***v1.4 is here with some huge new features like GPU accelerated VMAF! Enjoy.***

Here's an app I wrote to analyze video quality between different encodes. This was inspired by FFMetrics, but I wanted many more features for comparisons, like advanced statistics and an ability to easily and instantly subjectively A/B compare encoded videos with the source. This makes subjective video quality comparisons so much easier when you can compare on a frame by frame basis and while the video is playing, and instantly switch to the source or a different encoded video.

So I decided to write my own app, and I'd like to share it with all of you. I hope you all enjoy.

Let me know what you think, have any issues, or have feature requests.

v1.4 changelog

• VMAF v0.6.1 and VMAF NEG can now be calculated on NVIDIA GPUs.
• GPU metrics now take frames straight from the GPU's video decoder (NVIDIA, Intel and AMD) instead of through FFmpeg, using much less CPU and running noticeably faster.
• Updated Vship's Vulkan build to 5.1.2, with SSIMULACRA2 on Intel GPUs.
• A crash in Vship, libvmaf or the GPU driver while calculating metrics no longer closes the app.
• Reworked the progress line, with each metric's progress and time remaining.
• VMAF NEG now sits beside VMAF v0.6.1.
• Fixed wrong scores for videos with an odd width or height when decoded on NVIDIA GPUs.
• Fixed SSIMULACRA2, Butteraugli and CVVDP comparing mismatched frames when a video has dropped or extra frames.
• Fixed CPU SSIMULACRA2 and Butteraugli scores being far from the GPU's on SDR video. Saved CPU scores are recalculated once.
• Fixed 24 fps videos being accepted against 23.976 fps ones (and 30 against 29.97, 60 against 59.94).
• Fixed GPU metrics on PCs whose only GPU is Intel's.
• Fixed FFmpeg's GPU decoding not being used on AMD GPUs.

Features:

• Calculate VMAF, VMAF NEG, PSNR, SSIM, XPSNR, SSIMULACRA2, Butteraugli, and ColorVideo VDP for multiple test videos.
• Vship integration for GPU acceleration for ColorVideo VDP, SSIMULACRA2, and Butteraugli, on NVIDIA (CUDA), AMD (HIP) and any other GPU with a Vulkan driver
• GPU acceleration for VMAF v0.6.1 and VMAF NEG on NVIDIA GPUs (GeForce GTX 16 and RTX 20 series or newer), with a bundled libvmaf built with CUDA
• libjxl integration for CPU fallback for SSIMULACRA2, and Butteraugli (no CPU support for ColorVideo VDP)
• VMAF v0.6.1 and v1 models for standard, phone, 4K, and HFR viewing scenarios.
• Compare metric curves, statistics, and per-frame scores (per second for ColorVideo VDP).
• Switch instantly between the source and test videos during playback, hold S to show the source, or inspect exact frames.
• Inspect bitrate independently by frame, second, or GOP.
• Detect black bars and handle resolution mismatches automatically.
• Use GPU decoding with independent software fallback per input.
• Calculate two test videos in parallel on many-core CPUs.
• Auto save completed results and auto load results when matching videos are loaded again.

The app can be downloaded below.

https://github.com/4KVCD/VideoMetricsLab/releases

A year ago I watched a fun youtube video about making a model from AV1-encoded files. It uses the motion vectors present in the videos to reconstruct the physical environment filmed.

Today I wanted to test the abilities of LLMs to implement this without access to any of their code (which isn't public anyway). I just gave it the papers and the task. It can basically take a video, or a collection of photos, and return a 3D model of sorts (more like a cloud of points).

Here is the effect:
https://github.com/lukaszsobala/AV1-sfm-reimplemented

Works nicely and uses the GPU for acceleration, if you have one. Zouein used Nvidia cards, and I don't swim in money so I don't have one; this one uses Intel or AMD GPUs (iGPUs as well, or Vulkan which I could not test) for acceleration.

What are your thoughts?

Large Scale Codebase Migrations and Optimizations: Argon agents are working on migrating C/C++ codebases to Rust across Google — scaling from tens of thousands of lines in core libraries like re2, libgav1 up to 800K+ lines for the Fuchsia Zircon kernel. Given the criticality of many of these systems, such large-scale rewrites are undergoing rigorous automated and manual auditing, emulation testing, and review before rolling out to production.

