kadirnar
e21711a049
- Updated model selection in image-to-image, mask generation, object detection, video classification, zero-shot image classification, zero-shot object detection, document question answering, feature extraction, image-to-text, image-text-to-text, visual question answering, conversational, fill mask, question answering, sentence similarity, table question answering, zero-shot classification, text classification, text generation, and token classification pipelines to use a default string instead of a model list. - Removed unused keypoint detection, summarization, text2text generation, and translation pipelines. - Added utility nodes for type conversion: IntToString, StringToInt, FloatToString, and StringToFloat. - Updated all pipeline calls to include trust_remote_code=True for enhanced security. - Improved requirements by adding timm and opencv-python for better functionality.
86 lines
1.8 KiB
Python
86 lines
1.8 KiB
Python
class IntToString:
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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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"value": ("INT", {"default": 0}),
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},
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("text",)
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FUNCTION = "convert"
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CATEGORY = "Transformers/Utility"
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def convert(self, value):
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return (str(value),)
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class StringToInt:
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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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"text": ("STRING", {"default": "0"}),
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},
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}
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RETURN_TYPES = ("INT",)
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RETURN_NAMES = ("value",)
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FUNCTION = "convert"
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CATEGORY = "Transformers/Utility"
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def convert(self, text):
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return (int(text.strip()),)
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class FloatToString:
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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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"value": ("FLOAT", {"default": 0.0}),
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},
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("text",)
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FUNCTION = "convert"
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CATEGORY = "Transformers/Utility"
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def convert(self, value):
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return (str(value),)
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class StringToFloat:
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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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"text": ("STRING", {"default": "0.0"}),
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},
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}
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RETURN_TYPES = ("FLOAT",)
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RETURN_NAMES = ("value",)
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FUNCTION = "convert"
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CATEGORY = "Transformers/Utility"
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def convert(self, text):
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return (float(text.strip()),)
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NODE_CLASS_MAPPINGS = {
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"IntToString": IntToString,
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"StringToInt": StringToInt,
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"FloatToString": FloatToString,
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"StringToFloat": StringToFloat,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"IntToString": "Int to String",
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"StringToInt": "String to Int",
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"FloatToString": "Float to String",
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"StringToFloat": "String to Float",
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}
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