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Crop Radiance image inputs to multiples of 16 instead of erroring to be in line with existing VAE behavior

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blepping 2025-08-27 20:12:54 -06:00
parent e5aee26ee3
commit 731a892a31
1 changed files with 17 additions and 11 deletions
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28
comfy_extras/nodes_chroma_radiance.py
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@ -28,7 +28,7 @@ class ChromaRadianceLatentToImage:
self.device = comfy.model_management.intermediate_device()
@classmethod
def INPUT_TYPES(s):
def INPUT_TYPES(s) -> dict:
return {"required": {"latent": ("LATENT",)}}
DESCRIPTION = "For use with Chroma Radiance. Converts an input LATENT to IMAGE."
@ -37,7 +37,7 @@ class ChromaRadianceLatentToImage:
CATEGORY = "latent/chroma_radiance"
def go(self, *, latent):
def go(self, *, latent: dict) -> tuple[torch.Tensor]:
img = latent["samples"].to(device=self.device, dtype=torch.float32, copy=True)
img = img.clamp_(-1, 1).movedim(1, -1).contiguous()
img += 1.0
@ -49,26 +49,32 @@ class ChromaRadianceImageToLatent:
self.device = comfy.model_management.intermediate_device()
@classmethod
def INPUT_TYPES(s):
def INPUT_TYPES(s) -> dict:
return {"required": {"image": ("IMAGE",)}}
DESCRIPTION = "For use with Chroma Radiance. Converts an input IMAGE to LATENT."
DESCRIPTION = "For use with Chroma Radiance. Converts an input IMAGE to LATENT. Note: Radiance requires inputs with width/height that are multiples of 16 so your image will be cropped if necessary."
RETURN_TYPES = ("LATENT",)
FUNCTION = "go"
CATEGORY = "latent/chroma_radiance"
def go(self, *, image):
def go(self, *, image: torch.Tensor) -> tuple[dict]:
if image.ndim == 3:
image = image.unsqueeze(0)
elif image.ndim != 4:
raise ValueError("Unexpected input image shape")
dims = image.shape[1:-1]
for d in range(len(dims)):
d_adj = (dims[d] // 16) * 16
if d_adj == d:
continue
d_offset = (dims[d] % 16) // 2
image = image.narrow(d + 1, d_offset, d_adj)
h, w, c = image.shape[1:]
if h < 16 or w < 16 or not (h / 16).is_integer() or not (w / 16).is_integer():
raise ValueError("Chroma Radiance image inputs must have sizes that are multiples of 16.")
if c > 3:
image = image[..., :3]
elif c == 1:
if h < 16 or w < 16:
raise ValueError("Chroma Radiance image inputs must have height/width of at least 16 pixels.")
image = image[..., :3]
if c == 1:
image = image.expand(-1, -1, -1, 3)
elif c != 3:
raise ValueError("Unexpected number of channels in input image")
@ -83,7 +89,7 @@ class ChromaRadianceStubVAE:
self.image_to_latent = ChromaRadianceImageToLatent()
self.latent_to_image = ChromaRadianceLatentToImage()
DESCRIPTION = "For use with Chroma Radiance. Allows converting between latent and image types with nodes that require a VAE input."
DESCRIPTION = "For use with Chroma Radiance. Allows converting between latent and image types with nodes that require a VAE input. Note: Radiance requires inputs with width/height that are multiples of 16 so your image will be cropped if necessary."
RETURN_TYPES = ("VAE",)
FUNCTION = "go"