体，然后根据您的字体修改数字。

The font used for images in this guide was Vivaldi so I changed ocrb 0 0 1 0 0 to vivaldi 1 0 0 0 0 since my font, Vivaldi, was Italics only and was not in bold or monospace or serif or fraktur.

本指南中用于图像的字体为Vivaldi，因此我将ocrb 0 0 1 0 0更改为vivaldi 1 0 0 0 0 因为我的字体Vivaldi仅是斜体，而不是粗体，等宽字体，衬线或fraktur。

Similarly in 17th line, in the last part I had to change pol.ocrb.exp to eng.vivaldi.exp. And in 18th line, I changed pol.ocrb.exp to eng.vivaldi.exp. In line numbers 20th, 21st, 22nd and 23rd, I modified pol.inttemp, pol.normproto, pol.pffmtable, pol.shapetable to eng.inttemp, eng.normproto, eng.pffmtable and eng.shapetable respectively.

同样在第17行中，在最后一部分中，我不得不更改pol.ocrb.exp 至 eng.vivaldi.exp 。 在第18行中，我将pol.ocrb.exp更改为eng.vivaldi.exp 。 在第pol.inttemp和23行中，我修改了pol.inttemp ， pol.normproto ， pol.pffmtable ， pol.shapetable 至 eng.inttemp ， eng.normproto ， eng.pffmtable和eng.shapetable 分别。

In 24th and final line, change the line depending on your language. Since all my text is in English, I write combine_tessdata eng.. If you use Japanese, make it combine_tessdata jpn. and so on.

在第24行(也是最后一行)中，根据您的语言更改行。 由于我所有的文字都是英文，所以我写了combine_tessdata eng. 。 如果使用日语，请将其设置为combine_tessdata jpn. 等等。

As already mentioned a few times before, you need to make changes according your specifications. All the necessary modifications that are required to be made in the script are completed, so now we are ready to save this file. But, when saving, right before you hit save, you will see this option called “Save as type” that you can change. Click on that and select the save type as “Unix script type”. Name the file whatever you want, I named it “train” and save it.

如前所述，您需要根据自己的规范进行更改。 脚本中需要进行的所有必要修改都已完成，因此现在我们可以保存该文件。 但是，在保存时，在单击“保存”之前，您将看到一个可以更改的名为“ 另存为类型 ”的选项。 单击该按钮，然后将保存类型选择为“ Unix脚本类型 ”。 随便命名文件，我都将其命名为“ train ”并保存。

So far so good! Everything you need to configure on your windows system is completed. Now, go to

到目前为止，一切都很好！ 您在Windows系统上需要配置的所有内容均已完成。 现在，去

Login using your Google Cloud id and create a Compute Engine Instance with Ubuntu 18.04.4 LTS. Once you have created the Compute Engine instance, SSH into it.

使用您的Google Cloud ID登录并使用Ubuntu 18.04.4 LTS创建Compute Engine实例。 创建Compute Engine实例后，请通过SSH进入该实例。

Upload the following files from your windows system onto the cloud instance:

将以下文件从Windows系统上载到云实例：

• All the images that you want to train Tesseract on, and its edited box files.您要在其上训练Tesseract的所有图像及其编辑的框文件。

• The Unix script file that you created in the end which I called “train”.

  最后您创建的Unix脚本文件，我称之为“ train ”。

Once the upload is completed, you need to install Tesseract and its training tools onto this Ubuntu machine. You can do that using the the following commands:

上传完成后，您需要在此Ubuntu计算机上安装Tesseract及其培训工具。 您可以使用以下命令来执行此操作：

sudo apt install tesseract-ocrsudo apt install libtesseract-dev

That’s it. You have installed all the tools needed to train Tesseract. Now let’s check the version of our Tesseract and see if it’s installed properly and runs properly.

而已。 您已经安装了训练Tesseract所需的所有工具。 现在，让我们检查Tesseract的版本，看看它是否已正确安装并正常运行。

tesseract — version

You should see an output similar to the one you saw when you typed the same command in the windows system.

您应该看到类似于在Windows系统中键入相同命令时看到的输出。

Now you do not know where Tesseract and all its libraries have been installed. To find it let’s use the following command:

现在您不知道Tesseract及其所有库的安装位置。 要找到它，我们使用以下命令：

sudo find / -name "tessdata" 

This should give you the directory where tessdata is located. For me it’s /usr/share/tesseract-ocr/4.00/tessdata. “tessdata” is the folder where Tesseract stores all its training data on the various languages it has been trained on. Remember this folder, you will need to use this folder later.

