● Ffmpeg use cuda executed at unknown time! ffmpeg -version. 1. less space & the same quality. LS h264 H. /ffmpeg -hwaccel cuvid -c:v h264_cuvid -i /data/1920x800. Here is a sample of BAD quality CPU encoding using libx264 and a crf = 63. I would like to go one step further and display those frames directly from the GPU - it would be a pity having to download them to the CPU (as the above sample code This guide includes instructions on how to compile ffmpeg with CUDA support, and may get you started with hardware-accelerated filters. So I try to use nvidia cuda to accelerate it. Some of those encoders are built to use GPUs, some are not. Ffmpeg have to use mps to share the same context as usually multiple encoding/decoding sessions use multiple ffmpeg processes. I have used ffmpeg to transcode with my GPU several times using the command. BUT When I decode this 264 file by my code use 'h264_cuvid' decoder, something problem happens, this is my code: Q A Bug? no New Feature? maybe Version Used 0. Here is some output: For it is necessary to configure FFmpeg with:--enable-cuda-sdk --enable-filter=scale_cuda --enable-filter=thumbnail_cuda We can resize frames at the decoding step then not necessary to use scale_npp filter. ts" -vcodec h264_nvenc -preset slow -level 4. GPU : Quadro P2000 NVIDIA Driver Version: 387. Assuming that you use OpenCV 3. Anyway, I recommend to use NVIDIA Video Codec SDK directly for this purpose. Previous message (by thread): [FFmpeg-user] Using FFMpeg with Nvidia CUDA to crop and scale videos Next message (by thread): [FFmpeg-user] Regarding . The command is following. 2 OS Ubuntu 18. dep, installed the cuda package and the nvidia-352 package, then compiled ffmpeg. 18. It’s part of a personal project to build a distributed compute cluster for handling load balancing and serving of multimedia to different clients, all in as efficient a package as possible. exe, you can encode videos with just this command: ffmpeg. mkv". See opencv/opencv#11220 (comment) This is the reason why I use ffmpeg with cuvid support. 264 decode using CUVID: ffmpeg -c:v h264_cuvid -i input. I use ffmpeg to process some audios as follow, fmpeg -i input. wav -f wav -ar 16000 -ab 12800 -ac 1 output. mp4" -c:v h264_cuvid -gpu:v 1 -preset slow -c copy "c:\testingvids\AEON FLUX 2005 nvidia. This speed is achieved with a Quadro P4000 from NVidia when encoding 1920×1080 movies with -preset slow. Simply follow the examples . You signed in with another tab or window. mkv -vf scale_npp=1280:720 -b:a 320k -c:v h264_nvenc -preset slow -rc vbr_hq -b:v 3M -maxrate:v 4M /data/out. ffmpeg cuda video-encoding ffmpeg-command video-encoder amd-cpu Resources. 0 with CUDA Extensions. Our best hypothesis so far is that it’s a race condition and the speed improvements that we recently did expose this problem. Use nv-codec-headers old version if you want to use on old gpus. ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i input. /ffmpeg -hwaccel cuda -i input -c:v h264_nvenc -preset slow output. Can anyone help cant seem to find how to use hwaccel with the 265 encoder and decoder Ok, by default colab would have ffmpeg using only CPU. yuv works fine, the generated yuv file is ok. HW-assisted encoding is enabled through the use of a specific encoder (for example h264_nvenc). But, for better comparison, we first run FFmpeg with sorry for my bad english i have managed running ffmpeg with cuda support and libfdk-aac. 0 FFMPEG version : 3. Why could that be? For the sake of completeness, here is the relevant code sudo apt remove cuda sudo aot-get autoremove --purge cuda cd /var # Here I removed files like cuda-repo-9-0-local-xxx cd /etc/apt/sources. scale_npp filter may support other conversions (I don't know). FFmpeg is one of the most popular open-source multimedia manipulation tools with a library of plugins that can be applied to various parts of the audio and video processing pipelines and have achieved wide adoption across the world. You'll want to tune the bitrate parameter until it looks acceptable to you. You can also use FFmpeg 5 or 6. I'm trying to speed up the rendering of a video by using the GPU instead of the CPU. 264 videos at various output resolutions and bit rates. Before using scale_cuda, we have to upload the frame from the CPU memory to the GPU memory using hwupload_cuda filter. d # Here I removed files like cuda-9-0-xxx. 1, and add disable_multiplane=1 in the ffmpeg command. mkv "hwdownload,format=p010le,format=yuv420p,hwupload_cuda" downloads frames from hardware to system memory in the original format (in this Does CUDA have support for encoding of lossless images? The format does not need to be PNG, but it does need to be lossless. mp4 -vf fps=1/2 output-%04d. I'm generating many at the same . . Using CUDA (on a Pascal 1050 Ti), I expect the corresponding command to be cuda::videoreader isn't supported anymore and it works only with CUDA <= 6. Is there a way to use the nvenc encoder without using cuda? So, as part of my problem solving process I am trying to use nvenc but without cuda - is that cuda. cuda container as a reference for all required libraries and steps. Hi, ffmpeg with GPU support is not enabled on Jetson platform. Encode video with ffmpeg using CUDA without NVENC. 