Fixed naming
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@@ -28,7 +28,7 @@ class imageInferenceInputs:
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"default": "",
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})
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optionalInputs[f"Reference Type {i}"] = ("STRING", {
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"tooltip": f"Optional type for {ordinal} reference, e.g. 'sketch' for illustrious style models. Leave empty to omit.",
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"tooltip": f"Optional type for {ordinal} reference, e.g. 'sketch' for illustrative style models. Leave empty to omit.",
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"default": "",
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})
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optionalInputs[f"Reference Strength {i}"] = ("FLOAT", {
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@@ -50,7 +50,7 @@ class imageInferenceInputs:
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"optional": optionalInputs
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}
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DESCRIPTION = "Configure custom inputs for Runware Image Inference, including reference images (with optional type e.g. 'sketch' for illustrious style models, and strength 0-1 for sketch) that can be passed to the inference node."
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DESCRIPTION = "Configure custom inputs for Runware Image Inference, including reference images (with optional type e.g. 'sketch' for illustrative style models, and strength 0-1 for sketch) that can be passed to the inference node."
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FUNCTION = "createInputs"
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RETURN_TYPES = ("RUNWAREIMAGEINFERENCEINPUTS",)
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RETURN_NAMES = ("Inference Inputs",)
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@@ -80,7 +80,7 @@ class imageInferenceInputs:
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def _collectReferences(self, kwargs):
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"""Collect and convert reference images to list. Each entry may include type (e.g. 'sketch') and strength (0-1, only for sketch)."""
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referenceSlots = []
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reference_slots = []
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for i in range(1, self.MAX_REFERENCE_IMAGES + 1):
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image = kwargs.get(f"Reference Image {i}", None)
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@@ -88,28 +88,28 @@ class imageInferenceInputs:
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ref_type = kwargs.get(f"Reference Type {i}", "")
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strength = kwargs.get(f"Reference Strength {i}", 0.0)
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if image is not None:
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referenceSlots.append((image, tag, ref_type, strength))
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reference_slots.append((image, tag, ref_type, strength))
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if not referenceSlots:
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if not reference_slots:
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return []
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has_tags = any(
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isinstance(tag, str) and tag.strip() != ""
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for _, tag, _, _ in referenceSlots
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for _, tag, _, _ in reference_slots
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)
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has_type = any(
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isinstance(rt, str) and rt.strip() != ""
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for _, _, rt, _ in referenceSlots
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for _, _, rt, _ in reference_slots
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)
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if not has_tags and not has_type:
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return [
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rwUtils.convertTensor2IMG(image)
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for image, _, _, _ in referenceSlots
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for image, _, _, _ in reference_slots
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]
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references = []
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for image, tag, ref_type, strength in referenceSlots:
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for image, tag, ref_type, strength in reference_slots:
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entry = {"image": rwUtils.convertTensor2IMG(image)}
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if isinstance(tag, str) and tag.strip() != "":
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entry["tag"] = tag.strip()
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