这应该给您tessdata所在的目录。 对我来说是/usr/share/tesseract-ocr/4.00/tessdata 。 “ tessdata ”是Tesseract在其中存储所有培训数据的各种培训资料的文件夹。 记住该文件夹，以后您将需要使用此文件夹。

Now go back to your home directory using the command:

现在，使用以下命令返回您的home目录：

cd /home/<username>

Since this is the directory where all your uploaded files reside. Make sure all your files: images, box files and script file are in this folder. Now you just need to run the script file. Do this by executing the following two commands in sequence:

因为这是所有上载文件所在的目录。 确保所有文件： 图像 ， 框文件和脚本文件都在此文件夹中。 现在，您只需要运行脚本文件。 通过依次执行以下两个命令来执行此操作：

chmod +x train./train

Here train is the name of my script file. If your script file is called something else, put that name in place of the “train” in both the lines. Once the script has been executed successfully. Hit the ls command to check that files in your present working directory.

这里train是我的脚本文件的名称。 如果您的脚本文件被称为其他名称，请在两行中将该名称替换为“ train ”。 脚本成功执行后。 点击ls命令，检查当前工作目录中的文件。

You will see an extra .tr file for every image file that you used for training as well as six other files called eng.inttemp, eng.normproto, eng.pffmtable, eng.shapetable, eng.unicharset and finally, eng.traineddata. Of course the prefix eng. will change depending on the language in the text.

您将为用于训练的每个图像文件看到一个额外的.tr文件，以及其他六个文件， eng.normproto eng.inttemp ， eng.normproto ， eng.pffmtable ， eng.shapetable ， eng.unicharset和eng.traineddata 。 当然前缀eng. 会根据文本中的语言而变化。

If you don’t see these six files, you have made some error. Go back and check where you made one. It’s highly likely that your script may have some mistake. Try to find and fix it.

如果看不到这六个文件，则说明您犯了一些错误。 返回并检查您的位置。 您的脚本很可能有一些错误。 尝试查找并修复它。

Now, this eng.traineddata file is what you have been trying to create. This is your trained Tesseract file. Its basically has all the data about the mistakes Tesseract made in your images and your corrections. Now, you want to move this file to the tessdata folder.

现在，您一直在尝试创建这个eng.traineddata文件。 这是您训练有素的Tesseract文件。 它基本上具有有关Tesseract在图像中所做的错误和校正的所有数据。 现在，您想将此文件移动到tessdata文件夹。

However, tessdata already has a file called eng.traineddata that has information of thousands of images in the English language and it is the language file that Tesseract uses to detect text in the English language in your images.

但是， tessdata已经有一个名为eng.traineddata的文件，该文件具有成千上万个使用英语的图像信息，这是Tesseract用于检测图像中英语文本的语言文件。

Here, you want to add more capability to your Tesseract and hence you do not have to remove or overwrite this file. So, while moving your eng.traineddata file you should rename it to eng1.traineddata using the following command:

在这里，您想为Tesseract添加更多功能，因此不必删除或覆盖此文件。 因此，在移动eng.traineddata文件时，应使用以下命令将其重命名为eng1.traineddata ：

mv eng.traineddata /usr/share/tesseract-ocr/4.00/tessdata/eng1.traineddata

Here, mv stands for move but it can also be used for renaming files while moving. Here the directory name entered after eng.traineddata in the above command is where your tessdata folder is located.

在这里， mv代表移动，但也可以用于移动时重命名文件。 在此之后，进入目录名eng.traineddata在上面的命令是你tessdata文件夹的位置。

Congratulations, your training of tesseract is now complete. Now use Tesseract with your custom training, type the following command to try it out:

恭喜，您对tesseract的训练现已完成。 现在将Tesseract与您的自定义培训一起使用，键入以下命令进行尝试：

tesseract eng.vivaldi.exp0.png stdout -l eng1

Remember to specify the language as eng1. It refers to your trained Tesseract data file and will be used to predict the characters in the image.

请记住将语言指定为eng1 。 它指的是您训练有素的Tesseract数据文件，将用于预测图像中的字符。

You should train Tesseract only when its making poor predictions in your specific use case. For example, when you are using Tesseract to detect text in some very obscure font. In my case I was making predictions on the Vivaldi font which is an italics font and Tesseract performs very poorly.

仅当在您的特定用例中对Tesseract做出不良预测时，您才应该对其进行培训。 例如，当您使用Tesseract来检测某些非常模糊的字体的文本时。 就我而言，我正在对Vivaldi字体(一种斜体字体)进行预测，而Tesseract的表现非常差。

Hope you find this guide helpful to train Tesseract specifically for your use case and font type. I hope you will be successful in following and implementing this guide.

希望本指南对您针对用例和字体类型的Tesseract培训有所帮助。 希望您能够成功遵循并实施本指南。