04 64 bit; ffmpeg 3. Sample decode using CUDA: ffmpeg -hwaccel cuda -i input output Sample decode using CUVID: ffmpeg -c:v h264_cuvid -i input output FFplay supports older option -vcodec hevc_cuvid, but not -c:v hevc_cuvid (though support for -hwaccel was recently added). Some of the arguments of h264_nvenc are different from libx264. One is the crf setting. nv-codec: NVIDIA's GPU accelerated video codecs. I tried to use different commands, but the result was always the same, on Windows and Ubuntu. list. ffmpeg -hwaccel cuvid -c:v hevc_cuvid \\ -i video. The Decklink SDI input is fed RGB 10 bits, which is well handled by ffmpeg with the decklink option -raw_format rgb10, which gets recognized by ffmpeg as 'gbrp10le'. Ask Question Asked 6 years, 4 months ago. First, however, enter nvidia-smi to see whether the container can see your NVIDIA devices. 6: 3651: January 27, 2022 How to convert pix format in hardware when transcoding 10 bit HEVC to h264? I'm trying to use my GPU for video encoding/decoding operations on macOS. -map 0 -map -0:t -filter_complex "scale_cuda=1920:1080:format=yuv420p:interp_algo=lanczos,hwdownload" -fps_mode:v passthrough -c:v h264_nvenc -preset 18 -profile:v high -level 4. We use the libraries that come with ffmpeg for everything else. AutoGen library to perform CUDA decoding. You can always track GPU utilization and memory transfers between host and device by Create high-performance end-to-end hardware-accelerated video processing, 1:N encoding and 1:N transcoding pipeline using built-in filters in FFmpeg; Ability to add your own custom high-performance CUDA filters using the shared CUDA Here is how to use your Nvidia GPU to hardware accelerate video encoding with ffmpeg. Report repository Releases. Using x264 all attempts so far have produced mixed results at best. ffmpeg was installed using sudo apt --no-install-recommends install ffmpeg to keep from installing the desktop specific stuff. ffmpeg -y -vsync 0 -hwaccel cuda -hwaccel_output_format cuda -i 05. 292. /ffmpeg -init_hw_device cuda=cuda FFmpeg build with CUDA support for Linux (especially for Google Colab, updated for NVIDIA driver version 460. 264 / AVC / MPEG-4 AVC / MPEG-4 part 10 (decoders: h264 h264_v4l2m2m h264_qsv ) (encoders: libx264 libx264rgb h264_omx h264_qsv h264_v4l2m2m h264_vaapi ), and the transcoding process shows: [hevc @ 0x561e69691a00] Using auto hwaccel type vaapi with new default device. When we use the thumbnail_cuda filter we can set NV12 as the output format to prevent additional pixel format convertation. Here is the line i'm using. mp4 \ -vf scale_npp=w=426:h=240 -c:v h264_nvenc -profile:v main -b:v 400k -sc_threshold 0 -g 25 \ -c:a aac -b:a 64k -ar 48000 \ -f hls -hls_time 6 -hls_playlist_type vod \ -hls_allow_cache 1 -hls_key_info_file encription. 1 watching. add /user/local/cuda/bin: on the beginn of this file ! cp -r . We've already linked to CUDA through the use of the NVIDIA Face Tracking filter, and just have to extend the API a little bit. I am able to render the video in GPU using the flags -c:v h264_nvenc, I see a short peak in the GPU encoding, but with a long period of computer CPU hight load, I guess preparing the FFmpeg is the leading multimedia framework, able to decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created. 5 (Sierra) //hackintosh if it matters CUDA Toolkit 8. mp4 -hwaccel cuda -hwaccel_output_format cuda -i intermediate2. In order to achive that, I'm compiling the code using the nvidia-cude-10. 04LTS: FFmpeg resize using CUDA scale (filter scale_cuda is GPU accelerated video resizer ), full hardware transcoding example: $ ffmpeg -hwaccel cuvid -c:v h264_cuvid -i INPUT -vf scale_cuda=-1:720 -vcodec h264_nvenc -acodec copy OUTPUT. The reason it's lightning-fast is because it's not actually doing anything: Rather than re-encoding the video stream, it's basically copying the video stream bit-for-bit, out of the old file and into the new file. Note that unlike NVENC or NVDEC, which otherwise have little-to-no GPU performance impact, OpenCL or CUDA accelerated filters will consume GPU resources and could impact your captured application's performance. Must be combined with "CUDA output" Checked. Follow Here is the example command: time ffmpeg -hide_banner -hwaccel cuda -hwaccel_output_format cuda -i source. Reload to refresh your session. Sample decode using CUDA/NVDEC: ffmpeg -hwaccel cuda -i input. ffmpeg; video For several years I've been using a batch file script that utilizes ffmpeg to re-encode videos to h265. And that I had some accelerators: $ ffmpeg -hwaccels -hide_banner Hardware acceleration methods: vdpau cuda vaapi opencl cuvid. 3 on my debian 11 by default, but Shutter Encoder uses a embedded version inside the appimage file. On my test machine, I have a Intel 2600k + Nvidia 970 running in Ubuntu with FFMpeg compiled with cuda (encoder) and libnpp (decoder). 2 devel docker image. 0 FFmpeg Version 7:3. How can i do this? Downloading and Configuring FFmpeg: Downloads the latest FFmpeg source code, configures it with necessary flags for CUDA support, and compiles it. ffmpeg cannot do it, and all the FFmpeg requires separate git repository nvcodec-headers for NV-accelerated ffmpeg build. Im currently using FFMPEG 4. 