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Fix Soft Inpaint for AnimateDiff #15148

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merged 3 commits into from
Mar 6, 2024
Merged

Fix Soft Inpaint for AnimateDiff #15148

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73e635c
fix
continue-revolution Mar 6, 2024
7f766cd
Merge branch 'dev' into conrevo/fix-soft-inpaint
continue-revolution Mar 6, 2024
7d59b3b
rm comment
continue-revolution Mar 6, 2024
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26 changes: 20 additions & 6 deletions extensions-builtin/soft-inpainting/scripts/soft_inpainting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,10 +57,14 @@ def latent_blend(settings, a, b, t):

# NOTE: We use inplace operations wherever possible.

# [4][w][h] to [1][4][w][h]
t2 = t.unsqueeze(0)
# [4][w][h] to [1][1][w][h] - the [4] seem redundant.
t3 = t[0].unsqueeze(0).unsqueeze(0)
if len(t.shape) == 3:
# [4][w][h] to [1][4][w][h]
t2 = t.unsqueeze(0)
# [4][w][h] to [1][1][w][h] - the [4] seem redundant.
t3 = t[0].unsqueeze(0).unsqueeze(0)
else:
t2 = t
t3 = t[:, 0][:, None]

one_minus_t2 = 1 - t2
one_minus_t3 = 1 - t3
Expand Down Expand Up @@ -135,7 +139,10 @@ def apply_adaptive_masks(
from PIL import Image, ImageOps, ImageFilter

# TODO: Bias the blending according to the latent mask, add adjustable parameter for bias control.
latent_mask = nmask[0].float()
if len(nmask.shape) == 3:
latent_mask = nmask[0].float()
else:
latent_mask = nmask[:, 0].float()
# convert the original mask into a form we use to scale distances for thresholding
mask_scalar = 1 - (torch.clamp(latent_mask, min=0, max=1) ** (settings.mask_blend_scale / 2))
mask_scalar = (0.5 * (1 - settings.composite_mask_influence)
Expand All @@ -157,7 +164,14 @@ def apply_adaptive_masks(
percentile_min=0.25, percentile_max=0.75, min_width=1)

# The distance at which opacity of original decreases to 50%
half_weighted_distance = settings.composite_difference_threshold * mask_scalar
if len(mask_scalar.shape) == 3:
if mask_scalar.shape[0] > i:
half_weighted_distance = settings.composite_difference_threshold * mask_scalar[i]
else:
half_weighted_distance = settings.composite_difference_threshold * mask_scalar[0]
else:
half_weighted_distance = settings.composite_difference_threshold * mask_scalar

converted_mask = converted_mask / half_weighted_distance

converted_mask = 1 / (1 + converted_mask ** settings.composite_difference_contrast)
Expand Down
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