commit cf7011ded03d64da0c4f09fa65101803a234f31d Author: WhatDreamsCost Date: Fri Mar 20 02:23:37 2026 -0500 Initial commit diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..dfe0770 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,2 @@ +# Auto detect text files and perform LF normalization +* text=auto diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..e62ec04 --- /dev/null +++ b/LICENSE @@ -0,0 +1,674 @@ +GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Copyright (C) + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/__init__.py b/__init__.py new file mode 100644 index 0000000..092ed56 --- /dev/null +++ b/__init__.py @@ -0,0 +1,21 @@ +from .ltx_keyframer import LTXKeyframer +from .multi_image_loader import MultiImageLoader +from .ltx_sequencer import LTXSequencer + +# Register the node classes +NODE_CLASS_MAPPINGS = { + "LTXKeyframer": LTXKeyframer, + "MultiImageLoader": MultiImageLoader, + "LTXSequencer": LTXSequencer +} + +# Provide clean display names for the ComfyUI interface +NODE_DISPLAY_NAME_MAPPINGS = { + "LTXKeyframer": "LTX Keyframer", + "MultiImageLoader": "Multi Image Loader", + "LTXSequencer": "LTX Sequencer" +} + +WEB_DIRECTORY = "./js" + +__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS', 'WEB_DIRECTORY'] \ No newline at end of file diff --git a/__pycache__/__init__.cpython-312.pyc b/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000..1cec220 Binary files /dev/null and b/__pycache__/__init__.cpython-312.pyc differ diff --git a/__pycache__/ltx_keyframer.cpython-312.pyc b/__pycache__/ltx_keyframer.cpython-312.pyc new file mode 100644 index 0000000..a51a1f8 Binary files /dev/null and b/__pycache__/ltx_keyframer.cpython-312.pyc differ diff --git a/__pycache__/ltx_sequencer.cpython-312.pyc b/__pycache__/ltx_sequencer.cpython-312.pyc new file mode 100644 index 0000000..71bbabd Binary files /dev/null and b/__pycache__/ltx_sequencer.cpython-312.pyc differ diff --git a/__pycache__/multi_image_loader.cpython-312.pyc b/__pycache__/multi_image_loader.cpython-312.pyc new file mode 100644 index 0000000..0c25f73 Binary files /dev/null and b/__pycache__/multi_image_loader.cpython-312.pyc differ diff --git a/js/ltx_keyframer.js b/js/ltx_keyframer.js new file mode 100644 index 0000000..d5d0bc4 --- /dev/null +++ b/js/ltx_keyframer.js @@ -0,0 +1,419 @@ +import { app } from "../../scripts/app.js"; + +// Global registry to track all LTXKeyframer nodes across all subgraphs +window._LTXKeyframerGlobalNodes = window._LTXKeyframerGlobalNodes || new Set(); + +// ComfyUI native trick to cleanly hide/show widgets without deleting them +function toggleWidget(widget, visible) { + if (visible) { + if (widget.origType !== undefined) { + widget.type = widget.origType; + widget.computeSize = widget.origComputeSize; + delete widget.origType; + delete widget.origComputeSize; + } + } else { + if (widget.type !== "hidden") { + widget.origType = widget.type; + widget.origComputeSize = widget.computeSize; + widget.type = "hidden"; + widget.computeSize = () => [0, -4]; + } + } +} + +// --- NEW SYNC HELPER FUNCTION --- +// Finds all other LTXKeyframer nodes globally and mirrors the value to them +function syncWidgetAcrossNodes(sourceNode, widgetName, value) { + if (!window._LTXKeyframerGlobalNodes) return; + + for (const targetNode of window._LTXKeyframerGlobalNodes) { + // Target all OTHER LTXKeyframer nodes by direct object reference + if (targetNode !== sourceNode) { + + // 1. Always update the hidden properties cache so it remembers the sync + // even if the widget isn't currently visible (e.g. fewer images loaded right now) + targetNode.properties[widgetName] = value; + + // 2. If the widget is currently visible on the UI, update it visually + if (targetNode.widgets) { + const targetWidget = targetNode.widgets.find(w => w.name === widgetName); + if (targetWidget && targetWidget.value !== value) { + targetWidget.value = value; + targetNode.setDirtyCanvas(true, false); + } + } + } + } +} + +app.registerExtension({ + name: "Comfy.LTXKeyframer.DynamicInputs", + async nodeCreated(node) { + if (node.comfyClass !== "LTXKeyframer") return; + + // Register this node instance globally + window._LTXKeyframerGlobalNodes.add(node); + + node._currentImageCount = -1; // Force first update + + // Initialize persistent properties cache + node.properties = node.properties || {}; + + // Add subtle separator line above images_loaded + node.addCustomWidget({ + name: "num_images_separator", + type: "text", + draw(ctx, node, widget_width, y, widget_height) { + ctx.save(); + ctx.strokeStyle = "#444"; + ctx.lineWidth = 1; + ctx.beginPath(); + ctx.moveTo(10, y + 5); + ctx.lineTo(widget_width - 10, y + 5); + ctx.stroke(); + ctx.restore(); + }, + computeSize(width) { + return [width, 10]; + } + }); + + // Move separator before num_images + const moveSeparator = () => { + const idx = node.widgets.findIndex(w => w.name === "num_images"); + const sepIdx = node.widgets.findIndex(w => w.name === "num_images_separator"); + if (idx !== -1 && sepIdx !== -1) { + const separator = node.widgets.splice(sepIdx, 1)[0]; + node.widgets.splice(idx, 0, separator); + } + }; + setTimeout(moveSeparator, 50); // Small delay to ensure num_images is present + + // Core update: synchronize widget visibility to match imageCount + node._applyWidgetCount = function(count) { + const isInitialLoad = this._currentImageCount === -1; + + if (this._currentImageCount === count && !isInitialLoad) return; + this._currentImageCount = count; + + const initialWidth = this.size[0]; + const numWidget = this.widgets?.find(w => w.name === "num_images"); + if (numWidget) { + numWidget.label = "images_loaded"; + numWidget.value = Math.max(0, Math.min(count || 0, 50)); + } + + // 1. Store current widget values in properties BEFORE removing them + // We skip reading from `this.widgets` on the initial load because it might be scrambling. + if (!isInitialLoad && this.widgets) { + this.widgets.forEach(w => { + if (w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) { + this.properties[w.name] = w.value; + } + }); + } + + // 2. Remove all existing dynamic insert_frame/strength/header widgets + if (this.widgets) { + this.widgets = this.widgets.filter(w => + !w.name.startsWith("insert_frame_") && + !w.name.startsWith("strength_") && + !w.name.startsWith("header_") + ); + } else { + this.widgets = []; + } + + // 3. Add back exactly the right amount of widgets using the cached values + for (let i = 1; i <= count; i++) { + // Add header/separator widget for grouping + const headerName = `header_${i}`; + this.addCustomWidget({ + name: headerName, + type: "text", + value: `Image #${i}`, + draw(ctx, node, widget_width, y, widget_height) { + ctx.save(); + const margin = 10; + const topPadding = 15; + + // Subtle separator line + ctx.strokeStyle = "#333"; + ctx.lineWidth = 1; + ctx.beginPath(); + ctx.moveTo(margin, y + 5); + ctx.lineTo(widget_width - margin, y + 5); + ctx.stroke(); + + // Text label + ctx.fillStyle = "#dddddd"; // Light gray + ctx.font = "bold 12px Arial"; + ctx.textAlign = "left"; + ctx.fillText(`Image #${i}`, margin, y + topPadding + 10); + ctx.restore(); + }, + computeSize(width) { + return [width, 35]; // Vertical gap + label height + } + }); + + const insertFrameWidgetName = `insert_frame_${i}`; + const strengthWidgetName = `strength_${i}`; + + // Add insert_frame widget with Sync Callback + const savedInsertFrameValue = this.properties[insertFrameWidgetName]; + this.addWidget("number", insertFrameWidgetName, + savedInsertFrameValue !