In my last post I described using AVSampleBufferDisplayLayer to output manually-uncompressed YUV video frames in an iOS app, for playing WebM and Ogg files from Wikimedia Commons. After further experimentation I’ve decided to instead stick with using OpenGL ES directly, and here’s why…
640×360 output regularly displays with a weird horizontal offset corruption on iPad Pro 9.7″. Bug filed as rdar://29810344
Can’t get any pixel format with 4:4:4 subsampling to display. Theora and VP9 both support 4:4:4 subsampling, so that made some files unplayable.
Core Video pixel buffers for 4:2:2 and 4:4:4 are packed formats, and it prefers 4:2:0 to be a weird biplanar semi-packed format. This requires conversion from the planar output I already have, which may be cheap with Neon instructions but isn’t free.
Instead, I’m treating each plane as a separate one-channel grayscale image, which works for any chroma subsampling ratios. I’m using some Core Video bits (CVPixelBufferPool and CVOpenGLESTextureCache) to do texture setup instead of manually calling glTeximage2d with a raw source blob, which improves a few things:
Can do CPU->GPU memory copy off main thread easily, without worrying about locking my GL context.
No pixel format conversions, so straight memcpy for each line…
Buffer pools are tied to the video buffer’s format object, and get swapped out automatically when the format changes (new file, or file changes resolution).
Don’t have to manually account for stride != width in the texture setup!
It could be more efficient still if I could pre-allocate CVPixelBuffers with on-GPU memory and hand them to libvpx and libtheora to decode into… but they currently lack sufficient interfaces to accept frame buffers with GPU-allocated sizes.
A few other oddities I noticed:
The clean aperture rectangle setting doesn’t seem to be preserved when creating a CVPixelBuffer via CVPixelBufferPool; I have to re-set it when creating new buffers.
For grayscale buffers, the clean aperture doesn’t seem to be picked up by CVOpenGLESTextureGetCleanTexCoords. Not sure if this is only supposed to work with Y’CbCr buffer types or what… however I already have all these numbers in my format object and just pull from there. 🙂
I also fell down a rabbit hole researching color space issues after noticing that some of the video formats support multiple colorspace variants that may imply different RGB conversion matrices… and maybe gamma…. and what do R, G, and B mean anyway? 🙂 Deserves another post sometime.
I’ve often wished that for ogv.js I could send my raw video and audio output directly to a “real” <video> element for rendering instead of drawing on a <canvas> and playing sound separately to a Web Audio context.
In particular, things I want:
Not having to convert YUV to RGB myself
Not having to replicate the behavior of a <video> element’s sizing!
The warm fuzzy feeling of semantic correctness
Making use of browser extensions like control buttons for an active video element
Being able to use browser extensions like sending output to ChromeCast or AirPlay
Disabling screen dimming/lock during playback
This last is especially important for videos of non-trivial length, especially on phones which often have very aggressive screen dimming timeouts.
Well, in some browsers (Chrome and Firefox) now you can do at least some of this. 🙂
I’ve done a quick experiment using the <canvas> element’s captureStream() method to capture the video output — plus a capture node on the Web Audio graph — combining the two separate streams into a single MediaStream, and then piping that into a <video> for playback. Still have to do YUV to RGB conversion myself, but final output goes into an honest-to-gosh <video> element.
To my great pleasure it works! Though in Firefox I have some flickering that may be a bug, I’ll have to track it down.
Flickering on Firefox. Might just be my GPU, might be something else.
The <video> doesn’t have insight to things like duration, seeking, etc, so can’t rely on native controls or API of the <video> alone acting like a native <video> with a file source.
Pretty sure there are inefficiencies. Have not tested performance or checked if there’s double YUV->RGB->YUV->RGB going on.
Of course, Chrome and Firefox are the browsers I don’t need ogv.js for for Wikipedia’s current usage, since they play WebM and Ogg natively already. But if Safari and Edge adopt the necessary interfaces and WebRTC-related infrastructure for MediaStreams, it might become possible to use Safari’s full screen view, AirPlay mirroring, and picture-in-picture with ogv.js-driven playback of Ogg, WebM, and potentially other custom or legacy or niche formats.
Unfortunately I can’t test whether casting to a ChromeCast works in Chrome as I’m traveling and don’t have one handy just now. Hoping to find out soon! 😀
“It’s an older codec, but it checks out. I was about to let them through.”
This first generation uses the Ogg Theora video codec, which we started using on Wikipedia “back in the day” before WebM and MP4/H.264 started fighting it out for dominance of HTML5 video. In fact, Ogg Theora/Vorbis were originally proposed as the baseline standard codecs for HTML5 video and audio elements, but Apple and Microsoft refused to implement it and the standard ended up dropping a baseline requirement altogether.
