text2video utility

a tool for leveraging text2image tools such as StableDiffusion for generating videos.

Mainly based on PyTTI and deforum, but adding and focusing around:

• designed around a CLI interface with well-structured and very versatile YAML configuration
• audio-reactivity and other multi-modality to come
• PyTTI style functions for most generative parameters
• extensible design for adding arbitrary mechanisms for generating animations

usage

installation

• prerequisite: Install python3.10+
• create venv: python3 -m venv venv
• source venv: source venv/Scripts/activate (or source venv/bin/activate on linux/macOS)
• install requirements: pip install -r requirements.txt
• get the remaining dependencies that don't come with wheels/proper build systems: ./init.sh (or just copy the few git clone commands from the file on windows)

general usage

• use https://github.com/AUTOMATIC1111/stable-diffusion-webui
• add the --api startup flag (in webui.sh or webui.bat or however you launch it) to expose the REST API (you can verify this by going to http://localhost:7860/docs and ensure there is a /sdapi/... endpoint there)
• Set your mechanism to api and configure the host parameter (if running locally it's always just http://localhost:7860)
• ensure web-ui is running
• check out the examples or the doc and build your config
• make sure the venv is sourced (see above)
• Run your scenario with python3 -cp config -cn=yourconfig main.py where -cp specifies the path to your config directory and -cn specifies which config to run.

Creating the final video

Once you have generated your frames, pyttv's job is done. Encoding to a video file is done by other tools.

A useful tool to use is Flowframes or similar tools that use RIFE interpolation or other decent interpolation mechanisms.

rife-ncnn-vulkan seems to work on macOS (M1).

If you just want to encode your frames directly to a video file, you can of course use ffmpeg. cd into your output frame directory and run

cat *.png | ffmpeg -framerate 18 -f image2pipe -i - -c:v libx264 -pix_fmt yuv420p out.mp4

where 18 is to be replaced by your fps of course and out.mp4 is the output filename.

or to encode in a lossless format:

ffmpeg -framerate 18 -i directory\%05d.png -c:v copy output.mkv

Appending audio

ffmpeg -i out.mp4 -i audio.flac out_audio.mp4

Appending audio with an offset + limited duration

Example: Append audio, but the audio gets offset by 55s (-ss) and the audio duration is 5 seconds:

ffmpeg -i out.mp4 -ss 00:00:55.0 -t 00:00:05.0 -i audio.flac out_audio.mp4

Upscaling

If you created your video at a lower resolution, decent tools are RealESRGAN and UIs for it, e.g. cupscale.

Of course you can also use the WebUI for this, either by running a text conditioned upscale with batch img2img mode + SD upscale script or effectively only running ESRGAN by setting the denoising strength to 0.

macOS notes

If you use an M1 mac, use torch_device: cpu in your configs. unfortunately the depth model currently does not work directly on the mps device.