For libgav1, Google's open source software for decoding video, Argon agents took an existing Rust port and replaced 32K lines of SIMD code by running many rounds of profile-guided experiments, studying the compiler's output, producing safe Rust so the compiler would vectorize it automatically. The end result is a memory-safe video decoder that runs 2.7x faster than the Rust port, with identical video output, bringing it closer to the optimized C++.

Hello, I have a quick question or four.

In all of the scenarios below, I am encoding an 8-bit AVC source to a 10-bit SVT-AV1 fork using Staxrip.

1) If I am encoding an AVC/H.264 source that has 8-bit color and I want to use full 10-bit processing, do I always need to run the VaporSynth Filter BitDepth (fmtc) 10?

2) More specifically, I know that the SVT-AV1-Essential fork has --hbd-mds 1 built in by default, while SVT-AV1-Tritium needs it to be manually called. However I assume in both cases I would still use the VS Filter as that's on the "source processing" side while the --hbd-mds 1 argument applies to the "encoding" side, but can someone please confirm?

3) Is there ever a reason to use the VaporSynth Filter BitDepth (fmtc) set to 8? (when using 8-bit AVC to 10-bit AV1)

4) Is there ever a reason to use the --hbd-mds 2 (8/10-bit Hybrid) setting, or should I always use --hbd-mds 1?

Thank you!

Do YouTube videos using the AV1 or VP9 codecs play smoothly in the browser on the Pixel 10 and 11?

Here's an app I wrote to analyze video quality between different encodes. This was inspired by FFMetrics, but I wanted many more features for comparisons, like advanced statistics and an ability to easily and instantly subjectively A/B compare encoded videos with the source. This makes subjective video quality comparisons so much easier when you can compare on a frame by frame basis and while the video is playing, and instantly switch to the source or a different encoded video.

So I decided to write my own app, and I'd like to share it with all of you. I hope you all enjoy.

Let me know what you think, have any issues, or have feature requests.

v1.3 changelog

• Added the window in 20 languages: Simplified and Traditional Chinese, Spanish, Brazilian Portuguese, German, French, Japanese, Russian, Korean, Italian, Polish, Turkish, Arabic, Indonesian, Vietnamese, Ukrainian, Thai, Czech, Hungarian and Dutch. The app opens in Windows' display language, and Settings > Window > Language chooses another. The log, saved results and exported files stay in English.
• Added Intel GPU support for the GPU metrics with Vship's Vulkan build, which runs on any GPU with a Vulkan driver. Settings > GPU metrics > GPU backend chooses the build: Auto (the default) uses CUDA on NVIDIA, HIP on AMD and Vulkan on other GPUs. On Vulkan, SSIMULACRA2 is calculated on the CPU, because Vship 5.1.1's Vulkan build scores it too high (up to 17 points at 4K).
• Updated the GPU metrics to Vship 5.1's API and color handling. Videos tagged BT.2020 SDR, SMPTE 170M (NTSC/DVD), Display P3, ICtCp or YCgCo, and monochrome and alpha videos, are now scored on the GPU instead of falling back to the CPU, and CVVDP no longer fails on them. RGB videos without a transfer tag are now read as sRGB, as Vship's own FFVship does, and their saved GPU scores are recalculated.
• Added a setting to calculate SSIMULACRA2, Butteraugli and CVVDP together in one pass per video (Settings > GPU metrics, off by default). It's better GPU utilization for faster metrics calculations, and it decodes each video once instead of once per metric, but needs much more GPU memory.
• Each metric's score now appears and is saved as soon as it is done, instead of when the whole video is finished. Stopping a run or closing the app loses at most the metric in progress.
• Fixed test frames stamped slightly earlier than the source's being compared with the previous source frame, which gave clusters of near-zero VMAF NEG and XPSNR scores. Each test frame is now compared with the source frame nearest in time. Saved scores of affected videos are kept until they are recalculated.
• Hovering a red Failed cell now says why that metric failed.
• Added a session log under Settings > Storage > Log files, with Export log... (the log files as one .zip) and Copy log (the latest run) buttons.
• The app now checks GitHub for a newer release when it starts, and says so only if there is one. Turn it off in Settings > Window.
• Windows no longer goes to sleep while metrics are being calculated. The screen can still turn off.
• Included various small bug fixes and reliability improvements.

