Wolfram Computation Meets Knowledge

New in 13: Video, Image & Audio

Two years ago we released Version 12.0 of the Wolfram Language. Here are the updates in video, image and audio since then, including the latest features in 13.0. The contents of this post are compiled from Stephen Wolfram’s Release Announcements for 12.1, 12.2, 12.3 and 13.0.

 

The Beginning of Video Computation (March 2020)

We’ve been working towards it for nearly 15 years… but finally it’s here: computation with video! We introduced images into the language in 2008; audio in 2016. But now in Version 12.1 we for the first time have computation with video. There’ll be lots more coming in future releases, but there’s already quite a bit in 12.1.

So… just like Image and Audio, which symbolically represent images and audio, we now have Video.

This asks for five frames from a video:

VideoFrameList
&#10005

VideoFrameList[
 Video["ExampleData/Caminandes.mp4", Appearance -> Automatic, 
  AudioOutputDevice -> Automatic, SoundVolume -> Automatic], 5]

This asks to make a time series of the mean color of every frame:

VideoTimeSeries
&#10005

VideoTimeSeries[Mean, 
 Video["ExampleData/Caminandes.mp4", Appearance -> Automatic, 
  AudioOutputDevice -> Automatic, SoundVolume -> Automatic]]

And then one can just plot the time series:

DateListPlot
&#10005

DateListPlot[%, 
 PlotStyle -> {RGBColor[1, 0, 0], RGBColor[0, 1, 0], RGBColor[
   0, 0, 1]}]

Video is a complicated area, with lots of different encodings optimized for different purposes. In Version 12.1 we’re supporting more than 250 of them, for import, export and transcoding. You can refer to a video on the web as well:

Video
&#10005

Video["http://exampledata.wolfram.com/cars.avi"]

And the big thing is that video is now getting integrated into everything. So, for example, you can immediately use image processing or audio processing or machine learning functions on video. Here’s an example plotting the location of cars in the video above:

v = Video
&#10005

v = Video["http://exampledata.wolfram.com/cars.avi"]

ts = VideoTimeSeries
&#10005

ts = VideoTimeSeries[Point[ImagePosition[#, Entity["Word", "car"]]] &,
   v]

HighlightImage
&#10005

HighlightImage[
 VideoExtractFrames[v, Quantity[5, "Seconds"]], {PointSize[Medium], 
  Values[ts]}]

Let’s say you’ve got a Manipulate, or an animation (say from ListAnimate). Well, now you can just immediately make a video of it:

Video
&#10005

Video[CloudGet["https://wolfr.am/L9r00rk5"]]

You can add an audio track, then export the whole thing directly to a file, the cloud, etc.

So is this new video capability really industrial strength? I’ve been recording hundreds of hours of video in connection with a new project I’m working on. So I decided to try our new capabilities on it. It’s spectacular! I could take a 4-hour video, and immediately extract a bunch of sample frames from it, and then—yes, in a few hours of CPU time—“summarize the whole video”, using SpeechRecognize to do speech-to-text on everything that was said and then generating a word cloud:

Working session

Speaking of audio, there’s new stuff in Version 12.1 there too. We’ve redone the GUI for in-notebook Audio objects. And we’ve introduced SpeechInterpreter, which is the spoken analog of the Interpreter function, here taking an audio object and returning what airline name was said in it:

SpeechInterpreter
&#10005

SpeechInterpreter["Airline"][CloudGet["https://wolfr.am/L9r410jA"]]

In Version 12.0 we introduced the important function TextCases for extracting from text hundreds of kinds of entities and “text content types” (which as of 12.1 now have their own documentation pages). In 12.1 we’re also introducing SpeechCases, which does the same kind of thing for audio speech.

Mainstreaming Video (December 2020)

In Version 12.1 we began the process of introducing video as a built-in feature of the Wolfram Language. Version 12.2 continues that process. In 12.1 we could only handle video in desktop notebooks; now it’s extended to cloud notebooks—so when you generate a video in Wolfram Language it’s immediately deployable to the cloud.

