Sirshendu Ganguly
8d75a6933f
- Add Runware Video Background Removal node with Bria support - Add Runware Video Upscaler node with Bria support - Add Runware Vectorize node for image vectorization - Add Lightricks Provider Settings node - Add Video Inference Inputs node for structured inputs - Add Input Audios and Reference Videos nodes - Update video inference with speech support and reference videos - Add new video models: OmniHuman 1/1.5, PixVerse LipSync, LTX - Update Bytedance provider settings with boolean controls - Add corresponding workflow examples
47 lines
1.6 KiB
Python
47 lines
1.6 KiB
Python
from .utils import runwareUtils as rwUtils
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class videoInferenceInputs:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {},
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"optional": {
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"Image": ("IMAGE", {
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"tooltip": "Portrait image for video generation. This will be the main subject that will speak and move in the generated video."
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}),
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"Audio": ("STRING", {
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"tooltip": "Connect the mediaUUID output from Runware Media Upload node with audio file. This audio will be synchronized with the generated video."
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}),
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"Mask": ("IMAGE", {
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"tooltip": "Mask image to specify a specific subject in the image to speak. Use white/black mask format."
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}),
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}
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}
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DESCRIPTION = "Configure custom inputs for Runware Video Inference with OmniHuman 1.5 support, including image, audio, and mask inputs."
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FUNCTION = "createInputs"
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RETURN_TYPES = ("RUNWAREVIDEOINFERENCEINPUTS",)
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RETURN_NAMES = ("Video Inference Inputs",)
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CATEGORY = "Runware"
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def createInputs(self, **kwargs):
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image = kwargs.get("Image", None)
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audio = kwargs.get("Audio", None)
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mask = kwargs.get("Mask", None)
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inputs = {}
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if image is not None:
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image_uuid = rwUtils.convertTensor2IMG(image)
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inputs["image"] = image_uuid
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if audio is not None and audio.strip() != "":
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inputs["audio"] = audio.strip()
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if mask is not None:
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mask_uuid = rwUtils.convertTensor2IMG(mask)
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inputs["mask"] = mask_uuid
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return (inputs,)
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