== undefined ? savedInsertFrameValue : 0, + (value) => { + const rounded = Math.round(value); + this.properties[insertFrameWidgetName] = rounded; + syncWidgetAcrossNodes(this, insertFrameWidgetName, rounded); // Sync out + }, { min: -9999, max: 9999, step: 10, precision: 0 } + ); + + // Add strength widget with Sync Callback + const savedStrengthValue = this.properties[strengthWidgetName]; + this.addWidget("number", strengthWidgetName, + savedStrengthValue !== undefined ? savedStrengthValue : 1.0, + (value) => { + this.properties[strengthWidgetName] = value; + syncWidgetAcrossNodes(this, strengthWidgetName, value); // Sync out + }, { min: 0.0, max: 1.0, step: 0.01 } + ); + } + + this.setDirtyCanvas(true, true); + requestAnimationFrame(() => { + if (this.computeSize) { + this.setSize(this.computeSize()); + this.size[0] = initialWidth; // keep width fixed when restructuring + } + }); + }; + + // --- STRICT ARRAY MAPPER: FIXES ALL SHIFTING FOREVER --- + // This runs the exact instant the node is loaded, before any UI widgets shift indices. + // It locks the perfectly mapped array values directly into our properties dictionary. + const origConfigure = node.configure; + node.configure = function(info) { + if (origConfigure) { + origConfigure.apply(this, arguments); + } + if (this.widgets) { + this.widgets.forEach(w => { + if (w.name === "num_images" || w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) { + this.properties[w.name] = w.value; + } + }); + } + }; + + // Handle deserialization to load properties properly from JSON + const originalOnConfigure = node.onConfigure; + node.onConfigure = function(info) { + if (originalOnConfigure) { + originalOnConfigure.apply(this, arguments); + } + if (info.properties) { + this.properties = { ...this.properties, ...info.properties }; + } + setTimeout(() => { + const count = readSourceImageCount(this); + // Fallback to properties.num_images if source node disconnected + let targetCount = count !== null ? count : (this.properties.num_images || 0); + this._applyWidgetCount(targetCount); + }, 100); + }; + + // --- STRICT ARRAY GENERATOR --- + // Completely detach from ComfyUI's blind visual array saving. + // We construct an exact 101-element strict array that Python expects. + // This makes your node 100% immune to UI/Header index shifting. + const originalOnSerialize = node.onSerialize; + node.onSerialize = function(info) { + // Ensure properties are strictly synced with current widget values before building + if (this.widgets) { + this.widgets.forEach(w => { + if (w.name === "num_images" || w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) { + this.properties[w.name] = w.value; + } + }); + } + + if (originalOnSerialize) { + originalOnSerialize.apply(this, arguments); + } + + info.properties = { ...this.properties }; + + // Build the exact strict array that maps 1-to-1 to the Python backend + const strictArray = []; + const numWidgetVal = this.properties["num_images"]; + strictArray.push(numWidgetVal !== undefined ? numWidgetVal : 1); + + for (let i = 1; i <= 50; i++) { + const fVal = this.properties[`insert_frame_${i}`]; + const sVal = this.properties[`strength_${i}`]; + strictArray.push(fVal !== undefined ? fVal : 0); + strictArray.push(sVal !== undefined ? sVal : 1.0); + } + + info.widgets_values = strictArray; + }; + + // Set up manual num_images widget callback + setTimeout(() => { + const numWidget = node.widgets?.find(w => w.name === "num_images"); + if (numWidget) { + numWidget.callback = (val) => { + node.properties["num_images"] = val; + node._applyWidgetCount(val); + }; + } + }, 100); + + // Exposed receiver for push-based notifications + node._syncImageCount = function(count) { + this._applyWidgetCount(count); + }; + + // Helper: read image count from a connected MultiImageLoader node + function readSourceImageCount(self) { + const multiInput = self.inputs?.find(inp => inp.name === "multi_input"); + if (!multiInput || !multiInput.link) return null; + + const nodeGraph = self.graph || app.graph; + + // Helper to safely trace back through Reroutes and ComfyUI Group Nodes/Subgraphs + function traceUpstream(graph, linkId, visited = new Set()) { + if (!linkId || visited.has(linkId)) return null; + visited.add(linkId); + + const link = graph.links[linkId]; + if (!link) return null; + + const originNode = graph.getNodeById(link.origin_id); + if (!originNode) return null; + + if (originNode.comfyClass === "MultiImageLoader") { + return originNode; + } + + // Traverse Reroute nodes + if (originNode.type === "Reroute" || originNode.comfyClass === "Reroute") { + if (originNode.inputs && originNode.inputs.length > 0 && originNode.inputs[0].link) { + return traceUpstream(graph, originNode.inputs[0].link, visited); + } + } + + // Traverse standard ComfyUI Group Nodes (subgraphs) + if (typeof originNode.getInnerNode === "function") { + try { + const innerNode = originNode.getInnerNode(link.origin_slot); + if (innerNode && innerNode.comfyClass === "MultiImageLoader") { + return innerNode; + } + } catch (e) { + console.warn("Could not trace inner node", e); + } + } + + return null; + } + + let sourceNode = traceUpstream(nodeGraph, multiInput.link); + + // Helper to extract the count once we find a node + function getCountFromNode(n) { + if (typeof n._imageCount === "number") return n._imageCount; + const pathsWidget = n.widgets?.find(w => w.name === "image_paths"); + if (pathsWidget) { + return (pathsWidget.value || "").split('\n').map(p => p.trim()).filter(p => p.length > 0).length; + } + return null; + } + + if (sourceNode) { + return getCountFromNode(sourceNode); + } + + // Fallback Strategy: If it is connected to something, but we couldn't resolve it + // directly (e.g. complex nested 3rd party subgraphs), scan the entire UI. + // If there is EXACTLY ONE MultiImageLoader in the workspace, safely assume that's the one. + let multiImageLoaders = []; + function findAllLoaders(nodes) { + if (!nodes) return; + for (let n of nodes) { + if (n.comfyClass === "MultiImageLoader") { + multiImageLoaders.push(n); + } + if (n.subgraph && n.subgraph._nodes) { + findAllLoaders(n.subgraph._nodes); + } + } + } + if (app.graph && app.graph._nodes) { + findAllLoaders(app.graph._nodes); + } + + if (multiImageLoaders.length === 1) { + return getCountFromNode(multiImageLoaders[0]); + } + + return null; + } + + // --- Backup polling via setInterval (4 Hz) --- + const pollInterval = setInterval(() => { + if (!node.graph) { + clearInterval(pollInterval); + return; + } + const count = readSourceImageCount(node); + if (count !== null) { + node._applyWidgetCount(count); + } + }, 250); + + // Clean up the interval when the node is deleted + const origOnRemoved = node.onRemoved; + node.onRemoved = function() { + // Unregister this node instance + window._LTXKeyframerGlobalNodes.delete(node); + + clearInterval(pollInterval); + if (origOnRemoved) origOnRemoved.apply(this, arguments); + }; + + // --- Connection change handler --- + const onConnectionsChange = node.onConnectionsChange; + node.onConnectionsChange = function(type, index, connected, link_info) { + if (onConnectionsChange) onConnectionsChange.apply(this, arguments); + + if (type === 1) { // 1 = Input + const input = this.inputs[index]; + if (input && input.name === "multi_input") { + if (connected) { + setTimeout(() => { + const count = readSourceImageCount(this); + this._applyWidgetCount(count !== null ? count : (this.properties.num_images || 0)); + }, 100); + } else { + this._applyWidgetCount(0); + } + } + } + }; + + // --- Initial sync when first placed on canvas --- + const origOnAdded = node.onAdded; + node.onAdded = function() { + if (origOnAdded) origOnAdded.apply(this, arguments); + setTimeout(() => { + const count = readSourceImageCount(this); + this._applyWidgetCount(count !== null ? count : (this.properties.num_images || 0)); + }, 100); + }; + } +}); \ No newline at end of file diff --git a/js/ltx_sequencer.js b/js/ltx_sequencer.js new file mode 100644 index 0000000..27b18f5 --- /dev/null +++ b/js/ltx_sequencer.js @@ -0,0 +1,419 @@ +import { app } from "../../scripts/app.js"; + +// Global registry to track all LTXSequencer nodes across all subgraphs +window._LTXSequencerGlobalNodes = window._LTXSequencerGlobalNodes || new Set(); + +// ComfyUI native trick to cleanly hide/show widgets without deleting them +function toggleWidget(widget, visible) { + if (visible) { + if (widget.origType !== undefined) { + widget.type = widget.origType; + widget.computeSize = widget.origComputeSize; + delete widget.origType; + delete widget.origComputeSize; + } + } else { + if (widget.type !== "hidden") { + widget.origType = widget.type; + widget.origComputeSize = widget.computeSize; + widget.type = "hidden"; + widget.computeSize = () => [0, -4]; + } + } +} + +// --- NEW SYNC HELPER FUNCTION --- +// Finds all other LTXSequencer nodes globally and mirrors the value to them +function syncWidgetAcrossNodes(sourceNode, widgetName, value) { + if (!window._LTXSequencerGlobalNodes) return; + + for (const targetNode of window._LTXSequencerGlobalNodes) { + // Target all OTHER LTXSequencer nodes by direct object reference + if (targetNode !== sourceNode) { + + // 1. Always update the hidden properties cache so it remembers the sync + // even if the widget isn't currently visible (e.g. fewer images loaded right now) + targetNode.properties[widgetName] = value; + + // 2. If the widget is currently visible on the UI, update it visually + if (targetNode.widgets) { + const targetWidget = targetNode.widgets.find(w => w.name === widgetName); + if (targetWidget && targetWidget.value !== value) { + targetWidget.value = value; + targetNode.setDirtyCanvas(true, false); + } + } + } + } +} + +app.registerExtension({ + name: "Comfy.LTXSequencer.DynamicInputs", + async nodeCreated(node) { + if (node.comfyClass !== "LTXSequencer") return; + + // Register this node instance globally + window._LTXSequencerGlobalNodes.add(node); + + node._currentImageCount = -1; // Force first update + + // Initialize persistent properties cache + node.properties = node.properties || {}; + + // Add subtle separator line above images_loaded + node.addCustomWidget({ + name: "num_images_separator", + type: "text", + draw(ctx, node, widget_width, y, widget_height) { + ctx.save(); + ctx.strokeStyle = "#444"; + ctx.lineWidth = 1; + ctx.beginPath(); + ctx.moveTo(10, y + 5); + ctx.lineTo(widget_width - 10, y + 5); + ctx.stroke(); + ctx.restore(); + }, + computeSize(width) { + return [width, 10]; + } + }); + + // Move separator before num_images + const moveSeparator = () => { + const idx = node.widgets.findIndex(w => w.name === "num_images"); + const sepIdx = node.widgets.findIndex(w => w.name === "num_images_separator"); + if (idx !== -1 && sepIdx !== -1) { + const separator = node.widgets.splice(sepIdx, 1)[0]; + node.widgets.splice(idx, 0, separator); + } + }; + setTimeout(moveSeparator, 50); // Small delay to ensure num_images is present + + // Core update: synchronize widget visibility to match imageCount + node._applyWidgetCount = function(count) { + const isInitialLoad = this._currentImageCount === -1; + + if (this._currentImageCount === count && !isInitialLoad) return; + this._currentImageCount = count; + + const initialWidth = this.size[0]; + const numWidget = this.widgets?.find(w => w.name === "num_images"); + if (numWidget) { + numWidget.label = "images_loaded"; + numWidget.value = Math.max(0, Math.min(count || 0, 50)); + } + + // 1. Store current widget values in properties BEFORE removing them + // We skip reading from `this.widgets` on the initial load because it might be scrambling. + if (!isInitialLoad && this.widgets) { + this.widgets.forEach(w => { + if (w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) { + this.properties[w.name] = w.value; + } + }); + } + + // 2. Remove all existing dynamic insert_frame/strength/header widgets + if (this.widgets) { + this.widgets = this.widgets.filter(w => + !w.name.startsWith("insert_frame_") && + !w.name.startsWith("strength_") && + !w.name.startsWith("header_") + ); + } else { + this.widgets = []; + } + + // 3. Add back exactly the right amount of widgets using the cached values + for (let i = 1; i <= count; i++) { + // Add header/separator widget for grouping + const headerName = `header_${i}`; + this.addCustomWidget({ + name: headerName, + type: "text", + value: `Image #${i}`, + draw(ctx, node, widget_width, y, widget_height) { + ctx.save(); + const margin = 10; + const topPadding = 15; + + // Subtle separator line + ctx.strokeStyle = "#333"; + ctx.lineWidth = 1; + ctx.beginPath(); + ctx.moveTo(margin, y + 5); + ctx.lineTo(widget_width - margin, y + 5); + ctx.stroke(); + + // Text label + ctx.fillStyle = "#dddddd"; // Light gray + ctx.font = "bold 12px Arial"; + ctx.textAlign = "left"; + ctx.fillText(`Image #${i}`, margin, y + topPadding + 10); + ctx.restore(); + }, + computeSize(width) { + return [width, 35]; // Vertical gap + label height + } + }); + + const insertFrameWidgetName = `insert_frame_${i}`; + const strengthWidgetName = `strength_${i}`; + + // Add insert_frame widget with Sync Callback + const savedInsertFrameValue = this.properties[insertFrameWidgetName]; + this.addWidget("number", insertFrameWidgetName, + savedInsertFrameValue !