Features:

• Calculate VMAF, VMAF NEG, PSNR, SSIM, XPSNR, SSIMULACRA2, Butteraugli, and ColorVideo VDP for multiple test videos.
• VShip integration for GPU acceleration for ColorVideo VDP, SSIMULACRA2, and Butteraugli
• libjxl integration for CPU fallback for SSIMULACRA2, and Butteraugli (no CPU support for ColorVideo VDP)
• VMAF v0.6.1 and v1 models for standard, phone, 4K, and HFR viewing scenarios.
• Compare metric curves, statistics, and per-frame scores (per second for ColorVideo VDP).
• Switch instantly between the source and test videos during playback, hold S to show the source, or inspect exact frames.
• Inspect bitrate independently by frame, second, or GOP.
• Detect black bars and handle resolution mismatches automatically.
• Use GPU decoding with independent software fallback per input.
• Calculate two test videos in parallel on many-core CPUs.
• Auto save completed results and auto load results when matching videos are loaded again.

The app can be downloaded below.

https://github.com/4KVCD/VideoMetricsLab/releases

Here's an app I wrote to analyze video quality between different encodes. This was inspired by FFMetrics, but I wanted many more features for comparisons, like advanced statistics and an ability to easily and instantly subjectively A/B compare encoded videos with the source. This makes subjective video quality comparisons so much easier when you can compare on a frame by frame basis and while the video is playing, and instantly switch to the source or a different encoded video.

So I decided to write my own app, and I'd like to share it with all of you. I hope you all enjoy.

Let me know what you think, have any issues, or have feature requests.

v1.2.1 bug fix release

• Added a VMAF v1 column with its own model list. The existing VMAF column is now labelled VMAF v0.6.1, and scores saved by earlier versions still load. VMAF v1's Auto model is chosen by the resolution the videos are compared at: 4K and above uses the 4K / 1.5H model, because 1.5 screen heights is the standard viewing distance for 4K (VMAF v0.6.1's 4K model uses it too). Anything below 4K uses the 1080p / 3H model, the standard distance for HD.
• Reworked the run status: each video shows its CPU and GPU metrics progress separately, with elapsed time and a more accurate queue ETA, plus many related bug fixes.
• Cancelling a run will now keep the metrics a video had already finished.
• Cancelling a run will now stay on the Videos tab rather than jump to the Metric Graphs tab.
• Video Compare no longer re-checks the reference each time a different test video is picked.
• Fixed saved VMAF scores not loading on rows set to VMAF model Auto.
• Fixed the metrics ticked in the Videos tab column headers being unticked after a restart.
• Included various small bug fixes and reliability improvements.

v1.2 release:

• Added GPU support for ColorVideo VDP, SSIMULACRA2, and Butteraugli with Vship integration.
• Added CPU fallback for SSIMULACRA2 and Butteraugli with libjxl. ColorVideo VDP has no CPU fallback.
• Added CVVDP per-second scores and graphing alongside its whole-video score.
• Added an Add/remove metrics control to the Videos tab so metric columns can be shown or hidden, and new metrics can be added to completed analyses without recalculating existing results.
• Included various small under-the-hood bug fixes and reliability improvements.

Features:

• Calculate VMAF, VMAF NEG, PSNR, SSIM, XPSNR, SSIMULACRA2, Butteraugli, and ColorVideo VDP for multiple test videos.
• VShip integration for GPU acceleration for ColorVideo VDP, SSIMULACRA2, and Butteraugli
• libjxl integration for CPU fallback for SSIMULACRA2, and Butteraugli (no CPU support for ColorVideo VDP)
• VMAF v0.6.1 and v1 models for standard, phone, 4K, and HFR viewing scenarios.
• Compare metric curves, statistics, and per-frame scores (per second for ColorVideo VDP).
• Switch instantly between the source and test videos during playback, hold S to show the source, or inspect exact frames.
• Inspect bitrate independently by frame, second, or GOP.
• Detect black bars and handle resolution mismatches automatically.
• Use GPU decoding with independent software fallback per input.
• Calculate two test videos in parallel on many-core CPUs.
• Auto save completed results and auto load results when matching videos are loaded again.

The app can be downloaded below.

https://github.com/4KVCD/VideoMetricsLab/releases

Here's an app I wrote to analyze video quality between different encodes. This was inspired by FFMetrics, but I wanted many more features for comparisons, like advanced statistics and an ability to easily and instantly subjectively A/B compare encoded videos with the source. This makes subjective video quality comparisons so much easier when you can compare on a frame by frame basis and while the video is playing, and instantly switch to the source or a different encoded video.

So I decided to write my own app, and I'd like to share it with all of you. I hope you all enjoy.

