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Update Latent Upscale by Factor

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This commit is contained in:
Jordan Thompson
2023-04-10 22:31:09 -07:00
parent 6236f335ef
commit 1867844edf
1 changed files with 13 additions and 4 deletions
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WAS_Node_Suite.py
+13 -4
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@@ -3600,8 +3600,8 @@ class WAS_Latent_Upscale:
@classmethod
def INPUT_TYPES(cls):
return {"required": {"samples": ("LATENT",), "mode": (["bilinear", "bicubic"],),
"factor": ("FLOAT", {"default": 2.0, "min": 0.1, "max": 8.0, "step": 0.1}),
return {"required": {"samples": ("LATENT",), "mode": (["area", "bicubic", "bilinear", "nearest"],),
"factor": ("FLOAT", {"default": 2.0, "min": 0.1, "max": 8.0, "step": 0.01}),
"align": (["true", "false"], )}}
RETURN_TYPES = ("LATENT",)
FUNCTION = "latent_upscale"
@@ -3609,9 +3609,18 @@ class WAS_Latent_Upscale:
CATEGORY = "WAS Suite/Latent/Transform"
def latent_upscale(self, samples, mode, factor, align):
valid_modes = ["area", "bicubic", "bilinear", "nearest"]
if mode not in valid_modes:
raise ValueError(f"\033[34mWAS NS\033[0m Error: Invalid interpolation mode `{mode}` selected. Valid modes are: {', '.join(valid_modes)}")
align = True if align == 'true' else False
s = samples.copy()
s["samples"] = torch.nn.functional.interpolate(
s['samples'], scale_factor=factor, mode=mode, align_corners=(True if align == 'true' else False))
shape = s['samples'].shape
size = tuple(int(round(dim * factor)) for dim in shape[-2:])
if mode in ['linear', 'bilinear', 'bicubic', 'trilinear']:
s["samples"] = torch.nn.functional.interpolate(
s['samples'], size=size, mode=mode, align_corners=align)
else:
s["samples"] = torch.nn.functional.interpolate(s['samples'], size=size, mode=mode)
return (s,)
# LATENT NOISE INJECTION NODE