== undefined ? savedInsertFrameValue : 0, + (value) => { + const rounded = Math.round(value); + this.properties[insertFrameWidgetName] = rounded; + syncWidgetAcrossNodes(this, insertFrameWidgetName, rounded); // Sync out + }, { min: -9999, max: 9999, step: 10, precision: 0 } + ); + + // Add strength widget with Sync Callback + const savedStrengthValue = this.properties[strengthWidgetName]; + this.addWidget("number", strengthWidgetName, + savedStrengthValue !== undefined ? savedStrengthValue : 1.0, + (value) => { + this.properties[strengthWidgetName] = value; + syncWidgetAcrossNodes(this, strengthWidgetName, value); // Sync out + }, { min: 0.0, max: 1.0, step: 0.01 } + ); + } + + this.setDirtyCanvas(true, true); + requestAnimationFrame(() => { + if (this.computeSize) { + this.setSize(this.computeSize()); + this.size[0] = initialWidth; // keep width fixed when restructuring + } + }); + }; + + // --- STRICT ARRAY MAPPER: FIXES ALL SHIFTING FOREVER --- + // This runs the exact instant the node is loaded, before any UI widgets shift indices. + // It locks the perfectly mapped array values directly into our properties dictionary. + const origConfigure = node.configure; + node.configure = function(info) { + if (origConfigure) { + origConfigure.apply(this, arguments); + } + if (this.widgets) { + this.widgets.forEach(w => { + if (w.name === "num_images" || w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) { + this.properties[w.name] = w.value; + } + }); + } + }; + + // Handle deserialization to load properties properly from JSON + const originalOnConfigure = node.onConfigure; + node.onConfigure = function(info) { + if (originalOnConfigure) { + originalOnConfigure.apply(this, arguments); + } + if (info.properties) { + this.properties = { ...this.properties, ...info.properties }; + } + setTimeout(() => { + const count = readSourceImageCount(this); + // Fallback to properties.num_images if source node disconnected + let targetCount = count !== null ? count : (this.properties.num_images || 0); + this._applyWidgetCount(targetCount); + }, 100); + }; + + // --- STRICT ARRAY GENERATOR --- + // Completely detach from ComfyUI's blind visual array saving. + // We construct an exact 101-element strict array that Python expects. + // This makes your node 100% immune to UI/Header index shifting. + const originalOnSerialize = node.onSerialize; + node.onSerialize = function(info) { + // Ensure properties are strictly synced with current widget values before building + if (this.widgets) { + this.widgets.forEach(w => { + if (w.name === "num_images" || w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) { + this.properties[w.name] = w.value; + } + }); + } + + if (originalOnSerialize) { + originalOnSerialize.apply(this, arguments); + } + + info.properties = { ...this.properties }; + + // Build the exact strict array that maps 1-to-1 to the Python backend + const strictArray = []; + const numWidgetVal = this.properties["num_images"]; + strictArray.push(numWidgetVal !== undefined ? numWidgetVal : 1); + + for (let i = 1; i <= 50; i++) { + const fVal = this.properties[`insert_frame_${i}`]; + const sVal = this.properties[`strength_${i}`]; + strictArray.push(fVal !== undefined ? fVal : 0); + strictArray.push(sVal !== undefined ? sVal : 1.0); + } + + info.widgets_values = strictArray; + }; + + // Set up manual num_images widget callback + setTimeout(() => { + const numWidget = node.widgets?.find(w => w.name === "num_images"); + if (numWidget) { + numWidget.callback = (val) => { + node.properties["num_images"] = val; + node._applyWidgetCount(val); + }; + } + }, 100); + + // Exposed receiver for push-based notifications + node._syncImageCount = function(count) { + this._applyWidgetCount(count); + }; + + // Helper: read image count from a connected MultiImageLoader node + function readSourceImageCount(self) { + const multiInput = self.inputs?.find(inp => inp.name === "multi_input"); + if (!multiInput || !multiInput.link) return null; + + const nodeGraph = self.graph || app.graph; + + // Helper to safely trace back through Reroutes and ComfyUI Group Nodes/Subgraphs + function traceUpstream(graph, linkId, visited = new Set()) { + if (!linkId || visited.has(linkId)) return null; + visited.add(linkId); + + const link = graph.links[linkId]; + if (!link) return null; + + const originNode = graph.getNodeById(link.origin_id); + if (!originNode) return null; + + if (originNode.comfyClass === "MultiImageLoader") { + return originNode; + } + + // Traverse Reroute nodes + if (originNode.type === "Reroute" || originNode.comfyClass === "Reroute") { + if (originNode.inputs && originNode.inputs.length > 0 && originNode.inputs[0].link) { + return traceUpstream(graph, originNode.inputs[0].link, visited); + } + } + + // Traverse standard ComfyUI Group Nodes (subgraphs) + if (typeof originNode.getInnerNode === "function") { + try { + const innerNode = originNode.getInnerNode(link.origin_slot); + if (innerNode && innerNode.comfyClass === "MultiImageLoader") { + return innerNode; + } + } catch (e) { + console.warn("Could not trace inner node", e); + } + } + + return null; + } + + let sourceNode = traceUpstream(nodeGraph, multiInput.link); + + // Helper to extract the count once we find a node + function getCountFromNode(n) { + if (typeof n._imageCount === "number") return n._imageCount; + const pathsWidget = n.widgets?.find(w => w.name === "image_paths"); + if (pathsWidget) { + return (pathsWidget.value || "").split('\n').map(p => p.trim()).filter(p => p.length > 0).length; + } + return null; + } + + if (sourceNode) { + return getCountFromNode(sourceNode); + } + + // Fallback Strategy: If it is connected to something, but we couldn't resolve it + // directly (e.g. complex nested 3rd party subgraphs), scan the entire UI. + // If there is EXACTLY ONE MultiImageLoader in the workspace, safely assume that's the one. + let multiImageLoaders = []; + function findAllLoaders(nodes) { + if (!nodes) return; + for (let n of nodes) { + if (n.comfyClass === "MultiImageLoader") { + multiImageLoaders.push(n); + } + if (n.subgraph && n.subgraph._nodes) { + findAllLoaders(n.subgraph._nodes); + } + } + } + if (app.graph && app.graph._nodes) { + findAllLoaders(app.graph._nodes); + } + + if (multiImageLoaders.length === 1) { + return getCountFromNode(multiImageLoaders[0]); + } + + return null; + } + + // --- Backup polling via setInterval (4 Hz) --- + const pollInterval = setInterval(() => { + if (!node.graph) { + clearInterval(pollInterval); + return; + } + const count = readSourceImageCount(node); + if (count !== null) { + node._applyWidgetCount(count); + } + }, 250); + + // Clean up the interval when the node is deleted + const origOnRemoved = node.onRemoved; + node.onRemoved = function() { + // Unregister this node instance + window._LTXSequencerGlobalNodes.delete(node); + + clearInterval(pollInterval); + if (origOnRemoved) origOnRemoved.apply(this, arguments); + }; + + // --- Connection change handler --- + const onConnectionsChange = node.onConnectionsChange; + node.onConnectionsChange = function(type, index, connected, link_info) { + if (onConnectionsChange) onConnectionsChange.apply(this, arguments); + + if (type === 1) { // 1 = Input + const input = this.inputs[index]; + if (input && input.name === "multi_input") { + if (connected) { + setTimeout(() => { + const count = readSourceImageCount(this); + this._applyWidgetCount(count !