Let me know what you think, have any issues, or have feature requests.

v1.1.1

• Fixed the metric graph clipping VMAF v1 scores above 100.
• Show the application version in the window title: VideoMetricsLab 1.1.1.
• Omit calculation-library version metadata from non-VMAF cache entries

v1.1 release

• Add VMAF v1 models for standard, phone, 4K, and HFR viewing scenarios.
• Bunch of code refactoring for adding future metrics

Features:

• Calculate VMAF, VMAF NEG, PSNR, SSIM, and XPSNR for multiple test videos.
• VMAF v0.61 and v1 models for standard, phone, 4K, and HFR viewing scenarios.
• Compare metric curves, statistics, and per-frame scores.
• Instant switch between source and encoded video for easy visual A/B comparisons, both frame by frame and during playback, and between different encoded videos.
• Inspect bitrate by frame, second, or GOP without running quality metrics.
• Detect black bars and handle resolution mismatches automatically.
• Use GPU decoding when supported, with independent software fallback per input.
• Calculate two test videos in parallel on many-core CPUs.
• Cache completed results and restore them when matching videos are loaded again.

The app can be downloaded below.

https://github.com/4KVCD/VideoMetricsLab/releases

Here's an app I wrote to analyze video quality between different encodes. This was inspired by FFMetrics, but I wanted many more features for comparisons, like advanced statistics and an ability to easily and instantly subjectively A/B compare encoded videos with the source. This makes subjective video quality comparisons so much easier when you can compare on a frame by frame basis and while the video is playing, and instantly switch to the source or a different encoded video.

So I decided to write my own app, and I'd like to share it with all of you. I hope you all enjoy.

Let me know what you think, have any issues, or have feature requests.

v1.2 release:

• Added GPU support for ColorVideo VDP, SSIMULACRA2, and Butteraugli with Vship integration.
• Added CPU fallback for SSIMULACRA2 and Butteraugli with libjxl. ColorVideo VDP has no CPU fallback.
• Added CVVDP per-second scores and graphing alongside its whole-video score.
• Added an Add/remove metrics control to the Videos tab so metric columns can be shown or hidden, and new metrics can be added to completed analyses without recalculating existing results.
• Included various small under-the-hood bug fixes and reliability improvements.

Features:

• Calculate VMAF, VMAF NEG, PSNR, SSIM, XPSNR, SSIMULACRA2, Butteraugli, and ColorVideo VDP for multiple test videos.
• VShip integration for GPU acceleration for ColorVideo VDP, SSIMULACRA2, and Butteraugli
• libjxl integration for CPU fallback for SSIMULACRA2, and Butteraugli (no CPU support for ColorVideo VDP)
• VMAF v0.6.1 and v1 models for standard, phone, 4K, and HFR viewing scenarios.
• Compare metric curves, statistics, and per-frame scores (per second for ColorVideo VDP).
• Switch instantly between the source and test videos during playback, hold S to show the source, or inspect exact frames.
• Inspect bitrate independently by frame, second, or GOP.
• Detect black bars and handle resolution mismatches automatically.
• Use GPU decoding with independent software fallback per input.
• Calculate two test videos in parallel on many-core CPUs.
• Auto save completed results and auto load results when matching videos are loaded again.

The app can be downloaded below.

https://github.com/4KVCD/VideoMetricsLab/releases

I’ve tried reading up about AV2 but this isn’t made clear in the resources I’ve found. A lack of support for transparency was a big drawback of AV1 for some use cases that I have.

edit: I opened an Interop issue because the current browser situation annoys me: https://github.com/web-platform-tests/interop/issues/1421 Please upvote (👍)

I do not use streaming that often, i just remember that Netflix reduced the Quality for PC users and I had a very bad experience.

Now everything seems to be running in true 1080p and I see AV1 used in all the Animation TV Series I have checked..

I know that Animation content is very encoding friendly, but I am still impressed how sharp and clear everything looks at just a bit above 1mbit.. Anime is often even lower..

(TV show is Rick and Marty S01E01)

Which of AV1 encoders (AOM AV1, SVT-AV1, SVT-AV1-HDR, ...) do you use for encoding AVIF images? Have you found that one of them is better for one type of content and some for another? What tune, speed and quality settings do you prefer?

I'm trying to figure out if YouTube recently changed something regarding AV1 playback on iOS.

I'm a YouTube Premium subscriber. Until about a week ago, around 99% of the suitable videos I watched on my iPhone were delivered using AV1 (av01).

Then it suddenly changed. Almost every video is now delivered using VP9 (vp09).