5. So if you want to use libplacebo with CUDA, you need to compile libplacebo with version v6. exe -i input_file. You may also try accelerated MJPEG decoding by adding -vcodec mjpeg_cuvid before the -i. It takes roughly 1 minute to generate a 10 second timelapse. That is all. The H. scale_cuda=-1:720 means keep the same aspect ratio and match the other argument. mp4 -c:a copy -c:v h264_nvenc -b:v 5M output. ffmpeg -y -vsync 0 -hwaccel cuda -hwaccel_output_format cuda -i input. I am trying to find a way to use the drawbox and drawtext ffmpeg filters to overlay text onto video,and speed this process up using GPU acceleration. The command I was using before: ffmpeg -hide_banner -hwaccel cuda -i "input. The following command reads file input. Replace it it with -c:v h264_nvenc. 264 standard enjoys broad compatibility, with most consumer devices supporting accelerated decoding. py script. We should also use the following arguments (at the beginning): vsync=0, hwaccel='cuda', hwaccel_output_format='cuda'. Basically, get the best quality file, and convert it I'm currently generating timelapse videos using a thread on my CPU with fluent-ffmpeg running on nodejs. I want to use 'overlay_cuda' in filter complex. Discover how to set up the environment and apply it to your video decoding How to use CUDA GPU hardware encoding with ffmpeg to encode h264 and h264 HEVC movies in high quality and highspeed with our optimized parameter settings. . 04. Supported codecs in nvcodec: I am using NVIDIA Quadro P620. This is a Ubuntu 22. I compile ffmpeg follow this post However, there isn't any example to use it with audio. At this point, any pod with the GPU resources set and the right nodeAffinities will schedule on the GPU nodes and have access to the GPUs. T. ffmpeg is the same in that sense. mkv to get good quality-per-bitrate. Video Processing & Optical Flow. avi But i need to crop video file to 16:9 aspect ratio. I see that with newer versions of ffmpeg the line needs to be modified a little to this: FFMPEG a few months ago launched a new version with the new filter “overlay_cuda”, this filter makes the same as the “overlay” but using an Nvidia card for applying it. I am trying to encode a h264 . mkv -c:a copy -c: which means you cannot ask ffmpeg to use CUDA hardware acceleration" according to the one that helped me. #7582 (hwaccel cuvid/nvenc performance degredation when using aq (temporal-aq or spatial-aq) with multiple concurrent encodes) – FFmpeg. Our app is a using FFmpeg to decoder an input video and then CUDA to process frames. mp4 without any hardware acceleration. -init_hw_device cuda:0,primary_ctx=1. These encoders/decoders will only be available if a CUDA installation was found while building the binary. Lastly, ensure that the compiled version of ffmpeg GPU based encoding is specific to a codec/GPU computing standard (CUDA, OpenCL) so you would need to specify what are you using in your case. Choose the second device on the system. nano /etc/enviroment. Run the container mounting the current directory to /workspace processing input. mp4" But the quality is not as good as expected. This is super low quality but fast and provides a small (but useless) file full For GPU CUDA accelerated scaling we may use scale_cuda filter. After discuss with libplacebo author, there has some incompatible with ffmpeg master, CUDA. The only examples I found are from the developer commits but are to put a video or a photo over FFmpeg is the leading multimedia framework, able to decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created. Good luck. ffmpeg -hwaccel cuda -i input output Sample decode using CUVID: ffmpeg -c:v h264_cuvid -i input output Full hardware transcode with NVDEC and NVENC: ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i input -c:v h264_nvenc -preset slow output If ffmpeg was compiled with support for libnpp, it can be used to insert a GPU based scaler into the chain: The output of ffmpeg -codecs shows: DEV. The example command is When using -hwaccel cuda -hwaccel_output_format cuda, the decoding process is CUDA accelerated, and the decoded video is located in the GPU. ZM does not need to be recompiled to use cuda. From empirical comparison I think the bwdif deinterlacing algorithm is superior to yadif, however QTGMC is superior to all of those. ffmpeg -hwaccel cuda -hwaccel_output_format cuda -ss start_timestamp -t to_timestamp -i file_name -vf "fps=30,scale_cuda=1280:720" -c:v h264_nvenc -y output_file Note that the machine running the code has a 4090 This command is then executed via python, which gives it the right timestamps and file paths for each smaller clip in a for loop Try adding -extra_hw_frames 2 after -hwaccel_output_format cuda. - Glyx/colab-ffmpeg-cuda You are right, most decoders, filters and encoders of FFmpeg are runnning on the CPU. arch=compute_86,code=sm_86 is for Ampere GPUs except A100. 