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Added backward compatibility

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This commit is contained in:
Sirshendu Ganguly
2026-04-28 19:09:17 +05:30
parent acc3ac6456
commit fbdb3f15bb
4 changed files with 53 additions and 31 deletions
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modules/videoInference.py
+12 -8
View File
@@ -5,11 +5,12 @@ import comfy.model_management
class txt2vid:
@staticmethod
def _format_reference_images(referenceImages, model):
def _format_reference_images(referenceImages):
"""
Shape referenceImages per model requirements:
- skywork:skyreels@v4 -> list of groups: {type, tag, images, audio?}
- others -> flat list[str] (legacy behavior)
Shape referenceImages by payload style:
- If any entry uses `images` (Images1..N style), return grouped objects
[{type, tag, images, audio?}]
- Otherwise return flat list[str] (legacy behavior)
"""
if referenceImages is None:
return []
@@ -17,9 +18,12 @@ class txt2vid:
if not isinstance(referenceImages, list):
referenceImages = [referenceImages]
is_skyreels = model == "skywork:skyreels@v4"
has_grouped_images = any(
isinstance(ref, dict) and isinstance(ref.get("images"), list) and len(ref.get("images")) > 0
for ref in referenceImages
)
if is_skyreels:
if has_grouped_images:
grouped = []
for idx, ref in enumerate(referenceImages, start=1):
images = []
@@ -357,7 +361,7 @@ class txt2vid:
print(f"[Debugging] Frame images array: {rwUtils.sanitize_for_logging(frameImages)}")
# Add referenceImages if provided from Runware Reference Images node
if referenceImages is not None and len(referenceImages) > 0:
formattedReferenceImages = self._format_reference_images(referenceImages, model)
formattedReferenceImages = self._format_reference_images(referenceImages)
if len(formattedReferenceImages) > 0:
genConfig[0]["referenceImages"] = formattedReferenceImages
print(f"[Debugging] Reference images array: {rwUtils.sanitize_for_logging(formattedReferenceImages)}")
@@ -391,7 +395,7 @@ class txt2vid:
for key, value in inputs.items():
# Normalize referenceImages so non-SkyReels models keep legacy string[] payload
if key == "referenceImages":
formatted_input_refs = self._format_reference_images(value, model)
formatted_input_refs = self._format_reference_images(value)
if len(formatted_input_refs) > 0:
genConfig[0]["inputs"][key] = formatted_input_refs
continue
modules/videoInputsReferences.py
+39 -21
View File
@@ -6,6 +6,7 @@ class videoInputsReferences:
"""Video Inputs References node for configuring reference images with types"""
MAX_REFERENCES = 10
MAX_GROUPED_REFERENCES = 4
@classmethod
def INPUT_TYPES(cls):
@@ -14,20 +15,24 @@ class videoInputsReferences:
for i in range(1, cls.MAX_REFERENCES + 1):
ordinal = rwUtils.getOrdinal(i)
optionalInputs[f"Image{i}"] = ("IMAGE", {
"tooltip": f"{ordinal.capitalize()} reference image.",
})
optionalInputs[f"Tag{i}"] = ("STRING", {
"tooltip": f"Optional tag for the {ordinal} reference (e.g., @image{i}, @Actor-1).",
"default": "",
})
optionalInputs[f"Type{i}"] = ("STRING", {
"tooltip": f"Type for the {ordinal} reference (e.g., image or grid). Leave empty to omit.",
"default": "",
})
optionalInputs[f"Audio{i}"] = ("STRING", {
"tooltip": f"Optional audio URL/mediaUUID for the {ordinal} reference.",
"default": "",
"tooltip": f"{ordinal.capitalize()} single reference image (mutually exclusive with Images{i}).",
})
if i <= cls.MAX_GROUPED_REFERENCES:
optionalInputs[f"Images{i}"] = ("RUNWAREVIDEOINPUTSREFERENCEMULTIIMAGES", {
"tooltip": f"{ordinal.capitalize()} reference image group from the Multiple Images Connector (mutually exclusive with Image{i}).",
})
optionalInputs[f"Tag{i}"] = ("STRING", {
"tooltip": f"Optional tag for the {ordinal} reference (e.g., @image{i}, @Actor-1).",
"default": "",
})
optionalInputs[f"Type{i}"] = ("STRING", {
"tooltip": f"Type for the {ordinal} reference (e.g., image or grid). Leave empty to omit.",
"default": "",
})
optionalInputs[f"Audio{i}"] = ("STRING", {
"tooltip": f"Optional audio URL/mediaUUID for the {ordinal} reference.",
"default": "",
})
return {
"required": {},
@@ -35,8 +40,8 @@ class videoInputsReferences:
}
DESCRIPTION = (
"Configure multiple reference images for video inference inputs. "
"Use ImageN slots (Image1..Image10)."
"Configure up to 4 reference image entries for video inference inputs. "
"For each slot, provide either ImageN (single image) or ImagesN (connector output), not both."
)
FUNCTION = "createReferences"
RETURN_TYPES = ("RUNWAREVIDEOINPUTSREFERENCEIMAGES",)
@@ -49,26 +54,39 @@ class videoInputsReferences:
for i in range(1, self.MAX_REFERENCES + 1):
imageKey = f"Image{i}"
imagesKey = f"Images{i}"
tagKey = f"Tag{i}"
typeKey = f"Type{i}"
audioKey = f"Audio{i}"
image = kwargs.get(imageKey)
images = kwargs.get(imagesKey)
refTag = (kwargs.get(tagKey) or "").strip()
refType = kwargs.get(typeKey, "")
refAudio = (kwargs.get(audioKey) or "").strip()
if image is not None:
reference = self._createReference(image, refTag, refType, refAudio)
has_image = image is not None
has_images = isinstance(images, list) and len(images) > 0
if has_image and has_images:
raise ValueError(
f"Reference {i}: use either {imageKey} or {imagesKey}, not both."
)
if has_image or has_images:
reference = self._createReference(image, images, refTag, refType, refAudio)
references.append(reference)
return (references,)
def _createReference(self, image, refTag: str, refType: str, refAudio: str):
def _createReference(self, image, images, refTag: str, refType: str, refAudio: str):
"""Create reference entry."""
entry: Dict[str, Any] = {
"image": rwUtils.convertTensor2IMG(image)
}
entry: Dict[str, Any] = {}
if image is not None:
entry["image"] = rwUtils.convertTensor2IMG(image)
elif isinstance(images, list) and len(images) > 0:
entry["images"] = images
else:
return entry
if refTag:
entry["tag"] = refTag