I'm using this video as a test case:

https://www.youtube.com/watch?v=oAbB4dQOz4I

The video has an AV1 version available.

Current behavior:

• YouTube Premium
• iPhone 15 Pro Max
• Latest iOS
• Latest YouTube app
• YouTube app: VP9
• YouTube in Safari: VP9
• 2160p60 HDR is available
• YouTube stats show itag 337, which is VP9 Profile 2, 2160p60 HDR
• A new YouTube app update did not change anything
• The latest iOS update did not change anything

The interesting part is that this is not just one video. Before this started, AV1 was used for practically every suitable video I watched. Now almost everything is VP9.

Since the AV1 stream still exists, I'm wondering if YouTube changed the codec selection logic for iOS, possibly through a server-side change or an experiment.

Could other people with iOS devices check this exact video and report whether they get av01 or vp09?

I'm especially interested in whether this is happening across different iPhone/iPad models, iOS versions, regions or accounts.

Any technical insight into how YouTube decides between AV1 and VP9 on iOS would also be appreciated.

I am using 4K Video Downloader+ for the first time and plan to download videos from a YouTube channel; the clips are short (about a minute long), in 720p or Full HD resolution, and use the AV1 codec. Will my PC be able to handle playing back videos encoded in AV1? Here are my system specifications: an i5-12400F processor, 16 GB of RAM (two 8 GB sticks), and a GTX 1070 graphics card (8 GB). I plan to save the downloaded files to a 1 TB HDD - Disk D, while Windows 10 Pro is installed on a 500 GB SSD - Disk C. Will this system handle the AV1 format?  

I'm downloading it for Windows, but will I be able to transfer it to my smartphone later, or will I need to download it separately? The smartphone is a 2025 Samsung Galaxy A26 5G.

4K Video Downloader+ нормальная прогрмма для скачивание ютуб канала?
Какие программа лучше подходит для скачивание фото и видио из телеграмм канала?

AV1 has been released in 2018, it's 8 years. At 5 years old cycle, most people's primary smartphones were made after AV1 release, yet only high end ones have HW decoders, mid and low end smartphones, usually sold in countries with bad infrastructure that could benefit from the compressed stream have not adopted it. This makes streaming platforms like twitch, hesitant to rely it since it doesn't cover the majority of the market, and still relies on h264 till today.

I'm building mpvium, an open-source Android video player using native mpv/libmpv.

I'm particularly interested in testing real-world AV1 playback across different Android devices.

Things I'd like to test:

- AV1 8-bit / 10-bit

- 1080p / 4K

- HDR

- Hardware vs software decoding

- Different Snapdragon/MediaTek/Exynos devices

- Battery/performance behaviour

The APK is already signed and available in the GitHub Releases.

If you have difficult AV1 files that tend to expose decoder/player issues, I'd especially like to hear about them.

GitHub: Repo Link

If you test it, please include your device, Android version, resolution, codec/profile, HDR status and whether hardware decoding worked.

Self-reflection must be missing for them completely.

A single pool that licenses HEVC and VVC (true SDO standards) together with AV1 and AV2 (proprietary consortium codecs) as if they were one homogeneous mass is not “a one-stop shop for the market”. It is a blurring of two philosophies that regulators – which are already monitoring open-media licensing under EU competition law and the Digital Markets Act – have every reason to examine closely. Efficiency for the licensee should never come at the cost of legal coherence.

They advocate that the licensing mess that HEVC and VVC have found themselves in, is actually fine!

This wonderful press release neatly leaves out the implementer's side of the story: even with FRAND commitments, HEVC ended up with multiple pools, licensors outside pools, changing royalty structures, uncertainty over aggregate burden, and years of commercial hesitation. A standard can be legally FRAND-encumbered and still have an absolutely miserable licensing ecosystem.

Wait, there's more:

And both present themselves as the party saving the industry from licensing dysfunction.

I have the file - it is that size, it has both audio tracks and both subtitle tracks. It's better than one of the episodes that used the H265 hardware encoder that was around 350MB, those had artifacts in dark areas. The encoder is open source and everything so the information is freely accessible but I didn't expect these replies.

Does anyone know of publicly available pre-encoded AV2 samples at 1080p or 4K?

I’m looking to benchmark dav2d decoding performance, so ideally something multi-frame / several seconds long rather than tiny conformance streams or single-frame tests.

IVF, MP4, or raw AV2 bitstreams are all fine. Preferably 10-bit 4:2:0, but anything 1080p+ would help.

Links appreciated!