The AV1 codec has become very popular.
I hope you will add "NEW" codec/filter ("drivers") with AV1 support?
av1 encoders Hybrid currently supports atm.:
- aomenc
- rav1ve
- svt-av1
- QSVEnc (requires Intel GPU; only in dev build available atm.) (Supported on Windows only atm.)
I plan to add av1 support through NVEncC once I get my hands on one of the NVIDIA 40xx cards, but both the 4090 and 4080 cards are way out of my budget range (unless I win the lottery).
This should already cover every free available av1 encoder I know of.
=> If you can name additional av1 encoders that are free, have a command line interface and supports piped input, I can look into supporting them.
Cu Selur
you didn't understand me again
fresh versions needed
not these old ones - they are experimental - not stable
Dev version should be up-to-date, but you can simply replace the binaries if the command line interface didn't change.
Cu Selur
(12.11.2022, 10:23)Selur Wrote: [ -> ]Dev version should be up-to-date, but you can simply replace the binaries if the command line interface didn't change.
Cu Selur
Would a simple file replacement help?
without adjustments in the settings?
O_O.........
Anyone tried the --fp-mt=1 usage for better Threading yet? Will it speed up encoding a bit 6Core /12 Threads? Will the Video Quality drop like settings up tile columns and rows in AOM? I dont want to use chunked encoding yet, because i only have 16 GB of RAM, when i use chunked encoding with filters on, 2 gb ram left, vspipe will eat all of my RAM.
Greetings
I only did a few tests with SD and 4k content and couldn't find any speed gain when using --fp-mt=1, not sure whether there are any other requirements for it to do something. (Side note: when using chunked encoding, make sure to lower the threads count)
Cu Selur
Hi Selur, why lower the Threads count? even if i set full threads, AOM is not using all of my thread to 100% CPU Load is pending about 80%, with 2 chunks and still 12 Threads, i can get 100% cpu load all the time.
More threads mean more memory usage and overhead.
If you run multiple encodes in parallel, you might want to lower the per job threads count.