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Solution:

1. Open the folder in VS Code
2. Collapse the Java Projects Tab in the Explorer menu (make sure you have the [java language package extension][3] downloaded)
3. Click the three dots icon '...' which appears when you hover over the Java Projects area with your mouse.
4. Select 'Configure Java Runtime'. A new tab will open.
5. On the Java Version column, select the pencil icon.
6. Open the dropdown menu and select a Java Version from the Java Virtual Machines folder instead of opt/Homebrew directories (it may be the same JDK from Homebrew using an alias, but VS Code expects the Virtual Machine folder and that is my theory in why this works).

The task, as you have seen, is not trivial at all. OpenCV has a segmentation algorithm called "GrabCut" that tries to solve this particular problem. The algorithm is pretty good at classifying background and foreground pixels, however it needs very specific information to work. It can operate on two modes:

• 1st Mode (Mask Mode): Using a Binary Mask (same size as the original input) where 100% definite background pixels are marked, as well as 100% definite foreground pixels. You don't have to mark every pixel on the image, just a region where you are sure the algorithm will find either class of pixels.

• 2nd Mode (Foreground ROI): Using a bounding box that encloses 100% definite foreground pixels.

Now, I use the notation "100% definitive" to label those pixels you are 100% sure they correspond to either the background of foreground. The algorithm classifies the pixels in four possible classes: "Definite Background", "Probable Background", "Definite Foreground" and "Probable Foreground". It will predict both Probable Background and Probable Foreground pixels, but it needs a priori information of where to find at least "Definitive Foreground" pixels.

With that said, we can use GrabCut in its 2nd mode (Rectangle ROI) to try an segment the input image . We can try and get a first, rough, binary mask of the input. This will mark where we are sure the algorithm can find foreground pixels. We will feed this rough mask to the algorithm and check out the results. Now, the method is not easy and its automation not straightforward, there's some manual information we will set that work particularly well for this input image. I don't know the Java implementation of OpenCV, so I'm giving you the solution for Python. Hopefully you will be able to port it. This is the general outline of the algorithm:

1. Get a first rough mask of the foreground object via thresholding
2. Detect contours on the rough mask to retrieve a bounding rectangle
3. The bounding rectangle will serve as input ROI for the GrabCut algorithm
4. Set the parameters needed for the GrabCut algorithm
5. Clean the segmentation mask obtained by GrabCut
6. Use the segmentation mask to finally segment the foreground object

This is the code:

I figured it out, it wasn't installed correctly. I copied the windows installation jdk rather than installing the .rpm jdk via Alien. After proper installation it was installed in /usr/java/jdk-14.0.1, so I used that as the path.

I use the spring framework with gradle, lombok plugin and skdman (aside gradle, for maven is as good as well, I recommend use'em, they are all great), but I believe my configurations can be useful for everyone, so here it goes ...

One thing I may add thought its I got strange errors using plugins with command line gradle wich was corrected when i start using the vscode plugins interfaces only, therefor i would recommend give it a try and use the plugins buttons, if you have not done it yet.

At launch.json I have the following debug configurations:

Found the answer, put the extra -DOPENCV_JAVA_TARGET_VERSION=1.8 args to cmake in brew formula.

Java solves both issues presented in that article:

• Shallowly immutable data holders ➙ Records
• Read-only maps ➙ Map.copyOf

Leaking references is an important issue. But that article’s solution seems overwrought to me in its approach.

• Certainly creating the CustomerRecords to hold a map seems redundant and useless. Instead, use a non-modifiable map (discussed below).
• As for a "read-only" interface as view onto a mutable object, this might make sense in some limited situations. But you might also wreak havoc when the supposedly immutable "CustomerReadOnly" returns a different email address on the second call to "getEmail" after an update. Trying to be simultaneously both mutable and immutable is unwise. To handle immutability, instead make an immutable copy of the mutable state.

The Records feature being previewed in Java 14 and previewed again in Java 15, and discussed by Brian Goetz, provide for shallowly immutable data holders. This special kind of class handles automatically the constructor, “getter” accessors, equals, hashCode, and toString methods behind the scenes. So your example class Customer turns into this utterly simple code:

The path separator in all non-Windows systems is colon (:), not semicolon (;). You need to change this: