75 lines
2.2 KiB
Python
75 lines
2.2 KiB
Python
from __future__ import annotations
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import numpy as np
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from backend.node_registry import register_node
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from backend.execution_context import emit_preview
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from backend.data_types import (
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COLORMAPS,
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colormap_to_uint8,
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encode_preview,
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image_to_uint8,
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render_datafield_preview,
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resolve_colormap_input,
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)
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@register_node(display_name="Preview")
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class PreviewImage:
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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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"colormap": (["auto"] + list(COLORMAPS), {"hide_when_input_connected": "colormap_map"}),
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},
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"optional": {
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"colormap_map": ("COLORMAP", {"label": "colormap"}),
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"image": ("IMAGE",),
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"field": ("DATA_FIELD",),
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}
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}
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RETURN_TYPES = ()
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FUNCTION = "preview"
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OUTPUT_NODE = True
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DESCRIPTION = "Display an IMAGE or DATA_FIELD as a coloured thumbnail. Connect either input."
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_broadcast_fn = None
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_current_node_id: str = ""
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def preview(
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self,
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colormap: str,
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image: np.ndarray | None = None,
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field=None,
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colormap_map=None,
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) -> tuple:
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resolved_colormap = resolve_colormap_input(
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colormap,
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colormap_input=colormap_map,
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inherited=field.colormap if field is not None else None,
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default="gray",
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)
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if field is not None:
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arr_u8 = render_datafield_preview(field, resolved_colormap)
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elif image is not None:
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arr_u8 = image_to_uint8(image)
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if arr_u8.ndim == 2:
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if image.dtype == np.uint8:
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normalized = arr_u8.astype(np.float64) / 255.0
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else:
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imin, imax = image.min(), image.max()
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if imax > imin:
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normalized = (image - imin) / (imax - imin)
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else:
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normalized = np.zeros_like(image, dtype=np.float64)
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arr_u8 = colormap_to_uint8(normalized, resolved_colormap)
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else:
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raise ValueError("Connect either an IMAGE or DATA_FIELD input to Preview.")
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data_uri = encode_preview(arr_u8)
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emit_preview(data_uri)
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return ()
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