Ah, standards. There’s so many to choose from!
I’ve got preliminary support for WebM in ogv.js; it needs more work but the real blocker is performance. WebM’s VP8 and newer VP9 video codecs provide much better quality/compression ratios, but require more CPU horsepower to decode than Theora… On a fast MacBook Pro, Safari can play back ‘Llama Drama’ in 1080p Theora but only hits 480p in VP8.
That’s about a 5x performance gap in terms of how many pixels we can push… For now, the performance boost from using an older codec is worth it, as it gets older computers and 64-bit mobile devices into the game.
But it also means that to match quality, we have to double the bitrate — and thus bandwidth — of Theora output versus VP8 at the same resolution. So in the longer term, it’d be nice to get VP8 — or the newer VP9 which halves bitrate again — working well enough on ogv.js.
emscripten: making ur C into JS
Awesome town. But what are the limitations and pain points?
This is “convenient” for classic scripting in that you don’t have to worry about picking the right numeric type, but it has several horrible, horrible consequences:
When you really wanted 32-bit integers, floating-point math is going to be much slower
When you really wanted 64-bit integers, floating-point math is going to lose precision if your numbers are too big… so you have to emulate with 32-bit integers
If you relied on the specific behavior of 32-bit integer multiplication, you may have to use a slow polyfill of Math.imul
Did I say “luckily”? 😛
So this leads to one more ugly consequence:
In order to force the JIT compiler to run integer math, emscripten output coerces types constantly — “(x|0)” to force to 32-bit int, or “+x” to force to 64-bit float.
This actually performs well once it’s through the JIT compiler, but it bloats the .js code that we have to ship to the browser.
The heap is an island
Emscripten provides a C-like memory model by using Typed Arrays: a single ArrayBuffer provides a heap that can be read/written directly as various integer and floating point types.
Currently I’m simply copying the input packets into emscripten’s heap in a wrapper function, then calling the decoder on the copy. This works, but the extra copy makes me sad. It’s also relatively slow in Internet Explorer, where the copy implementation using Uint8Array.set() seems to be pretty inefficient.
Getting data out can be done “zero-copy” if you’re careful, by creating a typed-array subview of the emscripten heap; this can be used for instance to upload a WebGL texture directly from the decoder. Neat!
But, that trick doesn’t work when you need to pass data between worker threads.
Parallel computing is now: these days just about everything from your high-end desktop to your low-end smartphone has at least two CPU cores and can perform multiple tasks in parallel.
Unfortunately, despite half a century of computer science research and a good decade of marketplace factors, doing parallel programming well is still a Hard Problem.
This is actually a really nice model that reduces the number of ways you can shoot yourself in the foot with multithreading!
But, it maps very poorly to C/C++ threads, where you start with shared memory and foot-shooting and try to build better abstractions on top of that.
So, we’re not yet able to make use of any multithreaded capabilities in the actual decoders. 🙁
But, we can run the decoders themselves in Worker threads, as long as they’re factored into separate emscripten subprograms. This keeps the main thread humming smoothly even when video decoding is a significant portion of wall-clock time, and can provide a little bit of actual parallelism by running video and audio decoding at the same time.
The Theora and VP8 decoders currently have no inherent multithreading available, but VP9 can so that’s worth looking out for in the future…
Some browser makers are working on providing an “opt-in” shared-memory threading model through an extended ‘SharedArrayBuffer’ that emscripten can make use of, but this is not yet available in any of my target browsers (Safari, IE, Edge).
Waiting for SIMD
Modern CPUs provide SIMD instructions (“Single Instruction Multiple Data”) which can really optimize multimedia operations where you need to do the same thing a lot of times on parallel data.
But, my main targets (Safari, IE, Edge) don’t support SIMD in JS yet so I haven’t started…
The obvious next thing to ask is “Hey what about the GPU?” Modern computers come with amazing high-throughput parallel-processing graphics units, and it’s become quite the rage to GPU accelerate everything from graphics to spreadsheets.
The good news is that current versions of all main browsers support WebGL, and ogv.js uses it if available to accelerate drawing and YCbCr-RGB colorspace conversion.
The bad news is that’s all we use it for so far — the actual video decoding is all on the CPU.
It should be possible to use the GPU for at least parts of the video decoding steps. But, it’s going to require jumping through some hoops…
WebGL doesn’t provide general-purpose compute shaders, so would have to shovel data into textures and squish computation into fragment shaders meant for processing pixels.
WebGL is only available on the main thread, so if decoding is done in a worker there’ll be additional overhead shipping data between threads
If we have to read data back from the GPU, that can be slow and block the CPU, dropping efficiency again
The codec libraries aren’t really set up with good GPU offloading points in them, so this may be Hard To Do.