3 The NVENC encoders in FFmpeg support CUDA inputs, which also support 4:4:4 and RGBX formats. AutoGen. scale_cuda filter has a format parameter that supports conversion from yuv444 to yuv420p for example, but the filter does not support converting between YUV and RGB. Not strictly FFmpeg related, but as an advise for you to be able to use hugely performant GPU capabilities through OpenCV API. Checklist The results of this collaboration are an extended libvmaf API with GPU support, libvmaf CUDA feature extractors, as well as an accompanying upstream FFmpeg filter, libvmaf_cuda. Modified 6 years As far as I understood all of them just pass the encoding to hardware encoder, without actually using CUDA. or: ffmpeg -hwaccel cuda -loglevel quiet -i input_path. VMAF-CUDA must be built from the source. Why not using scale_cuda filter to replace to software based resizer? You don't need the proprietary npp filter since the cuda impl in ffmpeg is more than enough for you. ffmpeg -hwaccel cuda -i 12. 0 installed NVidia GTX 1080 with latest web driver My question is this - how does a program like Kodi, VLC, or FFMPEG come to make use of these GPUs for actual encoding and decoding? When I do research on how to make use of the Mali-450 GPU, for example, I find some esoteric and poorly documented C-examples of sending compressed frames to the GPU and getting decoded frames back. keyinfo \ -hls_segment_filename f-0-seg-%d. if i got it correctly, I must transfer CUDA pixel from GPU to RAM to get NV12 then convert it to YUV420p (don't know if sw_scale can do it!) then scale it using sw_scale again? while it takes too expensive process to gain a scalable frame with FFMPEG, do you think i should give up on FFMPEG and go to the NVIDIA SDK? if you say FFmpeg is the leading multimedia framework, able to decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created. -c:v hevc_nvenc or h264_nvenc I use ffmpeg to upscale from 1080p to 4k videos and it uses my cpu only 100% and gpu 0-1% utilization as i see from task manager: ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i input. webm file as the source content? I saw another comment to use "-f mp4" , but I'm concerned that might download a file that isn't the best quality, which is what I want. 264 source using ffmpeg with CUDA hardware acceleration. For more information you can see npplib\nppscale definition which will do the CUDA-accelerated format conversion and scaling since ffmpeg 3. the The benchmark tests encoding the target videos into H. /configure and nonfree Messages sorted by: List options of a filter using ffmpeg -h filter=XXXX. Yes, it’s possible to install 440. For the build: FFmpeg build with NVENC and all available CUDA-based filters on Ubuntu 18. x - you should use special OpenCV GPU Api for video decoding. For a given frame of a video that can be decoded with nvdec in ffmpeg, (AVPixelFormat)frame->format will give:. data[i] contain CUdeviceptr pointers exactly as for system memory frames. This code works, but I don't know if I'm doing it correctly. Stability : Instead of forking a ffmpeg process and exchanging data via pipes, you can now interact directly with ffmpeg's C ffmpeg -i input. hwupload_cuda; scale_cuda; scale_npp; thumnail_cuda; Build. It is my command. This post showcases how CUDA-accelerated VMAF (VMAF-CUDA) enables VMAF scores to be calculated on NVIDIA GPUs. Next message (by thread): [FFmpeg-user] Problem when using scale_cuda filter Messages sorted by: On Thu, 21 Mar 2019 at 05:25, Александр via ffmpeg-user < ffmpeg-user at ffmpeg. However, when I try to do the following call: As you see, ffmpeg receives data from standard input. In an older version of ffmpeg (from 2017) I used this line: fmpeg -hwaccel cuvid -i input -c:v hevc_nvenc -preset slow -rc vbr_hq -b:v 4M -c:a aac output. mp4 using the AV1 codec at 8 Mbps and put it into output. mp4-files. Watchers. The following options are recognized: primary_ctx. You can find a link to Nvidia website on how to compile the ffmpeg. 03 and CUDA version 11. E. If the ffmpeg command line works, then zm will too. Remove hwupload_cuda from the beginning of the filter chain. forum1 at ntlworld. 22 CUDA Version : 8. 1 -qmin 10 -qmax 52 "e:\output. x. list/save Now using the GUI software & Updates, in the additional drivers tab, sometimes wouldnt let me change from 390 to 396, so I'm pretty sure I first For the right codecs and for reference, the Stack Overflow post make ffmpeg chose Nvidia CUDA over Intel QSV mentioned that hardware acceleration was working with the following command: ffmpeg -hide_banner -hwaccel cuda -i "input. FFmpeg is the leading multimedia framework, able to decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created. org> wrote: > Hello, I am trying to do full hardware video transcoding with scaling. Without hardware acceleration, a typical command would be ffmpeg -i input. In case we like to decode both input videos using GPU decoder, we have to download the video to the CPU before using concat filter, and upload after:. mp4 FFmpeg is the leading multimedia framework, able to decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created. We will cover the key concepts and provide detailed examples to help you get started. The focus of this article is on using the FFmpeg. Whereas -c:v libx264 (or I guess -c:v h264works) will re-encode the video to a new H264 stream with default settings You may be able to use hardware accelerated decoding. 