I am working on a project which captures screen and encodes it. I can already capture screen using desktop duplication API (Win8+). Using the API I can get ID3D11Texture2D textures and transfer them from GPU to CPU and then use libx264 to encode them.
However, pulling textures from GPU to CPU can be a bottle neck which potentially can decrease the fps. Also libx264 takes up CPU cycles (depending on quality) to encode frames. I am looking for encoding ID3D11Texture2D textures in GPU itself instead of using CPU for encoding as an optimization.
I have already checked the documentation and some sample codes but I have had no success. I would appreciate if someone could point me to some resource that does exactly what I want reliably.
Video encoders, hardware and software, might be available in different form factors. Windows itself offers extensible APIs with choice of encoders, and then additional encoders might be available as libraries and SDKs. You are already using one of such libraries (x264). Hardware encoders are typically vendor-specific and depend on available hardware, which is involved directly in the process of encoding. If you are interested in solution for specific hardware, it might make sense to check for respective SDK.
Otherwise, typical generic interface for hardware backed video encoding in Windows is Media Foundation Transform (MFT). Microsoft provides stock software only H.264 video encoder which is unlikely to give any advantage over x264, except the fact that it shares MFT interface with other options. Video hardware drivers, however, would often install additional MFTs for the hardware available, which add more MFTs backed by hardware implementation. Examples of such are:
Intel® Quick Sync Video H.264 Encoder MFT
NVIDIA H.264 Encoder MFT
AMDh264Encoder
Offered by different vendors, they offer similar functionality and your using these MFTs to encode H.264 is a good way to take advantage of hardware video encoding with a wide range of hardware.
See also:
Registering and Enumerating MFTs
Basic MFT Processing Model
You have to check if sharing texture between GPU encoder and DirectX is possible.
I know it's possible to share texture between Nvidia Decoder and DirectX, because i've done it successfully. Nvidia has some interop capacity, so first, look if you can share texture to do all things in GPU.
With Nvidia you can do this : Nvidia Decoding->DirectX Display in GPU.
Check if DirectX Display->Nvidia Enconding is possible (knowing nvidia offers Interop)
For Intel and ATI, i don't know if they provide interop with DirectX.
The main thing to know is to check if you can interop your DirectX texture with GPU encoder texture.
Related
I'm developing a VoD application as a white label product that runs in a SaaS context using K8s. To enable streaming, I take the input video and re-convert it into HLS segments in multiple version and codecs to reach maximum compatibility.
Yesterday I started implementing AV1 as codec, as it will in near future detach h264 as it's more efficient with the same level of compatibility across all the available browsers.
That was the point where things started to get strange, as I want to have this codec instead of h264 ^^.
If you take a look at the following doc pages from ffmpeg: https://trac.ffmpeg.org/wiki/Encode/AV1
You will notice that there are 3 main encoders available to handle encoding to av1. These are: libaom, SVT-AV1 and rav1e. No matter which one of these I try, the performance is slow, even slower than with HEVC. Recently I came along a news article about Netflix and that they are upgrading their library to AV1. If I take a look at the numbers of media elements Netflix offers, the amount is just huge, and I really don't understand how they did it. From what I know, SVT-AV1 is developed by Netflix in cooperation with Intel, So I assume they somehow rely on hardware encoding using an Intel CPU extension.
Does somebody maybe know more and how they did it? I really can't imagine that they just do CPU only encoding. A movie would take days to get encoded.
Thanks in advance
Encoding quality and quality differs heavily between all encoders. SVT-AV1 is the fastest but looks like garbage. For real-time encoding you should probably use GPU's. Intels GPU's don't really put out great quality AV1 encodes though, Nvidia's H265 is basically the same quality.
With Nvidia and AMD soon getting AV1 encoding hardware support (currently drivers are a bit lacking but it's already possible on Nvidia). AMD GPU's coming out for it soon.
My application do encoding of captured frame from GDI or DXGI method. currently i am doing encoding with help x264 library.
AFAIK x264 is software based library, i want to do encoding with help of GPU, so it can save CPU cycles and hope speed also will be faster.
After searching, I found a H.264 Video Encoder MFT which is doing h264 encoding.
But couple of questions are answered for me.
1) is It faster than x264 encoding library?
2) can bitmap frame be encoded with help this MFT?
- i have seen only MFVideoFormat_I420, MFVideoFormat_IYUV, MFVideoFormat_NV12, MFVideoFormat_YUY2, MFVideoFormat_YV12 these formats are supported
3) is it hardware accelerated(mean it's using CPU or GPU)?
- Initially my understanding was it uses GPU but i get confused after reading this post MFT Encoder (h264) High CPU utilization.
4) can H.264 Video Encoder MFT be used stand alone without using sink writer, as i have to sent data on network?
5) is there any other alternative in windows?
It might be some questions are very silly, please feel free to edit.
Media Foundation H.264 Video Encoder is software encoder. From my [subjective] experience it slower than x264 and, perhaps more important, x264 offers wider range of settings, specifically when it comes to choose modes on the speed over quality end of the range. Either way, stock MS encoder is not hardware accelerated.
