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Add support for the stable diffusion x4 upscaling model.

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This is an old model.

Load the checkpoint like a regular one and use the new
SD_4XUpscale_Conditioning node.
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comfyanonymous
2024-01-03 03:30:39 -05:00
parent 2c4e92a98b
commit a7874d1a8b
6 changed files with 103 additions and 1 deletions
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21
comfy/model_base.py
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@@ -364,3 +364,24 @@ class Stable_Zero123(BaseModel):
cross_attn = self.cc_projection(cross_attn)
out['c_crossattn'] = comfy.conds.CONDCrossAttn(cross_attn)
return out
class SD_X4Upscaler(BaseModel):
def __init__(self, model_config, model_type=ModelType.V_PREDICTION, device=None):
super().__init__(model_config, model_type, device=device)
def extra_conds(self, **kwargs):
out = {}
image = kwargs.get("concat_image", None)
noise = kwargs.get("noise", None)
if image is None:
image = torch.zeros_like(noise)[:,:3]
if image.shape[1:] != noise.shape[1:]:
image = utils.common_upscale(image, noise.shape[-1], noise.shape[-2], "bilinear", "center")
image = utils.resize_to_batch_size(image, noise.shape[0])
out['c_concat'] = comfy.conds.CONDNoiseShape(image)
return out