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I am from Netherlands

systray27, Monday, Mar 25th 2019 Digg | Tweet | Delicious 0 comments  

Roffa citay!

systray27, Monday, Mar 25th 2019 Digg | Tweet | Delicious 0 comments  

I am from Italy

ddf, Sunday, Mar 24th 2019 Digg | Tweet | Delicious 0 comments  

I am from Italy

ddf, Sunday, Mar 24th 2019 Digg | Tweet | Delicious 0 comments  

I am from Germany

guest, Wednesday, Mar 20th 2019 Digg | Tweet | Delicious 0 comments  

I needed to implement a BVH acceleration structure before I could proceed to more complicated scenes. Now this thing rips.

polyrhythm, Tuesday, Mar 19th 2019 Digg | Tweet | Delicious 0 comments  

General Status

As you know, efforts have been going for the last year and a half into bringing a computer vision nodeset to VL.

The goal was to incorporate as many of the features covered by the world renowned ImagePack; contributed by Elliot Woods some years ago; while bringing in as many new features and improvements as we could.

In the winter of 2018, after setting a roadmap and having patched a decent initial nodeset, we happily announced the pre-release version of VL.OpenCV.

Since then, listening to your needs and constant feedback, we have tried to polish every corner, fix every bug, document every odd scenario, add plenty of demos and specially we tried to give you a clean, consistent and easy to use nodeset.

At this point in time, we are happy to announce that the goal has been nearly met. Most of the features available in the ImagePack made it into VL.OpenCV with the exception of Structured Light, Feature Detection, StereoCalibrate and some of the Contour detection functionality. At the same time, newer features such as YOLO, Aruco marker detection and others have been brought in for you to play with.

So what's next? Even better documentation and loads of examples!

In the mean time, here is a summary of the new things that have been brought into the package in the last couple of months:

CvImage

The new CvImage wrapper around OpenCV's Mat type allows for some optimizations, specially when dealing with non-changing images.

CvImage allows nodes to run only once when the image has changed, significantly reducing CPU usage

Cache Region lovvvves CvImage!

Since it is now possible to detect if an image has changed, CvImage is a perfect candidate to benefit from Cache regions.

Cache Region

Cache regions can now make proper usage of image inputs and outputs

Keep in mind that Cache regions have already been added to most VL.OpenCV nodes. When in doubt just open the node and have a look inside.

Renderer

The Renderer was re-built from the ground up to improve usability and to fix bugs and issues. Title, Render Mode and Show Info features were added. Renderer also remembers its bounds on document reload.

Renderer

New Renderer implementation introduces Title, Renderer Mode and Show Info pins

Histograms

Histogram analysis has been added to VL.OpenCV. A useful tool in many scenarios.

Hitograms

Histograms allow you to analyze pixel value tendencies per channel

Homography

Homography and reverse homography are now available in VL.OpenCV.

Homography

Homography (vvvv used only for point IOBox)

Stereo Matchers

Two new Stereo Matchers were added, these allow you to create a depth map from a set of stereo images. For more see the StereoDepth demo patch in VL.OpenCV.

Stereo Matcher

Depth map obtained from a pair of stereo images

Serialization

Serialization support was added for CvImage and Mat types, allowing you to use CvImage as part of more complex data structures which get serialized with no effort. This can be a heavy operation so make sure to trigger it when needed only.

For a hands on demonstration check out the Serialization VL demo that ships with VL.OpenCV.

Breaking Changes

As part of this final effort to clean everything even further and make the nodeset consistent and properly organized, we needed to rename and move a few things around which as you can imagine means the introduction of breaking changes. We understand this is an annoying thing to cope with, but this was basically the reason why we chose to keep this pack in a pre-release state until we felt confident with its structure and approach.

In summary yes, you will get red nodes when you upgrade your VL.OpenCV projects to the latest version, but in most cases it should be as easy as to double-click and find the node in its new category.

An exception to this are the nodes that got renamed, which we list below:

  • Reader (Intrinsics) -> IntrinsicsReader
  • Reader (View Projection) -> ViewProjectionReader
  • Writer (Intrinsics) -> IntrinsicsWriter
  • Writer (View Projection) -> ViewProjectionWriter
  • GetByteArray -> ToByteArray
  • GetValues -> ToValues
  • GetValues (Custom) -> ToValues (Custom)
  • FiducialTracker -> FiducialDetector
  • Update (FaceRecognizer) -> FaceRecognizerUpdate
  • VideoFile (Append) -> VideoWriter (Append)
  • VideoFile - VideoPlayer
  • Merge -> Join

Summarized Changelog

General

  • Introduced a new wrapper for Mat called CvImage
  • Cache region additions to improve performance on non-changing Images
  • ImageReader re-implementation
  • Renderer re-implementation
  • VideoIn re-implementation
  • Reintroduced "Supported Formats" output pin on VideoIn node
  • Upgraded to VL.Core 0.95.37
  • DirectX/OpenCV transformation documentation and cleanup
  • Added Blocking, Reactive and HoldLatestCopy versions of VideoIn node
  • Added Blocking and Reactive versions of ImageReader node
  • Reimplemented Extrinsics as a data type
  • Stabilized VideoFile Source node and moved from Experimental into Sources
  • Added Serialization support for Mat type
  • Added Serialization support for CvImage type

