Libvpx Installation and Configuration Guide

Libvpx is a free and open-source video codec that's widely used in various applications. It's a great alternative to other video codecs, offering high-quality video compression.

To get started with Libvpx, you'll need to install it on your system. The installation process is relatively straightforward, and you can follow the instructions in the Libvpx Installation section to get it up and running.

One of the key benefits of Libvpx is its ability to handle a wide range of video formats, including VP8 and VP9. This makes it a versatile choice for developers who need to work with different types of video content.

Before you start installing Libvpx, make sure you have the necessary dependencies installed on your system. The Libvpx Requirements section outlines the specific dependencies you'll need to meet.

Installation can be a straightforward process. You can install libvpx by running the following commands.

To test the results, issue LD_LIBRARY_PATH=. make test, which will download many files as part of its test process. This test suite will use all available cores for a few parts of it.

Alternatively, libvpx may be available when searching "vpxenc" or "libvpx" in your Linux or MacOS package manager.

To build libvpx from source, you'll need to configure it first. This is done by running the configure command, which allows for different options to be enabled and disabled.

To install libvpx, you'll need to run a few commands in your terminal. The first step is to install libvpx by running the following commands.

You can test the results by issuing the command `LD_LIBRARY_PATH=. make test`, which will download many files as part of its test process and use all available cores.

The `LD_LIBRARY_PATH=.:` is needed for the test suite to use the library that was just built, so don't forget to include it.

To see the options for configuring libvpx, run `./configure --help`, which will show you all the available options.

Some options you may want to use include disabling VP8 encoding and vpxdec (decoder) with `--disable-vp8 --disable-vp9-decoder --disable-vp8-decoder`.

If you want to prioritize smaller encoder binary size over encoding speed, use `--enable-small`.

For Windows compilation with MinGW, you may need to use `--target=x86_64-win64-gcc`, and for MacOS, use `--target=arm64-darwin22-gcc`.

Here are some additional options you can use:

Installing Binary is a relatively straightforward process for Linux and MacOS users. You can find the necessary packages by searching for "vpxenc" or "libvpx" in their respective package managers.

For Linux users, this is a great way to get started. It's a quick and easy way to install the required software.

You can then use the package manager to download and install the necessary packages. This will save you time and effort in the long run.

MacOS users will also find this method helpful. It's a great way to install the software without having to manually download and install each component.

Once you've installed the packages, you can start using the software right away. This is a big advantage over manual installation methods.

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Libvpx is used by major OTT video services including YouTube, Netflix, Amazon, JW Player, Brightcove, and Telestream, among which are the biggest sources of internet traffic with Netflix alone accounting for nearly a third of all internet traffic in the United States as of 2017.

There are alternatives for decoding VP8 and VP9, both commercial and closed source as well as open source. For encoding there are only commercial alternatives and some unfinished experimental software for VP8 including xvp8 as of 2016.

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To configure libvpx, you can use various ./configure options to either speed up compilation or drop unwanted features. You can disable VP8 encoding and the vpxdec (decoder) to be compiled using the --disable-vp8 --disable-vp9-decoder --disable-vp8-decoder option.

For Windows compilation with MinGW, you may need to use --target=x86_64-win64-gcc and --target=arm64-darwin22-gcc for MacOS. Here are some other options you may find useful:

To run unit tests, you can use make. For example, to run the decoder test, run the command as shown in the libvpx unit tests section.

The output will provide you with the results of the test, allowing you to see if the test passed or failed.

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libvpx is used by major OTT video services, including YouTube, Netflix, Amazon, JW Player, Brightcove, and Telestream.

These services are among the biggest sources of internet traffic, with Netflix alone accounting for nearly a third of all internet traffic in the United States as of 2017.

libvpx is a free video codec, and it's widely used in the industry.

There are alternatives for decoding VP8 and VP9, both commercial and closed source as well as open source.

Here are some key players in the video codec market:

Building in a dedicated directory is recommended by the libvpx developers, so it's a good idea to create a separate directory for building.

The --disable-static switch prevents the installation of static versions of the libraries, which is useful if you don't need them.

Disabling static builds can also save you some space on your hard drive.

The --disable-vp8 switch prevents building support for the VP8 codec, so if you don't need it, you can disable it.

Similarly, the --disable-vp9 switch prevents building support for the VP9 codec.

If you're building on a non-x86 or x86-64 system, you can use the --target=generic-gnu switch to disable optimizations specific to those architectures.

vpxenc supports a variety of color spaces, including YUV420P, YUVA420P, YUV422P, YUV440P, YUV444P, GBRP, YUV420P10LE, YUV422P10LE, YUV440P10LE, YUV444P10LE, and GBRP10LE.

The supported color spaces have different chroma subsampling rates, such as 4:2:0, 4:2:2, and 4:4:0. YUV420P, for example, uses 4:2:0 chroma subsampling.

Some color spaces have an alpha channel, like YUVA420P, which is used for transparency. YUVA420P is an 8-bit color space with an alpha channel.

The supported color spaces also have different bit depths, ranging from 8-bit to 12-bit. For instance, YUV420P and YUV422P are both 8-bit color spaces.