See list of pending fixes for additional improvements that should go out next week, after which I’ll make wider announcements.
Or simply if the integration code’s automatic benchmark overestimated your browser speed, running too much decoding just made everything crap.
Luckily, the HTML5 web platform has a solution — Web Workers.
The limitation is that scripts running in a Worker have no direct access to your code or data running in the web page’s main thread — you can communicate only by sending messages with ‘raw’ data types. Folks working with lots of DOM browser nodes thus can’t get much benefit, but for buffer-driven compute tasks like media decoding it’s perfect!
Threading comms overhead
My first attempt was to take the existing decoder class (an emscripten module containing the Ogg demuxer, Theora video decoder, and Vorbis audio decoder, etc) and run it in the worker thread, with a proxy object sending data and updated object properties back and forth.
This required a little refactoring to make the decoder interfaces asynchronous, taking callbacks instead of returning results immediately.
It worked pretty well, but there was a lot of overhead due to the demuxer requiring frequent back-and-forth calls — after every processing churn, we had to wait for the demuxer to return its updated status to us on the main thread.
This only took a fraction of a millisecond each time, but a bunch of those add up when your per-frame budget is 1/30 (or even 1/60) second!
I had been intending a bigger refactor of the code anyway to use separate emscripten modules for the demuxer and audio/video decoders — this means you don’t have to load code you won’t need, like the Opus audio decoder when you’re only playing Vorbis files.
It also means I could change the coupling, keeping the demuxer on the main thread and moving just the audio/video decoders to workers.
This gives me full speed going back-and-forth on the demuxer, while the decoders can switch to a more “streaming” behavior, sending packets down to be decoded and then displaying the frames or queueing the audio whenever it comes back, without having to wait on it for the next processing iteration.
The result is pretty awesome — in particular on older Windows machines, IE 11 has to use the Flash plugin to do audio and I was previously seeing a lot of “stuttery” behavior when the video decode blocked the Flash audio queueing or vice versa… now it’s much smoother.
The main bug left in the worker mode is that my audio/video sync handling code doesn’t properly handle the case where video decoding is consistently too slow — when we were on the main thread, this caused the audio to halt due to the main thread being blocked; now the audio just keeps on going and the video keeps playing as fast as it can and never catches up. 🙂
However this should be easy to fix, and having it be wrong but NOT FREEZING YOUR BROWSER is an improvement over having sync but FREEZING YOUR BROWSER. 🙂
I’ve been cleaning up some of my old test code for running Ogg media on iOS, adding WebM support and turning it into OGVKit, a (soon-to-be) reusable library that we can use to finally add video and audio playback to our Wikipedia iPhone app.
Of course decoding VP8 or Theora video on the CPU is going to be more expensive in terms of energy usage than decoding H.264 in dedicated silicon… but how much more?
The iOS 9 beta SDK supports enhanced energy monitoring in Xcode 7 beta… let’s try it out! The diagnostic detail screen looks like so:
Whoa! That’s a little overwhelming. What’s actually going on here?
First, what’s going on here
I’ve got my OGVKit demo app playing this video “Curiosity’s Seven Minutes of Terror” found on Wikimedia Commons, on two devices running iOS 9 beta: an iPod Touch (the lowest-end currently sold iDevice) and an iPad Air (one generation behind the highest-end currently sold iDevice).
The iPod Touch is playing a modest 360p WebM transcode, while the iPad Air is playing a higher-resolution 720p WebM transcode with its beefier 64-bit CPU:
First look: the cost of networking
At first, the energy usage looks pretty high:
This however is because in addition to media playback we’re buffering umpty-ump megabytes over HTTPS over wifi — as fast as a 150 Mbps cable connection will allow.
Once the download completes, the CPU usage from SSL decoding goes down, the wifi reduces its power consumption, and our energy usage relatively flattens.
Now what’s the spot-meter look like?
Pretty cool, right!?
See approximate reported energy usage levels for all transcode formats (Ogg Theora and WebM at various resolutions) if you like! Ogg Theora is a little faster to decode but WebM looks significantly better at the bitrates we use.
Ok but how’s that compare to native H.264 playback?
Good question. I’m about to try it and find out.
Ok here’s what we got:
The native AVPlayer downloads smaller chunks more slowly, but similarly shows higher CPU and energy usage during download. Once playing only, reported CPU usage dives to a percent or two and the reported energy impact is “Zero”.
Now, I’m not sure I believe “Zero”… 😉
I suppose I’ll have to rig up some kind of ‘run until the battery dies’ test to compare how reasonable this looks for non-trivial playback times… but the ‘Low’ reportage for WebM at reasonable resolutions makes me happier than ‘Very High’ would have!