04 Actual Behavior How GPU-accelerated video processing with ffmpeg? Expected Behavior ffmpeg use G For get video stream packet I'm use ffmpeg-dev libs avcodec, avformat My steps: 1) Open input file: avformat_open_input(&ff_formatContext,in_filename,nullptr,nullptr); Using video frame decoded by FFMPEG via CUDA as texture or In this article, we will explore how to use the FFmpeg. png [FFmpeg-user] Using FFMpeg with Nvidia CUDA to crop and scale videos SMF Forum 1 smf. /configure --enable-cuda --enable-nvenc --enable-cuvid Using the example provided here, I was able to get FFMPEG to decode an HEVC encoded video via CUDA (as evidenced by Task Manager showing me that my test program is using 75% of the GPU). My This article explores the integration of CUDA decode with FFmpeg using FFmpeg. The goal is high quality HDR stream usage with 10 bits. ffmpeg; hardware-acceleration; Share. Before using FFmpeg, it is recommended to refer to the FFmpeg documentation, note the The choice on the filter(s) you can use depend on how you build FFmpeg: Use the proprietary CUDA SDK and you'll get scale_npp and scale_cuda, or stick to an LLVM build without the CUDA SDK and you'll still get scale_cuda. In the following, we build FFmpeg 4 libraries with NVDEC/NVENC support. mp4 -s 224x224 -f image2pipe - -vcodec rawvideo I'm trying to use Ffmpeg for creating a hevc realtime stream from a Decklink input. 3) and cuda, hardware accelerator. Sort by: When using FFmpeg the tool, HW-assisted decoding is enabled using through the -hwaccel option, which enables a specific decoder. I can't share the link as currently I am on mobile, although it should be easy to find on internet. ffmpeg is amongst other things a wrapper for popular codecs like x264 and VP8 for video. Using Vulkan or Cuda to Encode AV1 on prior generation AMD and NVIDIA GPUs Have any of you guys researched using general purpose compute functionality to encode with This will start a daemonset that'll look for GPU enabled nodes and will run the nvidia installer each time a node starts. ts f-0 -c:v copy doesn't run on the GPU. Execute ffmpeg -h encoder=h264_nvenc for getting a list of options. If you want to use on old Nvidia gpu, you can download my binaries, or compile one yourself. The ffmpeg binary is used in some scripts for generating videos from the jpgs. Use FFmpeg command lines such as those in Sections 1:N HWACCEL Transcode with Scaling and 1:N HWACCEL encode from YUV or RAW Data. Use the Dockerfile. It depends on the installed system libraries. png Sample H. mkv. Perhaps a way to use all the cuda/tensor/etc cores to render timelapse videos instead of just relying on the limited nv_enc? ffmpeg; nvenc; Share. 1 Video encoding is OK by using following command . Now I just need to figure out how to make Automator work. I can see there is Create high-performance end-to-end hardware-accelerated video processing, 1:N encoding and 1:N transcoding pipeline using built-in filters in FFmpeg; Ability to add your own custom high-performance CUDA filters using the shared CUDA ffmpeg lets you control quality in a variety of ways. Use the example shown below. Hi all, I’m still struggling with my Jetson Nano 2GB board. † PyTorch / TorchAudio with CUDA support. FFmpeg does not support PTX JIT at this moment, CUDA will Unlock the full potential of your video editing workflow with the powerful combination of FFmpeg and NVIDIA hardware acceleration. mkv -pix_fmt yuv420p10le -c:v libx265 -crf 21 -x265-params profile=main10 out. This standard input is provided by the ffmpeg_gpu_benchmark. For accelerating the scale filter, remove the format=rgba, and I am trying to encode a 10-bit H. For example: ffmpeg -hwaccel_device 0 -hwaccel cuvid -c:v h264_cuvid -i <input> -b:v 2048k -vf scale_npp=1280:-1 -c:v h264_nvenc -y <output> And once you have ffmpeg. See: Using FFmpeg with NVIDIA GPU Once inside the container, as the default user anaconda, you can use the compiler to transcode using hardware acceleration. mp4 and transcodes it to two different H. I want to merge multiple h264 / mp4 files using a complex filter (simplified example): ffmpeg -hwaccel cuvid -c:v h264_cuvid 1:N HWACCEL Transcode with Scaling. Using a self-compiled version of ffmpeg version 6. AV_PIX_FMT_CUDA: HW acceleration through CUDA. hwaccel cuda : Full hardware transcode with NVDEC decoding-hwaccel cuda. 0 stars. Follow these instructions for installation. So, after some (long) time - it is a problem with the old version of ffmpeg - which is the version bundled with Ubuntu 22. Improve this question. Replace format=nv12 with format=yuv420p In your case, you'll need to build FFmpeg from source. That only apply NVIDIA GPUs. VMAF key elementary metrics Hi ffmpeg from git is running OK with cuda 9. Following the merge request opencv/opencv#11481 you can force the video codec ffmpeg uses with the folowing env var : We are developing a commercial product that is using FFMpeg to composite data onto a video stream and encode in h. 8-0ubuntu0. 4. docker build -t ffmpeg . No releases published. mp4. What I am trying to achieve is to accelerate video encoding using plain old CUDA on old pre-Kepler hardware (GTX 570 here To compile FFmpeg, the CUDA toolkit must be installed on the system, though the CUDA toolkit is not needed to run the FFmpeg compiled binary. TorchAudio’s official binary distributions are compiled to work with FFmpeg libraries, and they contain the logic to use hardware decoding/encoding. There are some GPU-accelerated filters, via cuda on Nvidia GPUs, vulkan, etc. mp4 -c:v av1_nvenc -b:v 8M -c:a copy output. 