objects | React Hooks for Mutable State | Frontend Utils library

Vector3 position = point.position; makes a copy of point.position. The following code then updates this copy, which in turn is thrown away when it goes out of scope at the end of the if statement.

The solution is simple enough - use a reference instead: Vector3 &position = point.position;. The rest of the code can be left as-is.

If you're going to use the CompareOptions enum, I feel like you might as well use it with the CompareInfo class that it's documented as being designed for:

Defines the string comparison options to use with CompareInfo.

Then you can just use the GetHashCode(string, CompareOptions) method from that class (and even the Compare(string, string, CompareOptions) method if you like).

So, this is a good opportunity to use purrr::map. You are half way there by applying code to one dataframe.

You can take the code that you have written above and put it into a function.

A functional approach would be (but probably not clean)

I can't decipher what you're doing there, but:

Tesseract takes a lang variable that you can expand to include different languages if they're installed. I've used the UB Mannheim (https://github.com/UB-Mannheim/tesseract/wiki) installation which includes a ton of languages supported.

To get better and more accurate results, the best thing to do is to process the image before handing it to Tesseract. Set a white/black threshold so that you have black text on white background with no shading. I'm not sure how to do this in Node, but I've done it with Python's OpenCV library.

If that font doesn't get you decent results with the out of the box, then you'll want to train your own, yes. This blog post walks through the process in great detail: https://towardsdatascience.com/simple-ocr-with-tesseract-a4341e4564b6. It revolves around using the jTessBoxEditor to hand-label the objects detected in the images you're using.

Edit: In brief, the process to train your own:

1. Install jTessBoxEditor (https://sourceforge.net/projects/vietocr/files/jTessBoxEditor/). Requires Java Runtime installed as well.
2. Collect your training images. They want to be .tiffs. I found I got fairly accurate results with not a whole lot of images that had a good sample of all the characters I wanted to detect. Maybe 30/40 images. It's tedious, so you don't want to do TOO many, but need enough in order to get a good sampling.
3. Use jTessBoxEditor to merge all the images into a single .tiff
4. Create a training label file (.box)j. This is done with Tesseract itself. tesseract your_language.font.exp0.tif your_language.font.exp0 makebox
5. Now you can open the box file in jTessBoxEditor and you'll see how/where it detected the characters. Bounding boxes and what character it saw. The tedious part: Hand fix all the bounding boxes and characters to accurately represent what is in the images. Not joking, it's tedious. Slap some tv episodes up and just churn through it.
6. Train the tesseract model itself

• save a file: font_properties who's content is font 0 0 0 0 0
• run the following commands:

tesseract num.font.exp0.tif font_name.font.exp0 nobatch box.train

unicharset_extractor font_name.font.exp0.box

shapeclustering -F font_properties -U unicharset -O font_name.unicharset font_name.font.exp0.tr

mftraining -F font_properties -U unicharset -O font_name.unicharset font_name.font.exp0.tr

cntraining font_name.font.exp0.tr

You should, in there close to the end see some output that looks like this:

Master shape_table:Number of shapes = 10 max unichars = 1 number with multiple unichars = 0

That number of shapes should roughly be the number of characters present in all the image files you've provided.

If it went well, you should have 4 files created: inttemp normproto pffmtable shapetable. Rename them all with the prefix of your_language from before. So e.g. your_language.inttemp etc.

Then run:

combine_tessdata your_language

The file: your_language.traineddata is the model. Copy that into your Tesseract's data folder. On Windows, it'll be like: C:\Program Files x86\tesseract\4.0\tessdata and on Linux it's probably something like /usr/shared/tesseract/4.0/tessdata.

Then when you run Tesseract, you'll pass the lang=your_language. I found best results when I still passed an existing language as well, so like for my stuff it was still English I was grabbing, just funny fonts. So I still wanted the English as well, so I'd pass: lang=your_language+eng.

You mean to use map instead of forEach.

Although they 'don't exist', can Format.ps1xml files be created/used in versions of PowerShell greater than 5.1?

• Yes; in fact any third-party code must use them to define custom formatting.

  • That *.ps1xml files are invariably needed for such definitions is unfortunate; GitHub issue #7845 asks for an in-memory, API-based alternative (which for type data already exists, via the Update-TypeData cmdlet).

• It is only the formatting data that ships with PowerShell that is now hardcoded into the PowerShell (Core) executable, presumably for performance reasons.

is there some better practice for suggesting to PowerShell how a certain function should format returned data?

The lack of an API-based way to define formatting data requires the following approach:

• Determine the full name of the .NET type(s) to which the formatting should apply.

  • If it is [pscustomobject] instances that the formatting should apply to, you need to (a) choose a unique (virtual) type name and (b) assign it to the [pscustomobject] instances via PowerShell's ETS (Extended Type System); e.g.:

    • For [pscustomobject] instances created by the Select-Object cmdlet:

You should separate creating your menu from your content. Please review the following example. I decoupled your menu, component, and event logic into meaningful phases.