New in VL

Nodes

  • StereoBMMatcher
  • StereoSGBMMatcher
  • ToValues (Custom)
  • ToValues
  • GetChannel
  • Histogram
  • DrawHistogram
  • ToByteArray
  • Transform (Perspective)
Demos

  • DrawNodes
  • Homography
  • Histogram
  • Serialization
  • StereoSGBMMatcher

New in vvvv

Nodes

  • IntrinsicsToProjectionMatrix
  • ExtrinsicsToViewMatrix
Demos

  • Calibrate and Reproject
  • SolvePnP
  • StereoDepth

Remember that in order to use VL.OpenCV you first need to manually install it as explained here. Also, until we move away from pre-release you need to use the latest alpha builds.

We hope you find good use for this library in your computer vision projects and as always, please test and report.

ravazquez, Sunday, Mar 17th 2019 Digg | Tweet | Delicious 3 comments  

Bi directional communication between cables.gl and vvvv..
Looks nice

AKa-visuals, Friday, Mar 15th 2019 Digg | Tweet | Delicious 0 comments  

Up until now VL had a rather rudimentary support for pin groups. Only nodes following a certain pattern had the option to have a dynamic amount of input pins. For simple nodes like a plus or a multiply this worked out fine, but for others it either felt like a hack or it was simply impossible to use at all. A node having a dynamic amount of outputs was never supported at all.

Pin Groups by Index

This all changes now by introducing proper support for pin groups. So let's jump right into it and have a look at the definition of the very famous Cons node:

As we can see the pin inspektor is showing one new entry called "Pin Group". This flag has to be enabled obviously. Then we annotate the pin with type Spread. This creates pins with the name "Input", "Input 2", "Input 3" etc. on the node.

If we now look at an application of the Cons node we can already see a couple of nice new features:

  1. It's much faster. To build the input spread it can make use of a spread builder allocating the needed memory in one go, compared to the old Cons node which concatenated one spread after the other, leading to a total of 8 copies.
  2. The returned spread will stay the same as long as the inputs stay the same. This is done by keeping the generated spread for the input group in an internal field. When building up the new spread each slice will be compared to with the one from before. And only if one of those slices change a new spread will be allocated.

Pin groups are not limited to inputs, they also work for outputs which brings us to a new node called Decons - deconstructing a spread into its outputs:

Pin Groups by Name

Cons and Decons are examples of using a pin group as a Spread. But there is another variant where the group gets annotated as a Dictionary<string,*>. Instead of addressing the pins by index, they get addressed by their actual name. Let's have a look at two other new nodes again called Cons and Decons but residing in the Dictionary category:

Pins can get added as usual with Ctrl - +, but what's new is that those pins can be renamed in the inspektor UI giving us the ability to quickly build up dictionaries.
The patch of the Cons building up a dictionary compared to the one building up a spread only differs in the type annotation of the input pin.

Apart from Spread and Dictionary the system also supports pin groups of type Array, MutableArray and MutableDictionary. According Cons and Decons nodes can be found when enabling the Advanced view in the node browser.

Creating Pins from within a Patch

So far the pins of a pin group have always been created by the user interface of the patch editor. Things get really interesting though when creating them from within the patch itself:

Imagine the string being an expression of some sort generating inputs for each unbound variable. The possibilities are endless :)

The nodes needed to create and remove pins can be found in the VL category after adding a reference to VL.Lang - the patch from the gif above can be found in the help folder of the VL.CoreLib package.

More information on those nodes will be covered in an upcoming blog post. Until then you can try these new pin groups in our latest alpha downloads and happy patching,

yours,
devvvvs

Elias, Friday, Mar 15th 2019 Digg | Tweet | Delicious 0 comments  

I am from United States of America

guest, Wednesday, Mar 13th 2019 Digg | Tweet | Delicious 0 comments  

anonymous user login

Shoutbox

~6d ago

auralscapes: By the way, if anyone would like to use any of my tracks or even parts thereof you are welcome. No fee. jerome@auralscapes.com

~7d ago

auralscapes: Thx for the advice. Much appreciated.

~7d ago

tonfilm: @auralscapes you can contact the author @dottore and ask him for the conditions.

~7d ago

auralscapes: A question for the group. I came across an application called Partitura. Is this app commercially available?

~7d ago

auralscapes: Don't have a clue how this all works but it is going to be an interesting journey indeed.

~10d ago

tonfilm: @all #vl now also has pin groups! vl-input-and-output-pin-groups #vvvv #creativecoding #visualprogramming #dotnet

~11d ago

evvvvil: Hey, broski, check my shader "The gamma ray feast" it goes bang and is commented with bad to mediocre jokes. https://www.shadertoy.com/view/wssXWl

~13d ago

hrovac: someone at b-seite on saturday?