1 OS : CentOS7. To compile FFmpeg, the CUDA toolkit must be installed on the system, though the CUDA toolkit FFmpeg supports GPU acceleration through a feature called CUDA, which is NVIDIA's parallel computing platform and API. The GTX 780 ffmpeg -y -vsync 0 -hwaccel cuda -hwaccel_output_format cuda -i my-video. yadif_cuda V->V Deinterlace CUDA frames. VMAF image feature extractors are ported to CUDA, enabling it to consume images that are decoded using 2. Just to start off I took an existing ffmpeg command that I was running to combine two videos and added -hwaccel cuda and no other changes. 04 I am following the instruction guide from NVIDIA's site to get ffmpeg running using GPU encoding. This will encode input_file. -c:v h264_nvenc tells ffmpeg to use NVENC H264 encoding -hwaccel cuda tells ffmpeg to use NVENC decoding for the input video -hwaccel_output_format cuda tells ffmpeg to keep the output of the NVENC If I do use CUDA acceleration by inputting this ffmpeg -y -vsync 0 -hwaccel cuda -hwaccel_output_format cuda -i D:\torrentz\examplefile. ffplay -vcodec hevc_cuvid file. This was true, but newer ffempeg implementations now use CUVID as a way to call NVENC/NVDEC, which is now reflected in the link provided in the documentation link at the bottom: CUVID for encode and decode is decades old and should be Hi, i dont know if im bothering asking this question, but do you have any news on the issue of using CUDA Hardware acceleration in Linux. mp4 最低限の動作確認終わり エンコードデコードは次回 ffmpeg tells you to use cuda instead of cuvid Everything is based on my experience in transcoding, searching multiple forums, guides, and compiling the source code. It doesn’t seem possible to reinstall CUDA after installing 440. Nothing that could be passed on to production ffmpeg -y -hide_banner -threads 8 -hwaccel cuda -hwaccel_device 1 -hwaccel_output_format cuda -v verbose -i "c:\testingvids\AEON FLUX 2005. 265 using the x264 and x265 open-source libraries in FFmpeg 6. Remember to change the --nvccflags option to match your GPU arch. FFmpeg also offers wrappers for hardware-accelerated decoders and encoders, either provided by the GPU driver (cuvid/nvenc for Nvidia, amf for AMD) or by the operating system (videotoolbox for macOS, ) env: ubuntu 16. /usr/bin/ Start coding or generate with AI. You can use that with a standard -c:v libx264 -preset slow -crf 22 -c:a libopus -b:a 80k output. mkv -vf "hwdownload,format=p010le,format=yuv420p,hwupload_cuda" -c:v hevc_nvenc -preset slow test. I try as follow, but it not work. device is the number of the CUDA device. mp4 -vf "scale_cuda=3840:2160,hwdownload,format=yuv420p" [other options] output. com Wed Sep 11 13:49:40 EEST 2024. Readme Activity. 265. But if I use nvidia-cuda-mps, then there is no performance hit. CUDA has a nvJPEG Library, but JPEG is a lossy format. Forks. mp4 -c:a copy -c:v h264_nvenc -b:v 5M ~/05__01. With ffmpeg and a decent GPU (like a Quadro P4000) the h265/HEVC encoder finaly gets a good speedboost with up to 90fps when encoding HD movies with the below parameter values and 200fps when using the GPU accelerated h264 encoder. Stars. Check the installed ffmpeg version [ ] [ ] Run cell (Ctrl+Enter) cell has not been executed in this session. Is it possible to do this and still remain within the FFMpeg LGPL open source licence? ffmpeg -hwaccel cuda -f gdigrab -framerate 24 -probesize 42M -i desktop -preset ultrafast -pix_fmt yuv420p camera1. All came back ok, also the cuda tests. I'm using my FFMPEG with the suport of my GPU (NVENC) to convert files from my satelite receiver (SD, mpeg2 . ffmpeg -i "e:\input. Note that while using the GPU video encoder and decoder, this command also uses the scaling filter (scale_npp) in FFmpeg for scaling the decoded video output into multiple desired --merge-output-format Does this still use the . const AVPixFmtDescriptor * av_pix_fmt_desc_get(enum AVPixelFormat pix_fmt) Out of curiosity I just ran some tests to get an idea of the difference in quality, if any, between yadif, yadif_cuda, cuvid deint and mcdeint. 12. avi" -c:a copy -ac 1 -c:v h264_nvenc -preset hq -movflags faststart -qp 30 "output. These command lines share the CUDA context across multiple transcode sessions, thereby reducing the CUDA context The question is whether it's possible to use CUDA cores to decode and encode video faster than the hardware engines (NVDEC and NVENC). If you are using L4 (Ada), you should change it to arch=compute_89,code=sm_89. mp4 Then ffmpeg stops transcoding and telling me off: No decoder surfaces left It seems the GPU memory got filled up and not released. I managed to solve it by use -hwaccel_device # instead of -gpu. wav And I need to do it as fast as possible. The test was based on the Big Buck Bunny movie and the procedure should be self-evident from the commands below, but roughly: transcode the original to NV12 lossless, use this as the base for comparison create an Hi dear @Rotem thanks for reply. We would like to use the CUDA toolkit to enable NVidia hardware acceleration in FFMpeg, to take advantage of our graphics card. 5: 3022: March 18, 2023 Ffmpeg: Mixing CPU and GPU processing. I need to concatenate multiple mp4, h264 encoded files into single one together with speed up filter, using GPU HW acceleration. /colab-ffmpeg-cuda/bin/. The log below indicates that it is (trying to) use cuda. Second, check to ensure that directory of ffmpeg is /usr/local/ffmpeg-nvidia by entering which ffmpeg into a shell. ffmpeg -hwaccel cuda -hwaccel_output_format cuda -c:v hevc_cuvid -i INPUT -vf scale_cuda=w=1920:h=-1 -c:v hevc_nvenc -preset default -c:a copy -c:s copy -y OUTPUT A docker container, with ffmpeg that supports scale_cuda among other things - aperim/docker-nvidia-cuda-ffmpeg The same also impacts the video encode pipeline as NPP's scaling functions run off the CUDA cores on the GPU, and as such, the performance impact introduced by the extra load should be analyzed on a case-by case basis to determine if the performance-quality trade-off is acceptable. 