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reduce blur when using latent mirroring

This commit is contained in:
Sean Sube 2024-01-28 13:09:33 -06:00
parent 256714b661
commit 964000e3a6
Signed by: ssube
GPG Key ID: 3EED7B957D362AF1
1 changed files with 6 additions and 6 deletions
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12
api/onnx_web/diffusers/patches/scheduler.py
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@ -39,8 +39,8 @@ class SchedulerPatch:
axis_of_symmetry = 3
expand_dims = (0, 1, 2)
white_point = 0
black_point = result.prev_sample.shape[axis_of_symmetry] // 8
white_point = 2
black_point = result.prev_sample.shape[axis_of_symmetry] // 4
center_line = result.prev_sample.shape[axis_of_symmetry] // 2
gradient = linear_gradient(
@ -48,19 +48,19 @@ class SchedulerPatch:
)
latents = result.prev_sample.numpy()
gradiated_latents = np.multiply(latents, gradient)
# gradiated_latents = np.multiply(latents, gradient)
inverse_gradiated_latents = np.multiply(
np.flip(latents, axis=axis_of_symmetry), gradient
)
latents += gradiated_latents + inverse_gradiated_latents
latents += inverse_gradiated_latents
mask = np.ones_like(latents).astype(np.float32)
gradiated_mask = np.multiply(mask, gradient)
# gradiated_mask = np.multiply(mask, gradient)
# flipping the mask would do nothing, we need to flip the gradient for this one
inverse_gradiated_mask = np.multiply(
mask, np.flip(gradient, axis=axis_of_symmetry)
)
mask += gradiated_mask + inverse_gradiated_mask
mask += inverse_gradiated_mask
latents = np.where(mask > 0, latents / mask, latents)