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Merge pull request #6299 from stysmmaker/feat/latent-upscale-modes

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Add more latent upscale modes
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AUTOMATIC1111 2023-01-04 13:47:36 +03:00 committed by GitHub
commit 6281c1bdb4
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2 changed files with 6 additions and 3 deletions
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2
modules/processing.py
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@ -713,7 +713,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
for i in range(samples.shape[0]): for i in range(samples.shape[0]):
save_intermediate(samples, i) save_intermediate(samples, i)
samples = torch.nn.functional.interpolate(samples, size=(target_height // opt_f, target_width // opt_f), mode=latent_scale_mode) samples = torch.nn.functional.interpolate(samples, size=(target_height // opt_f, target_width // opt_f), mode=latent_scale_mode["mode"], antialias=latent_scale_mode["antialias"])
# Avoid making the inpainting conditioning unless necessary as # Avoid making the inpainting conditioning unless necessary as
# this does need some extra compute to decode / encode the image again. # this does need some extra compute to decode / encode the image again.

7
modules/shared.py
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@ -564,8 +564,11 @@ if os.path.exists(config_filename):
latent_upscale_default_mode = "Latent" latent_upscale_default_mode = "Latent"
latent_upscale_modes = { latent_upscale_modes = {
"Latent": "bilinear", "Latent": {"mode": "bilinear", "antialias": False},
"Latent (nearest)": "nearest", "Latent (antialiased)": {"mode": "bilinear", "antialias": True},
"Latent (bicubic)": {"mode": "bicubic", "antialias": False},
"Latent (bicubic antialiased)": {"mode": "bicubic", "antialias": True},
"Latent (nearest)": {"mode": "nearest", "antialias": False},
} }
sd_upscalers = [] sd_upscalers = []