A major new video feature in 12.2 is VideoGenerator. Provide a function that makes images (and/or audio), and VideoGenerator will generate a video from them (here a 4-second video):

VideoGenerator
VideoGenerator
&#10005

VideoGenerator[Graphics3D[AugmentedPolyhedron[Icosahedron[], # - 2],
   ImageSize -> {200, 200}] &, 4]

To add a sound track, we can just use VideoCombine:

VideoCombine
&#10005

VideoCombine[{%, \!\(\*
TagBox[
RowBox[{"CloudGet", "[", "\"\<https://wolfr.am/ROWzckqS\>\"", "]"}],
Audio`AudioBox["AudioClass" -> "AudioData"],
Editable->False,
Selectable->False]\)}]

So how would we edit this video? In Version 12.2 we have programmatic versions of standard video-editing functions. VideoSplit, for example, splits the video at particular times:

VideoSplit
&#10005

VideoSplit[%, {.3, .5, 2}]

But the real power of the Wolfram Language comes in systematically applying arbitrary functions to videos. VideoMap lets you apply a function to a video to get another video. For example, we could progressively blur the video we just made:

VideoMap
VideoMap
&#10005

VideoMap[Blur[#Image, 20 #Time] &, %%]

There are also two new functions for analyzing videos—VideoMapList and VideoMapTimeSeries—which respectively generate a list and a time series by applying a function to the frames in a video, and to its audio track.

Another new function—highly relevant for video processing and video editing—is VideoIntervals, which determines the time intervals over which any given criterion applies in a video:

VideoIntervals
&#10005

VideoIntervals[%, Length[DominantColors[#Image]] < 3 &]

Now, for example, we can delete those intervals in the video:

VideoDelete
&#10005

VideoDelete[%, %%]

A common operation in the practical handling of videos is transcoding. And in Version 12.2 the function VideoTranscode lets you convert a video among any of the over 300 containers and codecs that we support. By the way, 12.2 also has new functions ImageWaveformPlot and ImageVectorscopePlot that are commonly used in video color correction:

ImageVectorscopePlot
&#10005

ImageVectorscopePlot[CloudGet["https://wolfr.am/ROWzsGFw"]]

One of the main technical issues in handling video is dealing with the large amount of data in a typical video. In Version 12.2 there’s now finer control over where that data is stored. The option GeneratedAssetLocation (with default $GeneratedAssetLocation) lets you pick between different files, directories, local object stores, etc.

But there’s also a new function in Version 12.2 for handling “lightweight video”, in the form of AnimatedImage. AnimatedImage simply takes a list of images and produces an animation that immediately plays in your notebook—and has everything directly stored in your notebook:

AnimatedImage
&#10005

AnimatedImage[
 Table[Rasterize[Rotate[Style["W", 40], \[Theta]]], {\[Theta], 0, 
   2 Pi, .1}]]

New in Video (May 2021)

We first introduced video into the Wolfram Language in Version 12.1, and in 12.2 we added many additional video capabilities. In 12.3 we’re adding still more capabilities, with yet more to come.

A major group of new capabilities in 12.3 revolve around programmatic video generation. There are three basic new functions: FrameListVideo, SlideShowVideo and AnimationVideo.

FrameListVideo takes a raw list of images, and assembles a video by treating them as successive raw frames. SlideShowVideo similarly takes a list of images, but now it creates a “slide show video” in which each image is displayed for a specified duration. Here, for example, each image is displayed in the video for 1 second:

&#10005

SlideShowVideo[{\!\(\*
GraphicsBox[
TagBox[RasterBox[CompressedData["
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SlideShowVideo can also do things like take a TimeSeries whose values are images, and turn this into a slide show video.

AnimationVideo doesn’t take existing images; instead it takes an expression and then evaluates it “Manipulate-style” for a range of values of a parameter. (In effect, it’s like a video-making analog of Animate.)

&#10005

AnimationVideo[
 Plot[Sin[a x] + Sin[x], {x, 0, 10}, Sequence[
  ImageSize -> 300, PlotRange -> {-2, 2}, Filling -> Axis, 
   FillingStyle -> LightOrange]], {a, 0, 3}]

What if you want to capture a video, say from a camera? Eventually there’ll be an interactive way to do this in a notebook. But in Version 12.3 we’ve added the underlying programmatic capabilities, and in particular the function VideoRecord. So this records 5 seconds from my default camera:

&#10005

sw = VideoRecord[$DefaultImagingDevice]; Pause[5]; VideoStop[];

And here’s the resulting video:

&#10005

swvid=Video[sw]

But VideoRecord can also use other sources. For example, if you give it a NotebookObject, it will record what’s happening in that notebook. And if you give it a URL (say for a webcam), it’ll record frames that are streaming from that URL:

Icon

A much-requested feature that we’ve added in Version 12.3 is the ability to combine videos, for example compositing one video into another, or assembling each frame as a collage.

So, for example, here’s me green-screen composited with the stream above:

&#10005

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Notice that in doing this we’re using Parallelize—which newly works with VideoFrameMap in 12.3.