04 SERVER (NO desktop, and normally accessed via ssh from other machines on the local network), with an Intel GPU but for some reason ffmpeg refuses to use it. CPU decode VS GPU decode. You will have to compile it on your own for it to use cuda. 0 forks. ffmpeg -hide_banner -loglevel warning -y -hwaccel cuda -hwaccel_output_format cuda -i intermediate1. I followed the instructions (as far as I can tell), installed the NVIDIA SDK local . 264 decoder may only support baseline profile). For AMD and Intel there may be other options. In terms of performance, don't expect much parity between them in terms of performance; both will run on the GPU either way. I have installed CUDA, together with Nvidia driver and configured ffmpeg with the following parameters: I have to burn subtitles based image on video using ffmpeg(v4. However, even when running the CUDA flag -c:v h264_nvenc, I observe ffmpeg and python still take up a lot of CPU time. 264 RTSP video stream to check if we have already succeeded. Using libavcodec, I've got a program that successfully encodes the input stream using avcodec_encode_video2(). mp4 video created from . Running this command completely offloads the work to Nvidia 970 (1% CPU Usage) - ". I am using a NVIDIA GeForce GT 745M Graphics card (GPU:GK107), which is compatible with cuvid as specified by NVIDIA here. mp4 -filter_complex For hardware accelerated encoding use h264_nvenc instead of libx264. m GPU-accelerated video processing integrated into the most popular open-source multimedia tools. 32. mp4" Was failing because it couldn't find the Nvidia adapter. What is the GPU . The results of this collaboration are an extended libvmaf API with GPU support, libvmaf CUDA feature extractors, as well as an accompanying upstream FFmpeg filter, libvmaf_cuda. Is Use Jetson nano as a NVR server possible? AastaLLL April 2, 2019, 3:20am 2. I installed vmaf from the latest commit, ran the tests. The TensorRT filter is enabled by the --enable-libtensorrt option. 31 when purging everything 418 related and all of CUDA, but then it’s no longer possible to build a working ffmpeg using CUDA. (Although, buying a new gpu is better. I’m playiog with this topic with both a VIZI AI board (Atom + Myriad X) and the Jetson Nano 2GB board. Start coding or generate with AI. I didn't see any improvement in It went smoothly when I built ffmpeg following the instructions on the web page. Examples from FFmpeg Wiki: Hardware Acceleration - NVDEC. Reply reply Hi, I have been trying to getting libvmaf to work with ffmpeg; but using cuda for feature extraction. I can run the following command line, and everything is working perfectly. When transcoding, no matter which gpu I select with -gpu option, ffmpeg always use gpu #0. jpg images using a 1070ti nvidia cuda power, having a a crossfade transition between each image. From the reference materials listed below, I have been unsuccessful in finding a way to do so, but I wanted to check with the community to see if there is are additional approaches. Now ffmpeg -hwaccel cuda works the first time. 87. After desisting for now to make OpenCV work with CUDA (will recover this topic in the future), the next thing is to try to get ffmpeg to encode video using the CUDA magic. Without decoder, I get about 13% CPU usage per feed -c:v h264_cuvid is calling CUVID, which is slower and less efficient than NVENC. See the shell scripts. It seemed that the GPU wasn’t detected or recognized properly. AutoGen library to perform CUDA decoding, and we will assume that you have a basic understanding of CUDA and FFmpeg. VMAF key elementary metrics How to use ffmpeg scale_cuda to implement 10bit transcode? Video Processing & Optical Flow. 2 build whih cuda cuvid libnpp use ffmpeg cmd: ffmpeg -vsync 0 -c:v h264_cuvid -i test. Please use MMAPI or ffmpeg -i input -s 224x224 -pix_fmt bgr24 -vcodec rawvideo -an -sn -f image2pipe - But when I'm trying to use some NVIDIA GPU encoding, I'm always getting noisy images. hwaccel_output_format cuda : Full hardware transcode with NVENC Encoding-hwaccel_output_format cuda. 264 -f rawvideo test. Examples: -init_hw_device cuda:1. However, I suspect that the reason it hangs is because its trying to use cuda. Each decoder may have specific limitations (for example an H. To utilize GPU acceleration with FFmpeg, you need a compatible NVIDIA GPU and the Several CUDA filters exist in FFmpeg that can be used as templates to implement your own high-performance CUDA filter. mp4 to output. Is there a similar image encoding library in CUDA for a lossless format (that is also integrated with ffmpeg)? Edit: Some more context. I am using Debian 10 Buster 64bit, and the card I am using is Nvidia Gainward GTX960. Notably, as far as I know libx264 and libx265 are CPU only A video game may do some parts using a GPU, but other parts using a CPU. hevc_nvenc/h264 : uses CUDA for accelerated h264 or h265(hevc) encoding. 