However, there might be other MFTs available (typically installed with respective hardware drivers) that do hardware accelerated H.264 encoding. You can discover them by enumerating MFTs, perhaps most popular is Intel Quick Sync Video (QSV) Encoder.
HardwareVideoEncoderTransform app does the enumeration and provides you with relevant details:
Typical input is NV12, some offer other input choices (such as e.g. 32-bit RGB). If you need other formats, you will have to pre-convert the input.
Hardware backed encoders CPU consumption is low, and their efficiency depends on the hardware implementation. Yes, you can use them standalone, entirely standalone or wrapped as DirectShow filter and included in normal DirectShow pipeline.
Alternate H.264 encoders are typically SDK based, or wrappers over those SDKs in DirectShow/MFT form factors because vendors package their implementation in well-known forms already familiar to multimedia developers.
I'm programming video capturing app and need to have 2 input sources (USB cams) to record from at the same time.
When I record only the raw footage simultaneously without compression at is working quite well (Low CPU load, no video lags), but when the compression is turned on the CPU is very high and the footage is lagging.
How to solve it? Or how to tune-up the settings so that it can be accomplished?
Note: the Raw streams are to big and thus cannot be used, otherwise I would not bother with compression at all and just leave it as it is.
The AVFoundation framework in its current configuration is setup to provide HW acceleration only for one source at time. For multiple accelerated sources one need to go deeper to VideoToolbox framework and even deeper.
I have a machine with 2x3 3ghz dual-core xeon and 4x10krpm scsi 320 disks in raid0.
The capture card is an osprey 560 64 bit pci card.
Operating system is currently Windows Server 2003.
The video-stream that I can open with VLC using direct show is rather nice quality.
However, trying to save this video-stream without loss of quality has proven quite difficult,
using the h264 codec I am able to achieve a satisfying quality, however, all 4 cores jump to 100% load after a few second and then it start dropping frames, the machine is not powerful enough for realtime encoding. I've not been able to achieve satisfying mpeg1 or 4 quality, no matter which bitrate I set..
Thing is, the disks in this machine are pretty fast even by todays standard, and they are bored.. I don't care about disk-usage, I want quality.
I have searched in vain for a way to pump that beautiful videostream that I see in VLC onto the disk for later encoding, I reckon the disks would be fast enough, or maybe something which would apply a light compression, enough that the disks can keep up, but not so much as to loose visible quality.
I have tried FFMPEG as it seems capable of streaming a yuv4 stream down to the disk, but ofcause FFMPEG is unable to open the dshow device ( same error as this guy Ffmpeg streaming from capturing device Osprey 450e fails )
Please recommend a capable and (preferably) software which can do this.
I finally found it out, it is deceptively simple:
Just uncheck the "transcode" option in the window where you can select an encoding preset.
2 gigabytes per minutes is a low price to pay for finally getting those precious memories off of old videotapes in the quality they deserve.
I have a potential job which will require me to do some video encoding with FFMPEG and x264. I'll have a series of files which I'll need to encode once, then I'll be able to bring down the instances. Since I'm not really sure of the resource utilization of x264 and FFMPEG, what kind of instances should I get? I'm thinking either a
High-CPU Extra Large Instance
7 GB of memory
20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: c1.xlarge
or, alternatively a
Cluster GPU Quadruple Extra Large Instance
22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge
What should I use? Does x264/FFMPEG perform better with faster/more CPUs or does it really pound the GPU more? In any case, it seems that the Cluster GPU seems to be the higher performance instance. What should I prefer?
Ffmpeg recently added support for VAAPI and VDPAU, but this allows it to use the GPU only for decoding of H.264 video. For encoding, it uses the CPU.
The short answer to CPU/GPU is, it depends on how you use ffmpeg to do the H264 encoding.
Also, you are confusing the H264 and x264. H264 is the video codec standard and x264 is one implementation of H264 standard. x264 is so popular, so sometimes it has become synonymous and confused with H264. The reason that I point that out is x264 is a software-based implementation of H264, which means it will only use the CPU cores for all the processes. There will be no GPU usage in your use case when you use x264 for video encoding.
That being said, maybe what you are trying to ask is whether to go for
hardware-based implementation of H264 (which uses the GPU), or
software-based implementation of H264 (which uses the CPU)
There are several implementations available for each available. Ffmpeg already has a nice page on this. If you are planning to use the Nvidia GPU instances, then you would need to compile FFmpeg with NVENC support to get the hardware implementation. Using GPUs/CPUs to efficiently do all your transcoding process is an art itself.
So in short, x264 will not use GPU. If you want to use GPU, you need to use hardware implementations of the encoders. Which implementation is better largely depends upon your use case and what you care about (quality, cost, turnaround time, etc.)
My background/ Disclaimer: I work as a Senior Engineer at Bitmovin. We solve this "cluster/resource" allocation engineering problem, among many many many other problems, to extract the best possible video quality out of a given bitrate. And in the end, we offer APIs where you can just simply plug them into your workflow. The views expressed here are my own.
In the present, Amazon EC2 offers (some) GPU accelerated instances using modern NVIDIA GPUs, meaning that you can take advantage of NVENC on them.
You are probably better off using a service like zencoder.com, they have an excellent API and the quality you will get out of it will most probably be better than hours of fiddling with Ffmpeg parameters optimisation.