Version 12.3 also adds some new video-editing capabilities. VideoTimeStretch lets you “warp time” in a video by any specified function. VideoInsert lets you insert a video clip into a video, and VideoReplace lets you replace part of a video with another one.

One of the best things about video in the Wolfram Language is that it can immediately be analyzed using all of the tools in the language. This includes machine learning, and in Version 12.3 we’ve started the process of allowing videos to be encoded for neural net computation. Version 12.3 includes a simple frame-based net encoder for videos, as well as a couple of built-in feature extractors. More will be coming soon, including a variety of video processing and analysis nets in the Wolfram Neural Net Repository.

Making Videos from Images & Videos (December 2021)

In Version 12.3 we released functions like AnimationVideo and SlideshowVideo which make it easy to produce videos from generated content. In Version 13.0 we now also have a collection of functions for creating videos from existing images, and videos.

By the way, before we even get to making videos, another important new feature in Version 13.0 is that it’s now possible to play videos directly in a notebook:


&#10005


This works both on the desktop and in the cloud, and you get all the standard video controls right in the notebook, but you can also pop out the video to view it with an external (say, full-screen) viewer. (You can also now just wrap a video with AnimatedImage to make it into a “GIF-like” frame-based animation.)

OK, so back to making videos from images. Let’s say you have a large image:

Tour video image

A good way to “experience” an image like this can be through a “tour video” that visits different parts of the image in turn. Here’s an example of how to do that:


&#10005


You can zoom as well as pan:


&#10005


As a more sophisticated example, let’s take a classic “physics image”:

Physics image

This finds the positions of all the faces, then computes a shortest tour visiting each of them:

&#10005


Now we can create a “face tour” of the image:


&#10005


In addition to going from images to videos, we can also go from videos to videos. GridVideo takes multiple videos, arranges them in a grid, and creates a combined new video:


&#10005

GridVideo[{Video[
   URLDownload[
    "https://www.wolframcloud.com/obj/sw-writings/Version-13/Video1.\
mp4"]], Video[
   URLDownload[
    "https://www.wolframcloud.com/obj/sw-writings/Version-13/Video2.\
mp4"]], Video[
   URLDownload[
    "https://www.wolframcloud.com/obj/sw-writings/Version-13/Video3.\
mp4"]], Video[
   URLDownload[
    "https://www.wolframcloud.com/obj/sw-writings/Version-13/Video4.\
mp4"]]}, Spacings -> 2]

We can also take a single video and “summarize” it as a series of video + audio snippets, chosen for example equally spaced in the video. Think of it as a video version of VideoFrameList. Here’s an example “summarizing” a 75-minute video:

There are some practical conveniences for handling videos that have been added in Version 13.0. One is OverlayVideo which allows you to “watermark” a video with an image, or insert what amounts to a “picture-in-picture” video:

&#10005


We’ve also made many image operations directly work on videos. So, for example, to crop a video, you just need to use ImageCrop:


&#10005


Image Stitching (December 2021)

Let’s say you’ve taken a bunch of pictures at different angles—and now you want to stitch them together. In Version 13.0 we’ve made that very easy—with the function ImageStitch:

&#10005


Part of what’s under the hood in image stitching is finding key points in images. And in Version 13.0 we’ve added two further methods (SIFT and RootSIFT) for ImageKeypoints. But aligning key points isn’t the only thing we’re doing in image stitching. We’re also doing things like brightness equalization and lens correction, as well as blending images across seams.

Image stitching can be refined using options like TransformationClass—which specify what transformations should be allowed when the separate images are assembled.

The Calculus of Annotations (March 2020)

How do you add metadata annotations to something you’re computing with? For Version 12.1 we’ve begun rolling out a general framework for making annotations—and then computing with and from them.

A completely different kind of structure that can also use annotations is audio. This annotates an Audio object with information about where there’s voice activity in the audio:

AudioAnnotate
&#10005

AudioAnnotate[ExampleData[{"Audio", "MaleVoice"}], "Voiced"]

This retrieves the value of the annotation:

AnnotationValue
&#10005

AnnotationValue[%, "Voiced"] // TimelinePlot

We’ll be rolling out annotations in lots of other things too. One that’s coming is images. But in preparation for that, in Version 12.1 we’ve added some new capabilities to HighlightImage.

Use machine learning to find what’s in the picture:

ImageBoundingBoxes
&#10005

ImageBoundingBoxes[CloudGet["https://wolfr.am/L9qz1zu4"]]

Now HighlightImage can use the annotation information:

HighlightImage
&#10005

HighlightImage[CloudGet["https://wolfr.am/L9qz1zu4"], %]