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Turn the loopback denoise strength change factor into a parameter rather than hardcoding to 0.95. Set the default to 1.

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rewbs
2022-09-08 12:02:06 +00:00
parent 61785cef65
commit ed01f69542
3 changed files with 13 additions and 5 deletions
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modules/img2img.py
+6 -3
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@@ -11,7 +11,7 @@ from modules.ui import plaintext_to_html
import modules.images as images
import modules.scripts
def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, height: int, width: int, resize_mode: int, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, denoising_strength_change_factor: float, seed: int, height: int, width: int, resize_mode: int, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
is_inpaint = mode == 1
is_loopback = mode == 2
is_upscale = mode == 3
@@ -50,7 +50,10 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
denoising_strength=denoising_strength,
inpaint_full_res=inpaint_full_res,
inpainting_mask_invert=inpainting_mask_invert,
extra_generation_params={"Denoising Strength": denoising_strength}
extra_generation_params={
"Denoising strength": denoising_strength,
"Denoising strength change factor": denoising_strength_change_factor
}
)
if is_loopback:
@@ -99,7 +102,7 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
p.init_images = [init_img]
p.seed = processed.seed + 1
p.denoising_strength = max(p.denoising_strength * 0.95, 0.1)
p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
history.append(processed.images[0])
grid = images.image_grid(history, batch_size, rows=1)