In the two months since the release of Version 0.8.0, a lot of bugs have been discovered – which now have been fixed with Version 0.8.1! Let’s take a closer look at the things that have been fixed.
Update: Update 0.8.2 has been released fixing the newly discovered issues in 0.8.1. The links in the post have been updated.
Update: 0.8.3 is out, and the links have been updated.
Improving the Installer experience on Windows
This had been on the table for a while, and finally made it in. Due to the excessive flood of people not reading the installation instructions and asking the same question – usually within seconds of the same question being answered – the installation process had to become a bit more automatic.With that in mind, I went to town on the installer.
Due to an excessive amount of channels required for StreamFX, I’ve decided to split it off into its own Discord server. You can join it using this link, and enjoy all the new features in it. Make sure to read the rules and select your roles according to what you want to do!
The Server features dedicated roles for each category of tasks, in order to better help users do things. Each role also has a dedicated releases channel for their own content in order to spread the content to other creators that are less skilled at the task.
You can also now advertise your content in the dedicated channels for it, such as your stream or your YouTube channel.
StreamFX has grown into one of the most used plugins for OBS Studio, often being called essential for big and small creators alike. And yet, there is a massive problem facing StreamFX: A lack of funding. Like any project, StreamFX can’t survive without it, so where do we go from here?
Currently the funding come from Github Sponsors, Twitch Subscriptions, Patreon, and my own job. The first three make up around $110 in total (+- some amount), which I’m really thankful for. While $110 is not a lot, it does help a bit, and reduces my time spent at work ever so slightly.
Dual-PC streaming with x264 has been the leader in H264 encoding for streaming for years – up until NVIDIA released their new Turing generation. This new generation of GPUs with a brand new encoder brough comparable quality to x264 medium (or better), has next to no impact on gaming (unlike an NDI-based dual-PC setup) and is much more affordable.
Let’s take a look at the necessary changes to get your NVENC encoding to look comparable to x264 medium (or better).
These settings are for an older FFmpeg version!
The settings provided here are for FFmpeg 4.3.x and earlier, and OBS Studio currently ships with FFmpeg 4.2.x. FFmpeg 4.4 has different Presets and Tuning values, which by default already reach the quality described here, requiring no additional custom configuration.
Setting up NVENC (for Streaming)
With modern OBS Studio, you have two options: NVENC NVENC H.264 (new) or StreamFXs NVIDIA NVENC H264/AVC (via FFmpeg). The latter has more options to configure, but both will give you comparable quality to x264 medium – as long as you have a Turing GPU encoder. You can check here to see if your GPU has a Turing encoder – note that the GTX 1650 Super also has a Turing encoder.
Ever since the day that we’ve been able to push sample rate higher than 44.1kHz, this question has appeared: What is the best sample rate for Audio, and can you actually hear the difference between 48kHz and 96kHz (or higher) sample rates?
Before we get into this, note that I am not an audio engineer, or a scientist. I am a software developer, who is often too curious for his own good, resulting in weird new projects – like StreamFX. So take this with a grain of salt, and if you know better, do feel free to contact me!
Performance is important, and even more so in live streaming. Every streamer and content creator absolutely hates it to see the FPS number dip below the configured number – especially if it is a far drop below. But what can you actually do against that as a streamer or content creator?
If you haven’t heard of RTX Voice, it’s basically “Krisp” in Discord but with less shitty audio quality. It’s based on Tensor, which can fall back onto CUDA hardware, but runs best on RTX due to the hardware accelerated Tensor cores on it. You can find a guide on how to set it up here on Nvidias own website.
A short while ago I teased a new filter live on stream, and now that the Nvidia counterpart for it is publicly released I can finally go into more detail on what it does, why it is useful, and how you too can now use it on your Nvidia GeForce RTX hardware.