Implement Compass Image Loader node with dynamic directory discovery and autocomplete
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9
__init__.py
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9
__init__.py
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from .compass_image_loader import CompassImageLoader
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NODE_CLASS_MAPPINGS = {
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"CompassImageLoader": CompassImageLoader,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"CompassImageLoader": "Compass Image Loader",
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}
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157
compass_image_loader.py
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157
compass_image_loader.py
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from PIL import Image
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import folder_paths
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import os
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import torch
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import numpy as np
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VALID_DIRECTIONS = {"n", "ne", "e", "se", "s", "sw", "w", "nw"}
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VALID_MODALITIES = {"image", "depth", "openpose"}
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def _discover_directories():
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base_dir = folder_paths.get_input_directory()
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if not os.path.exists(base_dir):
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return []
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candidates = set()
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for root, subdirs, _ in os.walk(base_dir, followlinks=True):
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current_path = root[os.path.dirname(root) + 1:]
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sub_dirs_lower = {s.lower() for s in subdirs}
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if VALID_DIRECTIONS & sub_dirs_lower or VALID_MODALITIES & sub_dirs_lower:
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candidates.add(current_path)
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return sorted(candidates)
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class CompassImageLoader:
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CATEGORY = "image/loaders"
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@classmethod
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def INPUT_TYPES(cls):
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directories = _discover_directories()
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return {
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"required": {
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"directory": (directories if directories else ["(none found)"],),
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"direction": (["", "n", "ne", "e", "se", "s", "sw", "w", "nw"],),
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"modality": (["image", "depth", "openpose"],),
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"frame": ("STRING", {"default": ""}),
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"width": ("INT", {"default": 0, "min": 0, "max": 16384, "step": 1}),
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"height": ("INT", {"default": 0, "min": 0, "max": 16384, "step": 1}),
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},
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}
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RETURN_TYPES = ("IMAGE", "STRING", "INT", "INT", "INT")
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RETURN_NAMES = ("IMAGE", "path", "width", "height", "frame_count")
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FUNCTION = "load_images"
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def load_images(self, directory, direction, modality, frame=None, width=0, height=0):
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base_dir = folder_paths.get_input_directory()
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if direction and direction.strip():
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target_dir = os.path.join(base_dir, directory, direction, modality)
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else:
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target_dir = os.path.join(base_dir, directory, modality)
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if not os.path.isdir(target_dir):
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raise RuntimeError(f"Compass directory not found: {target_dir}")
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supported_extensions = {"png", "jpg", "jpeg", "webp", "bmp", "gif", "tiff"}
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files = [
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f for f in sorted(os.listdir(target_dir))
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if os.path.isfile(os.path.join(target_dir, f)) and f.split(".")[-1].lower() in supported_extensions
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]
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if not files:
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raise RuntimeError(f"No images found in: {target_dir}")
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if frame is None or str(frame).strip() == "":
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selected_files = files
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output_path = target_dir
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else:
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try:
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index = int(str(frame).strip())
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except (ValueError, TypeError):
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raise RuntimeError(f"Invalid frame number: '{frame}'. Must be an integer.")
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if index < 0 or index >= len(files):
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raise RuntimeError(
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f"Frame index {index} out of bounds. Found {len(files)} images in {target_dir}."
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)
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selected_files = [files[index]]
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output_path = os.path.join(target_dir, files[index])
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tensors = []
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final_w, final_h = 0, 0
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for filename in selected_files:
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filepath = os.path.join(target_dir, filename)
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image = Image.open(filepath).convert("RGB")
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orig_w, orig_h = image.size
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if width == 0 and height == 0:
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pass
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elif width > 0 and height == 0:
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fw = width
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fh = int(orig_h * (width / orig_w))
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image = image.resize((fw, fh), Image.Resampling.LANCZOS)
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elif height > 0 and width == 0:
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fh = height
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fw = int(orig_w * (height / orig_h))
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image = image.resize((fw, fh), Image.Resampling.LANCZOS)
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else:
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scale = max(width / orig_w, height / orig_h)
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new_w = int(orig_w * scale)
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new_h = int(orig_h * scale)
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image = image.resize((new_w, new_h), Image.Resampling.LANCZOS)
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left = (new_w - width) // 2
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top = (new_h - height) // 2
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right = left + width
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bottom = top + height
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image = image.crop((left, top, right, bottom))
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final_w, final_h = image.size[0], image.size[1]
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np_image = np.array(image).astype(np.float32) / 255.0
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tensor = torch.from_numpy(np_image)[None,]
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tensors.append(tensor)
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if len(tensors) == 1:
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image_batch = tensors[0]
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else:
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image_batch = torch.cat(tensors, dim=0)
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return (image_batch, output_path, final_w, final_h, len(selected_files))
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@classmethod
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def IS_CHANGED(cls, directory, direction, modality, frame=None, width=0, height=0):
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base_dir = folder_paths.get_input_directory()
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if direction and direction.strip():