Here's a summary of the supported color spaces:

Libvpx offers a compelling option for delivering high resolution video on supported platforms due to its royalty-free nature, which provides a significant improvement over H.264 encoded by x264, especially at high resolutions like UHD.

You can benchmark either the encoding or decoding processes, and for performance benchmarking, you can select video encoding either on-demand or live stream.

To get started, you'll need to adjust the paths to the y4m files in the commands below, as the video files are large. You can also copy them to the current directory.

Try running the standard bit depth command with different --cpu-used values, such as --cpu-used=2, to see the results.

The FFmpeg project's ffvp8 has improved performance by 22 to over 66% compared to the initial release of libvpx.

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Video Encoding is a critical step in preparing your video for distribution. You can experiment with different number of processors to find the optimal balance between encoding speed and video quality.

For on-demand video encoding, you can try running with the --cpu-used argument to vary the number from 2 to 6. Lower numbers indicate better quality but longer encoding time, and a reasonable range of quality settings is 0-4 inclusive.

You can also experiment with different number of processors for live stream video encoding, using the --cpus-used in the range from 5 to 9. For high bit depth, it's recommended to run with a higher number of processors to achieve better results.

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Video Encoding is a crucial step in preparing videos for distribution. You can experiment with different encoding settings to achieve the best balance between quality and speed.

For on-demand encoding, you can adjust the number of processors used to encode your video. Try running with the --good flag and varying the --cpu-used argument from 2 to 6 to see how it affects performance.

Lower numbers on the --cpu-used flag indicate better quality but longer encoding time. For on-demand encoding, a reasonable range of quality settings is 0-4 inclusive.

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High bit depth encoding can be more demanding on your system. For standard bit depth with 8 CPUs, start by running with the following command.

In contrast, live stream encoding requires a different approach. You can experiment with different numbers of processors using the --cpus-used flag in the range from 5 to 9.

For live stream encoding, a reasonable range of quality settings is 5-9. Lower numbers on the --cpus-used flag still indicate better quality but longer encoding time, which can be a concern for live streams.

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VP9 is a popular video encoding format that's been around for a while, but its default parameters in vpxenc are not exactly optimal.

The default parameters in vpxenc are misconfigured, which can hurt coding efficiency at a relatively low cost.

To get the most out of VP9, it's recommended to use the optimal parameters, which have been found to be efficient.

However, it's worth noting that VP9 Profile 2 isn't compatible with many hardware-accelerated VP9 decoding implementations.

Activating alternate reference frames can improve encoding efficiency, and it's done by setting the auto-alt-ref parameter.

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Libvpx is written in C and assembly language, which is a clever combination that helps it run efficiently.

The choice of C and assembly language is a deliberate one, allowing libvpx to tap into the raw power of assembly code while still benefiting from the high-level abstraction of C.

As of 2015, libvpx did not have complete SIMD coverage, which is an important consideration for anyone looking to use it for video encoding or decoding.

Dependencies are a crucial part of any project, and understanding what's required can make all the difference.

Some dependencies are specific versions of tools, like yasm-1.3.0 or NASM-2.16.03, which are necessary for certain tasks.

Having the right dependencies in place can save you a lot of time and frustration in the long run.

libvpx is written in C and assembly language.

This is a deliberate choice, as it allows for fine-grained control over the code.

As of 2015, libvpx does not have complete SIMD coverage.

FFmpeg is a powerful tool that supports the WebM format, specifically through the use of the libvpx library for VP8 and libvpx-vp9 for VP9. To check if you have it, run the command `ffmpeg -h encoder=libvpx` or `ffmpeg -h encoder=libvpx-vp9`.

The WebM format is a royalty-free alternative to other video formats like H.264, designed for high-quality compression and efficient streaming.

Non-FFmpeg standard VP8/VP9 parameters are not supported, so you'll need to use the FFmpeg library to work with these codecs.

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FFmpeg is a powerful tool for encoding video and audio files, and it's particularly useful for working with WebM files. You can use FFmpeg to check if you have the vpxenc encoder available, which is necessary for encoding VP8 and VP9 video.

To check if you have the vpxenc encoder for VP8, run the command ffmpeg -h encoder=libvpx. If you have it installed, you'll see the available options for VP8 encoding. The same command can be used to check for VP9 encoding by replacing libvpx with libvpx-vp9.

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WebM is a media file format designed for the web, wrapping video streams compressed with the VP8 or VP9 codec, and audio streams compressed with the Vorbis or Opus codec.

Google developed this open standard to provide a royalty-free alternative to other video formats like H.264, aiming for high-quality compression and efficient streaming.

The format has gained widespread adoption due to its performance, open nature, and the fact that it’s backed by big names in tech.

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Libvpx implements single-pass and two-pass encoding modes, with either bitrate or quality target settings.

One of the key features of libvpx is its asymmetric codec, which means encoding takes much longer than decoding.

This allows for more efficient encoding, but it also introduces latency, which can hurt real-time performance.

You can configure libvpx to use a lookahead of up to 25 frames, which improves compression efficiency but also adds latency.

libvpx has a mode that uses the maximum CPU resources possible, keeping the encoding speed almost exactly equivalent to the playback speed, without sacrificing quality.

This mode is ideal for applications where high quality is a priority and some latency is acceptable.

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