31 (without going back to 418. These two formats are not supported by the DirectX backend, or the OpenGL backend, so using CUDA benefits us here. mp4 -f image2pipe -pix_fmt rgb24 -f rawvideo pipe:1. ) Old gcc means you can't compile new ffmpeg. OS: MacOS 10. For the supported and available hardware accelerated features you can achieve with a current generation NVENC-capable NVIDIA GPU, see this answer. Second issue is that format=nv12 is incompatible with the overlay filter. Here is what I use with FFMPEG to test out 1 minute of the But it did not help have anybody tried using cuda with ffmpeg? 1 Like. cuda, ffmpeg. avi -c:v h264_nvenc output. 264 and H. If it doesn't work, try increasing it up to 10 and see if it makes any difference (in my computer, it works with 4). mp4" This produced a 828x processing speed: But for taking that same file and compressing it I seem to only get a ~8x Speed. Then with cuda but it does not convert to h265 ffmpeg -vsync 0 -hwaccel cuvid -c:v h264_cuvid -i input. 0 on the CPU and the NVENC accelerator when using the Nvidia GPU. I need to compile FFmepg with specific configuration, that support nvidia cuda hardware acceleration. Share Add a Comment. 2) with pre-built binaries. In the case of the Vizi board, I have On Ubuntu 14. This project is intended to have some useful pre-defined command line commands to use with ffmpeg and CUDA Topics. mp4" Easy to use: You don't have to tackle the complex video processing problems concerning FFmpeg anymore. I am trying to use the nvenc nvidia hw accel encoder. Then i compiled ffmpeg with some minimal I have this same issue. ffmpeg is a whole lot of encoders and decoders and filters in one software package. Use old. nv-codec-headers Installation: Clones the nv-codec-headers repository and installs it, providing headers for Nvidia GPU accelerated video encoding/decoding. g. So they need to be ones that have cuda installed. If you have to stick with FFmpeg, the nnedi filter is definitely superior but at the cost of massive Hey guys! Wanted to post/begin a thread sharing my progress on building a cuda based ffmpeg filter designed to enable tonemaping of HDR content to an HDR colour space. Intel HD Graphics supports vpp_qsv filter. mp4 Full hardware transcode with NVDEC and NVENC: ffmpeg am I doing it right? So much time has passed since I use ffmpeg to convert clips on my home web server, now that mp4 (h264 & aac) is the current overall standard (works on every console, smartphone, smartTV, pc) I decided to convert my old clips from various digital cameras to to this new container/codecs. mp4 -c:v libx265 -crf 26 -preset fast -c:a aac -b:a 128k output. Choose the first device and use the primary device context I'm using an NVIDIA Pascal GPU under Windows 7 and am trying to use FFmpeg to control the h264_nvenc, rather than the NVIDIA SDK directly. Usage. 00). 3. Below is an example of drawtext and I am trying to use Nvidia hardware acceleration for FFmpeg using cuvid. 前言 本文章是针对 Windows 10 + Nvidia + FFMPEG 的，Linux、老版本 Windows 以及其他系统仅供参考 第一步 根据你的显卡型号，安装适合的 cuda 查看显卡支持的 cuda 版本 这里 可以下载旧版本的 cuda 安图所示，下载并安装，安装过程就一直下一步都行 The problem is that it doesn’t happen with cuda-gdb or compute-sanitizer. You signed out in another tab or window. I am trying to decode a video using the NVIDIA cuvid hardware acceleration with ffmpeg. After installation, we could decode a real-time H. It's still running on the CPU. This in-depth tutorial is How to concatenate two MP4 files using FFmpeg? shows how, including with inputs where the inputs are different formats or even resolutions and need rescaling or filtering. 1 -b:v 13000K -rc cbr -c:a copy -c:s copy Apparently i've solved by using latest ffmpeg (v7) and this command:-fps_mode:v Is there a way to use the CUDA cores (or other non-NVENC-chip aspects) of a GPU to help do video encoding? The context is either 1) being able to encode even faster / more streams than if just relying on the NVENC chip, 2) helping get around the 3 encode limitation on some GPUs, and/or 3) using GPU resources to help with encoding on GPUs which do not have a NVENC chip For reference that's the command I'm using: ffmpeg -loglevel quiet -i input_path. You switched accounts on another tab or window. > > Here is my console command: > ffmpeg FFmpeg libraries compiled with NVDEC/NVENC support. First off, it is much faster — about 5x faster in my case, although that varies with quality settings. However, when conducting basic tests, problems occurred. If set to 1, uses the primary device context instead of creating a new one. TS-Files) into h264 . I found on the FFMPEG website description of the filter, but no examples of how to use it. mp4 I tried the above code but it is not working because my computer doesn't have CUDA or GPU support. 265 video from a 8-bit H. I compiled ffmpeg with the following flags:. faxnoicwwcagzodceuulbpmjkwotptdtdopndtoqglhldmemcussqfmfs