Installing and using any trainer for tesseract
I was searching for a solution to train my tesseract and create a language file, now for 3 months, am not a professional programmer so am trying to learn, I need it to build an automatic solution for a project I have, but I didn't found any tutor video or any topic about installing any train extension or software and use , am using spider and python 3 , and have download qt,tests and other but how to use.
I need tutor any documentary can help, like box creating, export and test my file as language.
You can use JTessBoxEditor.
1)Provide the image
2)Generate boxes
3)Train your tesseract with generated boxes.
These are the steps.
Also you can train using txt file. Here is tutorial about it.
https://www.youtube.com/watch?v=i_1-hGsXxy8
Related
I'm using Matterport's free scanning software for Android and it spits out 2 files called 2b7cb66c-4c9e-408d-88c5-90b8c0322c13_sweep_features.pb and 2b7cb66c-4c9e-408d-88c5-90b8c0322c13_sweep_cloud.pb (the important thing is that they're of the forms [nums]_sweep_features.pb and [nums]_sweep_cloud.pb).
:^)
How can I open .pb files?
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My ultimate goal: the room in VR
I need to know how to open the file so I can walk around the rooms I scan in my Meta Quest 2 VR Headset. Ideally, I'd get it working in Unity, but UnrealEngine would be fine too. The most important thing is that I get the numerical and/or color information about the scanned room. Besides sweep_cloud.pb, there is also a file called sweep_features.pb.
Maybe .pb is a Tensorflow format? I say that because most of the .pb files I have found through Google for are Protocol Buffers, many of which store Neural Network (Tensorflow) files, and "feature" is jargon in Neural Networks and Machine Learning more generally!
Another guess would be something like a .obj file, a numpy (.npy) file or other point cloud format that probably has some color information in it!
Thanks!
I want to enter large amount of data in twincat3 as an array.
I have 6000*2 matrix(one column as time and other one is value corresponding of function).
I read this link of Beckhoff but it was a bit hazy for me. I'm looking for a simple example of how to load and use excel data in twincat3.
any help would be appreciated.
The link you included references the TF6429 Connectivity module. Here's a link to the documentation for that module. The specifics are in the documentation. As an FYI - the minimum steps you'll need to take are:
Download that module
Add it as a new TwinCat Connectivity project to your solution.
Add your excel sheet as a database connection.
Refer to chapter 6 of the documentation for PLC API instructions.
Best of luck!
I am trying to perform OCR with tesseract. I can do pdf to text using tesseract java lib as expected. My requirements is extended a bit now. I need to extract metadata based on template form (kind of passport example where we have fix place for first name, date of birth etc). Input could be either pdf or image with same template form.
I am facing hard time to find any such example or article to achieve or to get further help above using tesseract.
So my basic questions :
Is this possible using tesseract?
Is there any example/articles about how to achieve this using tesseract?
Is there any other software/library which is recommended to achieve this?
Thanks for reading this.
I was wondering if anybody knows of an API, toolbox, or library that extracts layers from an image format that is supported by a free editor such as Paint.NET (native format: .pdn)
Motivation: An interface to an image with layers that can be edited in a free image editor would be of interest for those of us who do computer vision and machine learning in MATLAB. For example, it could facilitate the automatic collection of manual pixel annotations for supervised learning.
I suggest using the .PSD Photoshop file format, which has layers support and is also implemented by many non-Adobe applications.
The PSD plugin for Paint.NET allows you to open and save PSD images: http://www.psdplugin.com/
You can then use Imagemagick to extract the layers to a format that MATLAB can read:
convert filename.psd filename-%d.png
Almost nothing can read a .pdn file. http://extension.nirsoft.net/pdn
So, you are left with the following options.
Use GIMP to read in the file, and export it into something matlab supports: http://www.mathworks.com/help/techdoc/ref/imread.html.
Use GIMP to read in the file, and export it into something ImageMagick supports:http://www.imagemagick.org/script/formats.php and then convert it into something matlab supports.
Export the data from Paint.NET into a matlab friendly format.
Note, the Matlab links are for the image processing toolbox, if you don't have that, the options are more limited.
I am trying to create an iPhone game with fairly large levels. Hard coding the platforms and physics objects is very time consuming. I have seen some people have made their own parsers for svg files to use in box2D, and Riq is selling levelSVG but it is a little pricey for me at the moment, and I only need basic features. Is there a tutorial on how to code a parser available online?
Have you taken a look at SVGQuartzRenderer? It is designed to render SVG files in Quartz, so I imagine you might be able to pull out the SVG parsing code from this. It's opensource, MIT license.
I don't know about any tutorials but its fairly easy to do this using an XML parsing library. In my project I use MiniDOM to load an svg file and then I convert the elements into objects in the box2d word. The only thing that I had to do manually was the parsing of the path element.
I've written an extensive tutorial on how to parse SVG files using Apache Batik SVG library. Included with the tutorial are a set of classes and a function I wrote in Java which will generate a set of Vec2 points given the location of the SVG file. If you're using Objective C you could try to port the scripts or at least get an idea of the process involved. The scripts support multiple paths per SVG file, transformations, straight lines and quadratic splines. The first tutorial in the series can be found here.