# ComfyUI-sonar
Very WIP and not very well tested implementation of Sonar sampling for [ComfyUI](https://github.com/comfyanonymous/ComfyUI). Currently it may not be even close to working _properly_ but it does produce pretty reasonable results.
Only supports Euler and Euler Ancestral sampling.
## Description
See https://github.com/Kahsolt/stable-diffusion-webui-sonar for a more in-depth explanation.
The `direction` parameter should (unless I screwed it up) work like setting sign to positive or negative: `1.0` is positive, `-1.0` is negative. You can also potentially play with fractional values.
Like the original documentation says, you normally would not want to set `momentum` to a value below `0.85`. The default values are considered reasonable, doing stuff like using a negative direction may not produce good results.
## Usage
The most flexible way to use this is with a custom sampler:
You can also just choose `sonar_euler`, `sonar_euler_ancestral` or `sonar_dpmpp_sde` from the normal samplers list (will use the default settings). I personally recommend using the custom sampler approach and the ancestral version.
## Nodes
1. `SamplerSonarEuler` — Custom sampler node that combines Euler sampling and momentum and optionally guidance. A bit boring compared to the ancestral version but it has predictability going for it.
2. `SamplerSonarEulerAncestral` — Ancestral version of the above. Same features, just with ancestral Euler.
4. `SonarGuidanceConfig` — You can optionally plug this into the Sonar sampler nodes. See the [Guidance](#guidance) section below.
5. `NoisyLatentLike` — If you give it a latent (or latent batch) it'll return a noisy latent of the same shape. Allows specifying all the custom noise types except `brownian` which has some special requirements. Provided just because the noise generation functions are conveniently available. You can also use this as a reference latent with `SonarGuidanceConfig` node and depending on the strength it can act like variation seed (you'd change the seed in the `NoisyLatentLike` node). *Note*: The seed stuff may or may not work correctly.
6. `SamplerSonarDPMPPSDE` — This one is extra experimental but it is an attempt to add moment and guidance to the DPM++ SDE sampler. It may not work correctly but you can sample stuff with it and get interesting results.
## Parameters
Very abbreviated section. The init type can make a big difference. If you use `RANDOM` you can get away with setting `direction` to high values (like up to `2.25` or so) and absurdly low values (like `-30.0`). It's also possible to set `momentum` and `momentum_hist` to negative values, although whether it's a good idea...
## Guidance
You can try the `SamplerSonarNaive` sampler which has an optional latent input. The guidance _probably_ isn't working correctly and the implementation definitely isn't exactly the same as the original A1111 version but it still might be fun to play with. The `linear` guidance type is a lot more sensitive to the `guidance_factor` than the `euler` type. For `euler`, reasonable values are around `0.01` to `0.1`, for `linear` reasonable values are more like `0.001` to `0.02`. It is also possible to set guidance factor to a negative value, I've found this results in high contrast and very vivid colors.
It is possible to set the start and end steps guidance is activate. Rather than setting a low guidance and using it for the whole generation, it's also possible to set high guidance and end it after a relatively low number of steps.
Without guidance it should basically work the same as the ancestral Euler version. There are some example images in the [Examples](#examples) section below.
**Note**: The reference latent needs to be the same size as the one being sampled. Also note that step numbers in the step range are 1-based and inclusive, so 1 is the first step.
## Noise
I basically just copied a bunch of noise functions without really knowing what they do. The main thing I can say is they produce a semi-reasonable result and it's different from the other noise samplers. See [Credits](#credits) below.
1. `gaussian`: This is the default noise type.
2. `uniform`: Might enhance background details?
3. `brownian`: This is the noise type SDE samplers use.
4. `perlin`
5. `studentt`: There's a comment that says it may enhance subject details. It seemed to produce a fairly dark result.
6. `studentt_test`: An experiment that may be removed, it doesn't seem to be adding enough noise. You can possibly compensate by increasing `s_noise`.
7. `pink`
8. `highres_pyramid`: Not extensively tested, but it is slower than the other noise types. I would guess it does something like enhance details.
You can scroll down to the the [Examples](#examples) section near the bottom to see some example generations with different noise types.
## Credits
Original Sonar Sampler implementation (for A1111): https://github.com/Kahsolt/stable-diffusion-webui-sonar
My version basically just rips off this Sonar sampler implementation for Diffusers: https://github.com/alexblattner/modified-euler-samplers-for-sonar-diffusers/
Noise generation functions copied from https://github.com/Clybius/ComfyUI-Extra-Samplers with only minor modifications. I may have broken some of them in the process _or_ they may not have been suitable for use and I took them anyway. If they don't work it is not a reflection on the original source.
## Examples
### Guidance
Expand guidance example images
#### Positive
Using the `linear` guidance type and `guidance_factor=0.02`. The reference image was a red and blue checkboard pattern.
#### Negative
Using the `linear` guidance type and `guidance_factor=-0.015`. The reference image was a red and blue checkboard pattern.
### Noise Types (img2img)
These were generated with `s_noise=1.05` to make the noise effect more pronounced, 30 steps at `0.66` denoise, sonar settings increased slightly to enhance the effect (`momentum=0.9, momentum_hist=0.85, direction=1.0, momentum_init=ZERO`). It is probably easier to compare using these as the image _mostly_ stays the same as the sonar sampler settings change.
Expand renoise example images
#### Base
Base image - no Sonar Sampler steps.
#### Euler A
Normal (non-sonar) Eular A. Not really a comparison with noise (think it would use gaussian) but with the difference in effect from momentum.
#### Gaussian
#### Brownian
#### Perlin
#### Uniform
#### Highres Pyramid
#### Pink
#### StudentT
#### StudentT_test
### Noise Types (Initial Generations)
These were generated with `s_noise=1.1` to make the noise effect more pronounced, default sonar settings (`momentum=0.95, momentum_hist=0.75, direction=1.0, momentum_init=ZERO`). It may be harder to see the noise effects since the composition can change a lot in initial generations.
Expand initial generation example images
#### Gaussian
#### Brownian
#### Perlin
#### Uniform
#### Highres Pyramid
#### Pink
#### StudentT
#### StudentT_test
