Cuda accelerated tonemap Filter

[FCLC]

Initial idea of using POCL as a cuda translation layer isnt viable because of POCL not working with image formats on cuda.

Currently reaching out to Yasroslav Pogrebnyak, the developer of the VF_overlay_cuda ffmpeg filter.

Reaching out to nyanmisaka. Seem's to have a lot of experience working on FFmpeg filters and frankly knows more than I do.

In addition to this, collaborating with Ed Borasky to confirm function on jetson platforms.

vf_tonemap_cuda.txt
(renamed from .c to .txt to make github happy )

Missing: tonemap.cu with proper kernel side code. this is easy once I know how to properly call the cuda kernel side from the ffmpeg side.

Standard stride blocks should work, define total amount of blocks using height. most resolution will be 16:9, so by using height parameter, we have a higher chance of hitting divisible by 3 cleanly, so we can take advantage of cuda language data structure.

Other option is taking the R G and B value of a given pixel which is guaranteed to be *3. this might also help for other tone mapping algorithms that use relative offset from local peak luma as input for tonemapping output

[FCLC]

major bodge, but the new version of /cuda_filter/vf_scale_cuda.cu should be able to do rein hard tonemapping. the below is an extract from the ffmpeg devel mailing list relevant to this:

For ease of developement, I've kept everything the same including the name of the filter, only changing the function within the file. This is very much a bodge to facilitate development. As such, for testing, this file should replace the vf_scale_cuda.cu file in ffmpeg/libavfilter/vf_scale_cuda.cu

FFmpeg should then be compiled as standard for cuda filters and should be called as you would call the standard vf_scale_cuda filter.
The command would be similar to:
ffmpeg -y -vsync 0 -hwaccel cuda -hwaccel_output_format cuda -i input.mp4 -vf scale_cuda=Source_width:Source_Height -c:a copy -c:v h264_nvenc -b:v 5M output.mp4

The above should decode in hardware, tonemap the frame on gpu and re-encode in hardware at a given bitrate.

[FCLC]

Used overlay filter as base instead of scale- seems much better for my purposes. reach out to @znmeb to ask for a test on his side.

syntax will be:
ffmpeg -i INPUT -i INPUT -filter_complex 'hwupload_cuda,overlay_cuda' OUTPUT

This is a bodge for now, since it's only modifying the output of the cuda kernel itself

to use it, replace ffmpeg/libavfilter/vf_overlay_cuda.cu with this file: https://github.com/Camofelix/Jetson_ffmpeg_trancode_cluster/blob/master/cuda_filter/vf_overlay_cuda.cu

It compiles fine, but can't test without a nano for actual usage.

will require to self build:

git fetch ffmpeg source code

make clean

./configure --enable-nonfree --enable-cuda

mv ~/path/to/new/file ~/path/to/ffmpeg/libavfilter/vf_overlay_cuda.cu

make -j

get coffee

ffmpeg -i INPUT -i INPUT -filter_complex 'hwupload_cuda,overlay_cuda' OUTPUT

ffplay output

is output different?

test file: https://4kmedia.org/lg-new-york-hdr-uhd-4k-demo/

[FCLC]

Further update:
Currently concerned about if the jetson will be able to use the standard library of Cuda filters in tandem with decoding and encoding, ideally without making too many memory copies.

[AnterCreeper]

In my test, opencl is necessary.
cuda accelerated filter is usable.

[AnterCreeper]

you just need to

1. git clone nv-codec-headers
2. build ffmpeg with --enable-cuda --enable-cuda-nvcc
3. enjoy
   however, the only usable filters is scale_cuda and yadif_cuda😅
   maybe i need to backport some features. like tonemap_cuda etc.

[FCLC]

you just need to

1. git clone nv-codec-headers

2. build ffmpeg with --enable-cuda --enable-cuda-nvcc

3. enjoy

however, the only usable filters is scale_cuda and yadif_cuda😅

maybe i need to backport some features. like tonemap_cuda etc.

I haven't looked at this project in a while, been working on other GPGPUrelated things.

Have they ported the cuda filters to work on the nano?

[AnterCreeper]

I don't know. I just test and finally build successfully.

[AnterCreeper]

The speed......😅 Not too bad. And the GPU usage is low.
h264 1080p -> h265 720p 6Mbps

[AnterCreeper]

Command:

sudo ffmpeg -init_hw_device cuda=gpu:0.0 -filter_hw_device gpu -c:v h264_nvmpi -i /mnt/source/Paprika.2006.JAPANESE.1080p.BluRay.x264.DTS-FGT.mkv -vf "format=yuv420p,hwupload,scale_cuda=1280:720,hwdownload,format=yuv420p" -c:v hevc_nvmpi -b:v 6000k -preset medium -profile:v high -acodec ac3 output.mp4

[AnterCreeper]

Also what i should say is that my device is throttled due to low current and voltage.😅 The power is utter garbage.