Ethanfel
cd0b8783dc
Render the pool as an in-node thumbnail grid with paste/drop/upload ingest, click-to-select (active border), inline label editing, and delete. Toolbar (upload/refresh/count) sits at the bottom per ComfyUI convention; the node auto-grows to fit content. pool_id is a declared STRING input (not a hidden input): ComfyUI only fills hidden inputs for built-in types, but forwards every serialized widget value by name. The JS mints a per-node UUID and hides the widget via widget.hidden=true (frontend 1.45), keeping it serialized. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
69 lines
2.6 KiB
Python
69 lines
2.6 KiB
Python
"""GridImagePool — the Image Pool (Grid) ComfyUI node."""
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import os
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from .gates_compat import grid_pool_base as _grid_pool_base
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from . import pool, imaging
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NODE_CLASS_MAPPINGS = {}
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NODE_DISPLAY_NAME_MAPPINGS = {}
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class GridImagePool:
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CATEGORY = "Datasete Gates"
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FUNCTION = "run"
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RETURN_TYPES = ("IMAGE", "MASK", "INT", "INT", "STRING")
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RETURN_NAMES = ("image", "mask", "index", "count", "label")
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@classmethod
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def INPUT_TYPES(cls):
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# pool_id is a per-node UUID owned by the JS extension. It must be a
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# NORMAL input, not a "hidden" one: ComfyUI only populates hidden inputs
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# for built-in types (UNIQUE_ID, PROMPT, ...), so a custom hidden
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# "POOL_ID" would always arrive as None. The frontend, however, forwards
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# every serialized widget value by name, so a declared STRING input
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# backed by a (hidden-rendered) widget reliably reaches run().
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return {
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"required": {
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"index": ("INT", {"default": -1, "min": -1, "max": 9999}),
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"pool_id": ("STRING", {"default": "default"}),
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},
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}
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@staticmethod
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def _resolve(index, pool_id):
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base = _grid_pool_base()
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m = pool.read_manifest(base, pool_id)
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idx = pool.resolve_slot(m, index)
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return base, m, idx
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def run(self, index, pool_id="default"):
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base, m, idx = self._resolve(index, pool_id)
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if idx < 0:
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img, mask = imaging.empty_outputs()
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return (img, mask, 0, 0, "")
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slot = m["slots"][idx]
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d = pool.pool_dir(base, pool_id)
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img = imaging.load_image_tensor(str(d / slot["image"]))
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h, w = int(img.shape[1]), int(img.shape[2])
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mask_name = slot.get("mask")
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mask = imaging.load_mask_tensor(str(d / mask_name) if mask_name else None, h, w)
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return (img, mask, idx, len(m["slots"]), slot.get("label", ""))
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@classmethod
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def IS_CHANGED(cls, index, pool_id="default", **kwargs):
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base, m, idx = cls._resolve(index, pool_id)
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if idx < 0:
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return imaging.change_hash(pool_id, -1, [])
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slot = m["slots"][idx]
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d = pool.pool_dir(base, pool_id)
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mtimes = []
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for key in ("image", "mask"):
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name = slot.get(key)
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p = d / name if name else None
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mtimes.append(os.path.getmtime(p) if p and p.exists() else 0.0)
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# include active so manual selection changes invalidate cache
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return imaging.change_hash(pool_id, f"{idx}:{m.get('active')}", mtimes)
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NODE_CLASS_MAPPINGS = {"GridImagePool": GridImagePool}
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NODE_DISPLAY_NAME_MAPPINGS = {"GridImagePool": "Image Pool (Grid)"}
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