I’ve been passing the last few days feverishly working on audio/video stuff, cause it’s been driving me nuts that it’s not quite in working shape.
TL;DR: Major fixes in the works for Android, Safari (iOS and Mac), and IE/Edge (Windows). Need testers and patch reviewers.
ogv.js for Safari/IE/Edge
I’ll want to update it to work with Video.js later, but I’d love to get this version reviewed and deployed in the meantime.
Please head over to https://ogvjs-testing.wmflabs.org/ in Safari 6.1+ or IE 10+ (or ‘Project Spartan’ on Windows 10 preview) and try it out! Particularly interested in cases where it doesn’t work or messes up.
However these get really bad compression ratios, so to keep bandwidth down similar to the 360p Ogg and WebM versions I had to reduce quality and resolution significantly. Hold an iPhone at arm’s length and it’s maybe ok, but zoom full-screen on your iPad and you’ll hate the giant blurry pixels!
This should also provide a working basic audio/video experience in our Wikipedia iOS app, until such time as we integrate Ogg or WebM decoding natively into the app.
Note that it seems tricky to bulk-run new transcodes on old files with TimedMediaHandler. I assume there’s a convenient way to do it that I just haven’t found in the extension maint scripts…
In progress: mobile video fixes
Audio has worked on Android for a while — the .ogg files show up in native <audio> elements and Just Work.
But video has been often broken, with TimedMediaHandler’s “popup transforms” reducing most video embeds into a thumbnail and a link to the original file — which might play if WebM (not if Ogg Theora) but it might also be a 1080p original which you don’t want to pull down on 3G! And neither audio nor video has worked on iOS.
This patch adds a simple mobile target for TMH, which fixes the popup transforms to look better and actually work by loading up an embedded-size player with the appropriately playable transcodes (WebM, Ogg, and the MJPEG last-ditch fallback).
ogv.js is used if available and necessary, for instance in iOS Safari when the CPU is fast enough. (Known to work only on 64-bit models.)
Future: codec.js and WebM and OGVKit
For the future, I’m also working on extending ogv.js to support WebM for better quality (especially in high-motion scenes) — once that stabilizes I’ll rename the combined package codec.js. Performance of WebM is not yet good enough to deploy, and some features like seeking are still missing, but breaking out the codec modules means I can develop the codecs in parallel and keep the high-level player logic in common.
Browser infrastructure improvements like SIMD, threading, and more GPU access should continue to make WebM decoding faster in the future as well.
I’d also like to finish up my OGVKit package for iOS, so we can embed a basic audio/video player at full quality into the Wikipedia iOS app. This needs some more cleanup work still.
This is currently very incomplete; video doesn’t come out right and audio’s not hooked up yet, and most notably you only get a few frames before it craps out. 🙂
Update: Got audio working after some sleep, and playback is more thorough. Yay! Still no seeking yet, and playback may not always reach completion.
I’ve seen a couple other attempts to build WebM decoders in JS using emscripten (eg Route9), but nobody’s gotten them hooked up to a full-blown player with audio yet. With a little more work on the decoder side, I should be able to leverage all of my investment in ogv.js’s player logic.
I’m using nestegg for the WebM container parsing; currently this is giving me some impedence mismatch with the first-generation ogv.js code due to different i/o models.
ogv.js’s C-side Ogg container parsing was set up with entirely asynchronous i/o due to the needs of using async XHR to fetch data over the network. Nestegg, however, uses synchronous i/o callbacks in some places, and I really don’t want to jump through all the hoops to do WebM cue seeking without using the library. (Already did that with Ogg and it was horrid!)
I may be able to adapt the ogv.js C-side code to using synchronous i/o callbacks and let them get mapped to async i/o on the JS side, thanks to some fancy features in emscripten — either Asyncify or the newer emterpreter mode for parts of the high-level code while keeping the low-level decoder in pure asm.js. Need to do a little more research… 🙂
Performance: speed on WebM/VP8 decoding won’t be as good as the Ogg/Theora decoder for now so may not be suitable for mobile devices, but should work fine on many laptop/desktop machines.
VP9: untested so far, but should work… though again, likely to be still slower than VP8.
Threading: currently threading is disabled in the build. There’s work ongoing at Mozilla to support pthreads for emscripten programs, using a new SharedArrayBuffer interface to share memory between Web Worker threads. Might experiment with that later as libvpx has some threading options (may only be useful for VP9 multi-slice decoding for now) but it’ll be a while before most browsers support it. However this might be a good use case for asking Microsoft and Apple to add support. 🙂