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asymmetric-tiling-sd-webui
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Change from custom script to extension. 

Extend to support turning tiling on and off mid-generation.
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tjm 2022-11-18 17:42:54 +00:00
parent 76c8bfcf64
commit b4470ddc38
2 changed files with 42 additions and 21 deletions
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6
README.md
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@ -1,11 +1,13 @@
# Asymmetric Tiling for stable-diffusion-webui
A custom script for [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) to configure seamless image tiling independently for the X and Y axes.
An always visible script extension for [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) to configure seamless image tiling independently for the X and Y axes.
To use, add [asymmetric_tiling.py](asymmetric_tiling.py) to your `scripts` directory in stable-diffusion-webui, restart your server, select `Asymmetric tiling` in the script dropdown, and check `Tile X` or `Tile Y` as desired. While this script is active, the `Tiling` checkbox in the main UI will be ignored.
To use, install this repository from the "Extensions" tab in stable-diffusion-webui, restart your server, open the `Asymmetric tiling` foldout on txt2img or img2img, and make it active, and check `Tile X` or `Tile Y` as desired. While this script is active, the `Tiling` checkbox in the main UI will be ignored.
Like existing tiling options this won't guarantee seamless tiling 100% of the time, but it should manage it for most prompts. You can check that images tile seamlessly using online tools like [Seamless Texture Check](https://www.pycheung.com/checker/).
For the old, non-extension version of this script, use the "classic_script" branch.
## X axis tiling examples
![00817-3274117678-midnight cityscape, stunning environment, wide-angle, massive scale, landscape, panoramic, lush vegetation, idyllic](https://user-images.githubusercontent.com/19196175/195132862-8c050327-92f3-44a4-9c02-0f11cce0b609.png)
![01064-1316547214-(((domino run))), domino toppling, line of standing dominoes, domino cascade, domino effect, black dominos](https://user-images.githubusercontent.com/19196175/195137782-e72fc69a-14f1-4ae7-bac2-219734509aea.png)

45
asymmetric_tiling.py → scripts/asymmetric_tiling.py
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@ -1,5 +1,6 @@
import modules.scripts
import modules.sd_hijack
import modules.shared
import gradio
from modules.processing import process_images
@ -19,39 +20,52 @@ class Script(modules.scripts.Script):
return "Asymmetric tiling"
# Override from modules.scripts.Script
def ui(self, is_img2img):
tileX = gradio.Checkbox(True, label="Tile X")
tileY = gradio.Checkbox(False, label="Tile Y")
return [tileX, tileY]
def show(self, is_img2img):
return modules.scripts.AlwaysVisible
# Override from modules.scripts.Script
def run(self, p, tileX, tileY):
def ui(self, is_img2img):
with gradio.Accordion("Asymmetric tiling", open=False):
active = gradio.Checkbox(False, label="Active")
tileX = gradio.Checkbox(True, label="Tile X")
tileY = gradio.Checkbox(False, label="Tile Y")
startStep = gradio.Number(0, label="Start tiling from step N", precision=0)
stopStep = gradio.Number(-1, label="Stop tiling after step N (-1: Don't stop)", precision=0)
return [active, tileX, tileY, startStep, stopStep]
# Override from modules.scripts.Script
def process(self, p, active, tileX, tileY, startStep, stopStep):
if (active):
# Record tiling options chosen for each axis.
p.extra_generation_params = {
"Tile X": tileX,
"Tile Y": tileY,
"Start Tiling From Step": startStep,
"Stop Tiling After Step": stopStep,
}
try:
# Modify the model's Conv2D layers to perform our chosen tiling.
self.__hijackConv2DMethods(tileX, tileY)
self.__hijackConv2DMethods(tileX, tileY, startStep, stopStep)
else:
# Restore model behaviour to normal.
self.__restoreConv2DMethods()
# Process images as normal.
return process_images(p)
finally:
# Restore model behaviour to normal, even if something went wrong during processing.
def postprocess(self, *args):
# Restore model behaviour to normal.
self.__restoreConv2DMethods()
# [Private]
# Go through all the "Conv2D" layers in the model and patch them to use the requested asymmetric tiling mode.
def __hijackConv2DMethods(self, tileX: bool, tileY: bool):
def __hijackConv2DMethods(self, tileX: bool, tileY: bool, startStep: int, stopStep: int):
for layer in modules.sd_hijack.model_hijack.layers:
if type(layer) == Conv2d:
layer.padding_modeX = 'circular' if tileX else 'constant'
layer.padding_modeY = 'circular' if tileY else 'constant'
layer.paddingX = (layer._reversed_padding_repeated_twice[0], layer._reversed_padding_repeated_twice[1], 0, 0)
layer.paddingY = (0, 0, layer._reversed_padding_repeated_twice[2], layer._reversed_padding_repeated_twice[3])
layer.paddingStartStep = startStep
layer.paddingStopStep = stopStep
layer._conv_forward = Script.__replacementConv2DConvForward.__get__(layer, Conv2d)
# [Private]
@ -69,6 +83,11 @@ class Script(modules.scripts.Script):
# paddingX (tuple, cached copy of _reversed_padding_repeated_twice with the last two values zeroed)
# paddingY (tuple, cached copy of _reversed_padding_repeated_twice with the first two values zeroed)
def __replacementConv2DConvForward(self, input: Tensor, weight: Tensor, bias: Optional[Tensor]):
step = modules.shared.state.sampling_step
if ((self.paddingStartStep < 0 or step >= self.paddingStartStep) and (self.paddingStopStep < 0 or step <= self.paddingStopStep)):
working = F.pad(input, self.paddingX, mode=self.padding_modeX)
working = F.pad(working, self.paddingY, mode=self.padding_modeY)
else:
working = F.pad(input, self.paddingX, mode='constant')
working = F.pad(working, self.paddingY, mode='constant')
return F.conv2d(working, weight, bias, self.stride, _pair(0), self.dilation, self.groups)