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target_dir = os.path.join(base_dir, directory, direction, modality)
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else:
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target_dir = os.path.join(base_dir, directory, modality)
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import hashlib
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m = hashlib.sha256()
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m.update(f"{directory}:{direction}:{modality}:{frame}:{width}:{height}".encode("utf-8"))
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if not os.path.isdir(target_dir):
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return ""
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supported_extensions = {"png", "jpg", "jpeg", "webp", "bmp", "gif", "tiff"}
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files = [
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f for f in sorted(os.listdir(target_dir))
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if os.path.isfile(os.path.join(target_dir, f)) and f.split(".")[-1].lower() in supported_extensions
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]
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if frame is None or str(frame).strip() == "":
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m.update(":".join(files).encode("utf-8"))
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else:
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try:
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index = int(str(frame).strip())
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filepath = os.path.join(target_dir, files[index])
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with open(filepath, "rb") as f:
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m.update(f.read(65536))
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except (ValueError, IndexErro
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116
js/compass_image_loader.js
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116
js/compass_image_loader.js
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import { app } from "../../../scripts/app.js";
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app.registerExtension({
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name: "CompassImageLoader",
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async beforeRegisterNodeDef(nodeType, nodeData) {
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if (nodeData.name !== "CompassImageLoader") return;
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const origOnNodeCreated = nodeType.prototype.onNodeCreated;
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nodeType.prototype.onNodeCreated = function () {
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if (origOnNodeCreated) origOnNodeCreated.apply(this, []);
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const directoryWidget = this.widgets.find(
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(w) => w.name === "directory"
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);
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if (!directoryWidget) return;
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directoryWidget._all_values = [...(directoryWidget.options.values || [])];
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try {
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if (typeof this.addDOMWidget === "function") {
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const inputEl = document.createElement("input");
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inputEl.type = "text";
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inputEl.value = directoryWidget.value;
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inputEl.addEventListener("change", () => {
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const filter = inputEl.value.toLowerCase();
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const filtered = directoryWidget._all_values.filter((v) =>
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v.toLowerCase().includes(filter)
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);
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directoryWidget.options.values = filtered;
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directoryWidget.value = filtered[0] || "";
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this.onResize?.();
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});
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const dropdownEl = document.createElement("div");
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dropdownEl.style.overflowY = "auto";
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dropdownEl.style.maxHeight = "200px";
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const listEl = document.createElement("ul");
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listEl.style.padding = "4px";
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listEl.style.margin = "0";
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listEl.style.background = "#333";
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inputEl.addEventListener("focus", () => {
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listEl.innerHTML = "";
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directoryWidget._all_values.forEach((v) => {
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const li = document.createElement("li");
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li.textContent = v;
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li.style.padding = "4px 8px";
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li.style.cursor = "pointer";
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li.addEventListener("click", () => {
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inputEl.value = v;
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directoryWidget.value = v;
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listEl.innerHTML = "";
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});
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listEl.appendChild(li);
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});
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});
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inputEl.addEventListener("blur", (e) => {
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setTimeout(() => {
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if (!listEl.contains(e.relatedTarget)) {
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listEl.innerHTML = "";
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}
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}, 0);
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});
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const textWidget = this.addDOMWidget(
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"directory_filter",
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"Directory Filter",
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inputEl,
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{},
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{ widget: directoryWidget }
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);
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textWidget.computeSize = () => [1, 40];
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}
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} catch (e) {
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console.warn("[CompassImageLoader] Widget setup failed:", e);
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}
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};
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},
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async loadedGraphNode(node) {
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if (node.type !== "CompassImageLoader") return;
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const directoryWidget = node.widgets?.find((w) => w.name === "directory");
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if (!directoryWidget) return;
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setTimeout(() => {
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try {
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app.api.addWebSocketMessageEventListener("fresh-node-defs", (event) => {
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const defs = event.detail || {};
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const compassDef = defs["CompassImageLoader"];
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if (!compassDef) return;
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const dirs = compassDef.input?.required?.directory;
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if (!dirs || !Array.isArray(dirs)) return;
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directoryWidget._all_values = [...dirs];
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directoryWidget.options.values = [...dirs];
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if (!directoryWidget._all_values.includes(directoryWidget.value)) {
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directoryWidget.value = directoryWidget._all_values[0] || "";
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}
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});
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} catch (e) {
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console.warn("[CompassImageLoader] Refresh listener failed:", e);
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}
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}, 100);
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},
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async getCustomWidgets() {
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return null;
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}
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});
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