== null ? count : (this.properties.num_images || 0)); + }, 100); + } else { + this._applyWidgetCount(0); + } + } + } + }; + + // --- Initial sync when first placed on canvas --- + const origOnAdded = node.onAdded; + node.onAdded = function() { + if (origOnAdded) origOnAdded.apply(this, arguments); + setTimeout(() => { + const count = readSourceImageCount(this); + this._applyWidgetCount(count !== null ? count : (this.properties.num_images || 0)); + }, 100); + }; + } +}); \ No newline at end of file diff --git a/js/multi_image_loader.js b/js/multi_image_loader.js new file mode 100644 index 0000000..9f04d9c --- /dev/null +++ b/js/multi_image_loader.js @@ -0,0 +1,561 @@ +import { app } from "../../scripts/app.js"; +import { api } from "../../scripts/api.js"; + +app.registerExtension({ + name: "Comfy.MultiImageLoader", + async nodeCreated(node) { + if (node.comfyClass !== "MultiImageLoader") return; + + // --- 1. UI Setup: Main Container --- + const container = document.createElement("div"); + container.style.cssText = ` + width: 100%; + background: #222222; + border: 1px solid #353545; + border-radius: 4px; + margin-top: 5px; + padding: 10px; + box-sizing: border-box; + display: flex; + flex-direction: column; + gap: 10px; + pointer-events: auto; + overflow: hidden; + `; + + // Top Bar for Actions + const topBar = document.createElement("div"); + topBar.style.cssText = "display: flex; justify-content: flex-start; align-items: center; width: 100%; gap: 8px;"; + + const uploadBtn = document.createElement("button"); + uploadBtn.innerText = "Upload Images"; + uploadBtn.style.cssText = ` + background: #3a3f4b; color: white; border: 1px solid #5a5f6b; + padding: 3px 8px; border-radius: 3px; cursor: pointer; font-size: 10px; + `; + + const removeAllBtn = document.createElement("button"); + removeAllBtn.innerText = "Remove All"; + removeAllBtn.style.cssText = ` + background: #cc2222; color: white; border: 1px solid #aa1111; + padding: 3px 8px; border-radius: 3px; cursor: pointer; font-size: 10px; + transition: background 0.2s; + `; + removeAllBtn.onmouseenter = () => { removeAllBtn.style.background = "#ff3333"; }; + removeAllBtn.onmouseleave = () => { removeAllBtn.style.background = "#cc2222"; }; + removeAllBtn.onclick = () => { + setWidgetValue([], false); + }; + + topBar.appendChild(uploadBtn); + topBar.appendChild(removeAllBtn); + container.appendChild(topBar); + + // The Grid Area - Setup to center the dynamically packed square blocks + const grid = document.createElement("div"); + grid.style.cssText = ` + position: relative; /* Crucial for anti-flicker offset calculations */ + flex-grow: 1; + display: grid; + gap: 8px; + width: 100%; + justify-content: center; + align-content: center; + `; + container.appendChild(grid); + + const fileInput = document.createElement("input"); + fileInput.type = "file"; + fileInput.multiple = true; + fileInput.accept = "image/*"; + fileInput.style.display = "none"; + container.appendChild(fileInput); + + // Add the Widget to the Node + const galleryWidget = node.addDOMWidget("Gallery", "html_gallery", container, { serialize: false }); + + // Permanently neutralize the DOM widget's built-in computeSize to prevent infinite LiteGraph loops + galleryWidget.computeSize = () => [0, 0]; + + // Find the paths widget and hide it + const pathsWidget = node.widgets.find(w => w.name === "image_paths"); + if (pathsWidget) { + pathsWidget.type = "hidden"; + if (pathsWidget.element) pathsWidget.element.style.display = "none"; + } + + const oldCallback = pathsWidget.callback; + + // Centralized helper to prevent infinite loops when updating values internally + function setWidgetValue(newPathsArray, isRearranging = false) { + const val = newPathsArray.join("\n"); + + // Temporarily silence the main callback + const tempCallback = pathsWidget.callback; + pathsWidget.callback = null; + + pathsWidget.value = val; + if (oldCallback) oldCallback.apply(pathsWidget, [val]); + + pathsWidget.callback = tempCallback; + refreshGallery(isRearranging); + } + + // --- 2. Logic: Output Syncing & Dynamic Packing --- + // Manages image_N outputs (slots 1+) while always preserving multi_output at slot 0 + function syncOutputs(count) { + if (!node.outputs) return; + + let changed = false; + // Target = multi_output (slot 0) + count image outputs + const targetTotal = count + 1; + + // Remove excess outputs from the end, but NEVER remove slot 0 (multi_output) + while (node.outputs.length > targetTotal && node.outputs.length > 1) { + node.removeOutput(node.outputs.length - 1); + changed = true; + } + + // Add missing image_N outputs after multi_output + for (let i = node.outputs.length; i < targetTotal; i++) { + node.addOutput(`image_${i}`, "IMAGE"); + changed = true; + } + + if (changed) { + updateLayout(); + } + } + + // Push-based notification: broadcast image count to all connected nodes + function notifyConnectedNodes(imageCount) { + if (!node.outputs) return; + for (const output of node.outputs) { + if (!output.links) continue; + for (const linkId of output.links) { + const link = app.graph.links[linkId]; + if (!link) continue; + const targetNode = app.graph.getNodeById(link.target_id); + if (targetNode && typeof targetNode._syncImageCount === "function") { + targetNode._syncImageCount(imageCount); + } + } + } + } + + // 2D Square Packing Algorithm: Calculates the optimal grid sizes to fill empty space + function optimizeGrid(nodeW, containerH) { + const paths = (pathsWidget.value || "").split(/\n|,/).map(s => s.trim()).filter(s => s); + const N = paths.length; + + if (N === 0) { + grid.style.gridTemplateColumns = 'repeat(auto-fit, minmax(75px, 1fr))'; + grid.style.gridAutoRows = 'max-content'; + return; + } + + // Approximate the available internal working space + const gridW = nodeW - 22; // Container padding + border + const gridH = containerH - 60; // Top bar height + container padding + gap + + if (gridW <= 0 || gridH <= 0) return; + + let bestS = 0; + let bestCols = 1; + + // Test every possible column combination to find the one that yields the largest squares + for (let c = 1; c <= N; c++) { + const r = Math.ceil(N / c); + const maxW = (gridW - (c - 1) * 8) / c; + const maxH = (gridH - (r - 1) * 8) / r; + const size = Math.min(maxW, maxH); + + if (size > bestS) { + bestS = size; + bestCols = c; + } + } + + bestS = Math.max(75, Math.floor(bestS)); // Keep a minimum size floor + + // Force the grid to perfectly adopt the optimal maximum square scale + grid.style.gridTemplateColumns = `repeat(${bestCols}, ${bestS}px)`; + grid.style.gridAutoRows = `${bestS}px`; + } + + // Centralized measurement function shared by automatic updates and manual resizes + function getGalleryHeights() { + const baseHeight = node.computeSize()[1]; + + // Temporarily force natural height measurement using minimum settings + const oldHeight = container.style.height; + const oldCols = grid.style.gridTemplateColumns; + const oldRows = grid.style.gridAutoRows; + + container.style.height = 'fit-content'; + grid.style.gridTemplateColumns = `repeat(auto-fit, minmax(75px, 1fr))`; + grid.style.gridAutoRows = `max-content`; + + const naturalGalleryHeight = container.offsetHeight || 100; + const minNodeHeight = baseHeight + naturalGalleryHeight + 15; + + // Restore styles instantly + container.style.height = oldHeight; + grid.style.gridTemplateColumns = oldCols; + grid.style.gridAutoRows = oldRows; + + return { baseHeight, minNodeHeight }; + } + + let isLayouting = false; + let isFirstLayout = true; + function updateLayout(forceHeight = null) { + if (isLayouting) return; + isLayouting = true; + + const { baseHeight, minNodeHeight } = getGalleryHeights(); + + let targetW = Math.max(node.size[0], 240); + let targetH = forceHeight !== null ? forceHeight : node.size[1]; + + if (isFirstLayout) { + targetH = 0; // Force shrink to minimum bounds on initial load + isFirstLayout = false; + } + + // Enforce minimum height + targetH = Math.max(targetH, minNodeHeight); + + if (node.size[0] !== targetW || node.size[1] !== targetH) { + node.setSize([targetW, targetH]); + app.graph.setDirtyCanvas(true, true); + } + + const availableGalleryHeight = targetH - baseHeight - 15; + container.style.height = availableGalleryHeight + "px"; + + // Recalculate and stretch image squares using the new node space + optimizeGrid(targetW, availableGalleryHeight); + + isLayouting = false; + } + + // Intercept user dragging the node corner to strictly enforce size constraints + const origOnResize = node.onResize; + node.onResize = function(size) { + if (origOnResize) origOnResize.call(this, size); + if (isLayouting) return; // Prevent duplicate cycles + + const { baseHeight, minNodeHeight } = getGalleryHeights(); + + // Prevent user from making node smaller than the minimum content + size[0] = Math.max(size[0], 240); + size[1] = Math.max(size[1], minNodeHeight); + + // Immediately apply the fluid heights for smooth dragging + const availableGalleryHeight = size[1] - baseHeight - 15; + container.style.height = availableGalleryHeight + "px"; + + // Expand the image slots instantly as you drag + optimizeGrid(size[0], availableGalleryHeight); + }; + + // Auto-adjust layout if dimensions change programmatically (e.g., undo/redo wrap reflows) + let lastWidth = -1; + let lastHeight = -1; + const resizeObserver = new ResizeObserver((entries) => { + for (const entry of entries) { + const currentWidth = entry.contentRect.width; + const currentHeight = entry.contentRect.height; + if ((lastWidth !== -1 && Math.abs(currentWidth - lastWidth) > 2) || + (lastHeight !== -1 && Math.abs(currentHeight - lastHeight) > 2)) { + requestAnimationFrame(() => updateLayout()); + } + lastWidth = currentWidth; + lastHeight = currentHeight; + } + }); + resizeObserver.observe(container); + + // --- 3. Logic: Gallery Rendering --- + let draggedNode = null; + let lastSwapX = 0; + let lastSwapY = 0; + let lastSwapTime = 0; + + function refreshGallery(isRearranging = false) { + grid.innerHTML = ""; + const paths = (pathsWidget.value || "").split(/\n|,/).map(s => s.trim()).filter(s => s); + + if (!isRearranging) { + syncOutputs(paths.length); + } + // Cache image count on the node for easy access by connected nodes + node._imageCount = paths.length; + // Push notification: immediately tell connected nodes about the new count + notifyConnectedNodes(paths.length); + + paths.forEach((path, index) => { + const item = document.createElement("div"); + item.dataset.path = path; // Store path on the node for easy retrieval + item.draggable = true; + item.style.cssText = ` + position: relative; + width: 100%; + height: 100%; + aspect-ratio: 1 / 1; + background: #000000; + border-radius: 4px; + border: 1px solid #444; + overflow: hidden; + cursor: grab; + display: flex; + align-items: center; + justify-content: center; + will-change: transform; + `; + + const img = document.createElement("img"); + img.src = `/api/view?filename=${encodeURIComponent(path)}&type=input`; + img.style.cssText = "max-width: 100%; max-height: 100%; object-fit: contain; pointer-events: none; display: block;"; + + // Delete Button + const del = document.createElement("div"); + del.style.cssText = ` + position: absolute; top: 0; right: 0; + background: #cc2222; color: white; + width: 18px; height: 18px; + display: flex; align-items: center; justify-content: center; + font-size: 14px; cursor: pointer; z-index: 10; + font-family: Arial, sans-serif; font-weight: bold; + line-height: 1; border-bottom-left-radius: 4px; + transition: background 0.2s; + `; + del.innerHTML = ` + + `; + + del.onmouseenter = () => { del.style.background = "#ff3333"; }; + del.onmouseleave = () => { del.style.background = "#cc2222"; }; + + del.onclick = (e) => { + e.stopPropagation(); + const newPaths = paths.filter((_, i) => i !== index); + setWidgetValue(newPaths, false); + }; + + // Number Badge + const numBadge = document.createElement("div"); + numBadge.style.cssText = ` + position: absolute; bottom: 0; left: 0; + background: rgba(0, 0, 0, 0.75); color: #fff; + padding: 2px 6px; font-size: 11px; font-family: sans-serif; + font-weight: bold; border-top-right-radius: 4px; pointer-events: none; + z-index: 5; + `; + numBadge.innerText = (index + 1).toString(); + + // Dynamic Animated Drag & Drop Events + item.ondragstart = (e) => { + draggedNode = item; + // Delay opacity drop so the browser capture image remains opaque + setTimeout(() => { + if (draggedNode === item) { + item.style.opacity = "0.4"; + item.style.pointerEvents = "none"; // Prevent drag ghost from capturing events + } + }, 0); + e.dataTransfer.effectAllowed = "move"; + }; + + item.ondragend = () => { + if (draggedNode) { + draggedNode.style.opacity = "1"; + draggedNode.style.pointerEvents = "auto"; + } + draggedNode = null; + + // The DOM visually reorders during dragover. Here we finalize it to data. + const newPaths = Array.from(grid.children).map(n => n.dataset.path); + const currentVal = (pathsWidget.value || "").trim(); + if (newPaths.join("\n") !== currentVal) { + setWidgetValue(newPaths, true); + } + }; + + item.ondragover = (e) => { + e.preventDefault(); + e.stopPropagation(); // Stop ComfyUI canvas listener from grabbing this internally + if (!draggedNode || draggedNode === item) return; + + // ANTI-FLICKER 1: Prevent rapid swaps if the mouse hasn't moved physically. + // Reduced delay from 300ms to 50ms and distance to 5px to drastically improve responsiveness + // while still absorbing the immediate CSS transform shock. + const distMoved = Math.hypot(e.clientX - lastSwapX, e.clientY - lastSwapY); + if (Date.now() - lastSwapTime < 50 && distMoved < 5) { + return; + } + + // ANTI-FLICKER 2: True logical target boundaries. + // Reduced the buffer from 25% down to 10%, meaning 80% of the target square + // is now an active drop zone, making it much easier to trigger a swap. + const gridRect = grid.getBoundingClientRect(); + const mouseX = e.clientX - gridRect.left; + const mouseY = e.clientY - gridRect.top; + + const left = item.offsetLeft; + const top = item.offsetTop; + const width = item.offsetWidth; + const height = item.offsetHeight; + + const bufferX = width * 0.10; + const bufferY = height * 0.10; + + if (mouseX < left + bufferX || mouseX > left + width - bufferX || + mouseY < top + bufferY || mouseY > top + height - bufferY) { + return; + } + + const items = Array.from(grid.children); + const draggedIdx = items.indexOf(draggedNode); + const targetIdx = items.indexOf(item); + + // FLIP Animation Step 1: Record old positions + const rects = new Map(); + items.forEach(node => rects.set(node, node.getBoundingClientRect())); + + // Physically move the DOM element to the new slot + if (draggedIdx < targetIdx) { + grid.insertBefore(draggedNode, item.nextSibling); + } else { + grid.insertBefore(draggedNode, item); + } + + // FLIP Animation Step 2: Calculate difference and animate + items.forEach(node => { + const oldRect = rects.get(node); + const newRect = node.getBoundingClientRect(); + const dx = oldRect.left - newRect.left; + const dy = oldRect.top - newRect.top; + + if (dx !== 0 || dy !== 0) { + // Instantly shift it visually back to the old spot + node.style.transition = 'none'; + node.style.transform = `translate(${dx}px, ${dy}px)`; + + // Force browser layout recalculation + node.offsetWidth; + + // Turn on transition and remove transform so it glides to its real new position + node.style.transition = 'transform 0.3s cubic-bezier(0.25, 0.8, 0.25, 1)'; + node.style.transform = ''; + } + }); + + // Log the swap to lock out rapid feedback triggers + lastSwapX = e.clientX; + lastSwapY = e.clientY; + lastSwapTime = Date.now(); + }; + + item.ondrop = (e) => { + e.preventDefault(); + e.stopPropagation(); // Stop ComfyUI canvas listener + // Finalization is handled safely in ondragend + }; + + item.appendChild(img); + item.appendChild(del); + item.appendChild(numBadge); + grid.appendChild(item); + }); + + if (!isRearranging) { + requestAnimationFrame(() => updateLayout()); + } + } + + // --- 4. Logic: File Handling --- + async function handleFiles(files) { + const uploaded = []; + for (const file of files) { + const body = new FormData(); + body.append("image", file); + try { + const resp = await api.fetchApi("/upload/image", { method: "POST", body }); + if (resp.status === 200) { + const data = await resp.json(); + let name = data.name; + if (data.subfolder) name = data.subfolder + "/" + name; + uploaded.push(name); + } + } catch (e) { console.error("Upload error", e); } + } + if (uploaded.length > 0) { + const current = (pathsWidget.value || "").trim(); + const allPaths = current ? current.split('\n').concat(uploaded) : uploaded; + setWidgetValue(allPaths, false); + } + } + + uploadBtn.onclick = () => fileInput.click(); + fileInput.onchange = (e) => handleFiles(e.target.files); + + container.ondragover = (e) => { + e.preventDefault(); + e.stopPropagation(); // Prevent ComfyUI from seeing the drag event over this node + container.style.borderColor = "#4CAF50"; + }; + container.ondragleave = (e) => { + e.preventDefault(); + e.stopPropagation(); // Prevent ComfyUI from seeing the drag event leave + container.style.borderColor = "#353545"; + }; + container.ondrop = (e) => { + e.preventDefault(); + e.stopPropagation(); // Crucial: Stop ComfyUI from capturing the dropped file and making a LoadImage node! + container.style.borderColor = "#353545"; + if (e.dataTransfer.files.length > 0) handleFiles(e.dataTransfer.files); + }; + + // --- 5. Logic: Paste Handling --- + const pasteHandler = (e) => { + // Only capture the paste if THIS specific node is currently selected in the graph + if (app.canvas.selected_nodes && app.canvas.selected_nodes[node.id]) { + const items = e.clipboardData?.items; + if (!items) return; + + const files = []; + for (let i = 0; i < items.length; i++) { + if (items[i].kind === 'file' && items[i].type.startsWith('image/')) { + files.push(items[i].getAsFile()); + } + } + + if (files.length > 0) { + e.preventDefault(); + e.stopImmediatePropagation(); // Crucial: Stops ComfyUI from turning the pasted image into a "Load Image" node + handleFiles(files); + } + } + }; + + // Use capture: true to intercept the event BEFORE ComfyUI's default global paste listener triggers + document.addEventListener("paste", pasteHandler, { capture: true }); + + // Clean up the global event listener if the node is deleted + const origOnRemoved = node.onRemoved; + node.onRemoved = function() { + document.removeEventListener("paste", pasteHandler, { capture: true }); + if (origOnRemoved) origOnRemoved.apply(this, arguments); + }; + + // Hooks the main callback for external state loads (e.g., undo/redo or initial graph load) + pathsWidget.callback = (v) => { + if (oldCallback) oldCallback.apply(pathsWidget, [v]); + refreshGallery(); + }; + + setTimeout(() => refreshGallery(), 100); + } +}); \ No newline at end of file diff --git a/ltx_keyframer.py b/ltx_keyframer.py new file mode 100644 index 0000000..e508a34 --- /dev/null +++ b/ltx_keyframer.py @@ -0,0 +1,117 @@ +import torch +import comfy.utils +from comfy_api.latest import io + +class LTXKeyframer(io.ComfyNode): + @classmethod + def define_schema(cls): + inputs = [ + io.Vae.Input("vae", tooltip="Video VAE used to encode the images"), + io.Latent.Input("latent", tooltip="Video latent to insert images into"), + io.Image.Input("multi_input", tooltip="Batched images from MultiImageLoader"), + ] + + inputs.append(io.Int.Input("num_images", default=1, min=0, max=50, step=1, display_name="images_loaded", tooltip="Select how many index/strength widgets to configure.")) + + for i in range(1, 51): # 1 to 50 images + inputs.extend([ + io.Int.Input( + f"insert_frame_{i}", + default=0, + min=-9999, + max=9999, + step=1, + tooltip=f"Frame insert_frame for image {i} (in pixel space).", + optional=True, + ), + io.Float.Input( + f"strength_{i}", + default=1.0, + min=0.0, + max=1.0, + step=0.01, + tooltip=f"Strength for image {i}.", + optional=True, + ), + ]) + + return io.Schema( + node_id="LTXKeyframer", + display_name="LTX Keyframer", + category="LTXVCustom", + description="Replaces video latent frames with the encoded input images. Number of widgets is dynamically configured.", + inputs=inputs, + outputs=[ + io.Latent.Output(display_name="latent", tooltip="The video latent with the images inserted and latent noise mask updated."), + ], + ) + + @classmethod + def execute(cls, vae, latent, multi_input, num_images, **kwargs) -> io.NodeOutput: + + samples = latent["samples"].clone() + scale_factors = vae.downscale_index_formula + _, height_scale_factor, width_scale_factor = scale_factors + + batch, _, latent_frames, latent_height, latent_width = samples.shape + width = latent_width * width_scale_factor + height = latent_height * height_scale_factor + + # Get existing noise mask if present, otherwise create new one + if "noise_mask" in latent: + conditioning_latent_frames_mask = latent["noise_mask"].clone() + else: + conditioning_latent_frames_mask = torch.ones( + (batch, 1, latent_frames, 1, 1), + dtype=torch.float32, + device=samples.device, + ) + + batch_size = multi_input.shape[0] if multi_input is not None else 0 + + # We process inputs up to num_images, extracting values from kwargs + for i in range(1, num_images + 1): + # Skip if this image index exceeds the batch + if i > batch_size: + continue + + image = multi_input[i-1:i] # Extract the single image frame from the batch + if image is None: + continue + + insert_frame = kwargs.get(f"insert_frame_{i}") + if insert_frame is None: + continue + strength = kwargs.get(f"strength_{i}", 1.0) + + if image.shape[1] != height or image.shape[2] != width: + pixels = comfy.utils.common_upscale(image.movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1) + else: + pixels = image + encode_pixels = pixels[:, :, :, :3] + t = vae.encode(encode_pixels) + + # Convert pixel frame insert_frame to latent insert_frame + time_scale_factor = scale_factors[0] + + # Handle negative indexing in pixel space + pixel_frame_count = (latent_frames - 1) * time_scale_factor + 1 + if insert_frame < 0: + insert_frame = pixel_frame_count + insert_frame + + # Convert to latent insert_frame + latent_idx = insert_frame // time_scale_factor + + # Clamp to valid range + latent_idx = max(0, min(latent_idx, latent_frames - 1)) + + # Calculate end insert_frame, ensuring we don't exceed latent_frames + end_index = min(latent_idx + t.shape[2], latent_frames) + + # Replace samples at the specified insert_frame range + samples[:, :, latent_idx:end_index] = t[:, :, :end_index - latent_idx] + + # Update mask at the specified insert_frame range + conditioning_latent_frames_mask[:, :, latent_idx:end_index] = 1.0 - strength + + return io.NodeOutput({"samples": samples, "noise_mask": conditioning_latent_frames_mask}) \ No newline at end of file diff --git a/ltx_sequencer.py b/ltx_sequencer.py new file mode 100644 index 0000000..629afbc --- /dev/null +++ b/ltx_sequencer.py @@ -0,0 +1,107 @@ +from comfy_extras.nodes_lt import get_noise_mask, LTXVAddGuide +import torch +import comfy.utils +from comfy_api.latest import io + +class LTXSequencer(LTXVAddGuide): + @classmethod + def define_schema(cls): + inputs = [ + io.Conditioning.Input("positive", tooltip="Positive conditioning to which guide keyframe info will be added"), + io.Conditioning.Input("negative", tooltip="Negative conditioning to which guide keyframe info will be added"), + io.Vae.Input("vae", tooltip="Video VAE used to encode the guide images"), + io.Latent.Input("latent", tooltip="Video latent, guides are added to the end of this latent"), + io.Image.Input("multi_input", tooltip="Batched images from MultiImageLoader"), + ] + + inputs.append(io.Int.Input("num_images", default=1, min=0, max=50, step=1, display_name="images_loaded", tooltip="Select how many index/strength widgets to configure.")) + + for i in range(1, 51): # 1 to 50 images + inputs.extend([ + io.Int.Input( + f"insert_frame_{i}", + default=0, + min=-9999, + max=9999, + step=1, + tooltip=f"Frame insert_frame for image {i} (in pixel space).", + optional=True, + ), + io.Float.Input( + f"strength_{i}", + default=1.0, + min=0.0, + max=1.0, + step=0.01, + tooltip=f"Strength for image {i}.", + optional=True, + ), + ]) + + return io.Schema( + node_id="LTXSequencer", + display_name="LTX Sequencer", + category="LTXVCustom", + description="Add multiple guide images at specified frame indices with strengths. Number of widgets is dynamically configured.", + inputs=inputs, + outputs=[ + io.Conditioning.Output(display_name="positive"), + io.Conditioning.Output(display_name="negative"), + io.Latent.Output(display_name="latent", tooltip="Video latent with added guides"), + ], + ) + + @classmethod + def execute(cls, positive, negative, vae, latent, multi_input, num_images, **kwargs) -> io.NodeOutput: + scale_factors = vae.downscale_index_formula + + # Clone latents to avoid overwriting previous nodes' operations + latent_image = latent["samples"].clone() + + # Helper logic to fetch or generate a noise mask + if "noise_mask" in latent: + noise_mask = latent["noise_mask"].clone() + else: + batch, _, latent_frames, latent_height, latent_width = latent_image.shape + noise_mask = torch.ones( + (batch, 1, latent_frames, 1, 1), + dtype=torch.float32, + device=latent_image.device, + ) + + _, _, latent_length, latent_height, latent_width = latent_image.shape + batch_size = multi_input.shape[0] if multi_input is not None else 0 + + # Process inputs up to num_images, extracting dynamic frame/strength values from kwargs + for i in range(1, num_images + 1): + # Skip if this image index exceeds the batch + if i > batch_size: + continue + + img = multi_input[i-1:i] # Extract the single image frame from the batch + if img is None: + continue + + f_idx = kwargs.get(f"insert_frame_{i}") + if f_idx is None: + continue + strength = kwargs.get(f"strength_{i}", 1.0) + + # Execution logic mirrored from LTXVAddGuideMulti + image_1, t = cls.encode(vae, latent_width, latent_height, img, scale_factors) + + frame_idx, latent_idx = cls.get_latent_index(positive, latent_length, len(image_1), f_idx, scale_factors) + assert latent_idx + t.shape[2] <= latent_length, "Conditioning frames exceed the length of the latent sequence." + + positive, negative, latent_image, noise_mask = cls.append_keyframe( + positive, + negative, + frame_idx, + latent_image, + noise_mask, + t, + strength, + scale_factors, + ) + + return io.NodeOutput(positive, negative, {"samples": latent_image, "noise_mask": noise_mask}) \ No newline at end of file diff --git a/multi_image_loader.py b/multi_image_loader.py new file mode 100644 index 0000000..c54eb4a --- /dev/null +++ b/multi_image_loader.py @@ -0,0 +1,98 @@ +import torch +import numpy as np +from PIL import Image, ImageOps +import os +import folder_paths +import io + +class MultiImageLoader: + @classmethod + def INPUT_TYPES(s): + return { + "required": { + "image_paths": ("STRING", {"default": "", "multiline": True}), + "width": ("INT", {"default": 0, "min": 0, "max": 8192, "step": 1}), + "height": ("INT", {"default": 0, "min": 0, "max": 8192, "step": 1}), + "upscale_method": (["lanczos", "bilinear", "nearest-exact"],), + "divisible_by": ("INT", {"default": 32, "min": 1, "max": 512, "step": 1}), + "img_compression": ("INT", {"default": 18, "min": 0, "max": 100, "step": 1}), + }, + } + + # Added "IMAGE" at the beginning for multi_output + 50 individual outputs = 51 outputs + RETURN_TYPES = ("IMAGE",) * 51 + RETURN_NAMES = ("multi_output",) + tuple(f"image_{i+1}" for i in range(50)) + FUNCTION = "load_images" + CATEGORY = "image" + + def load_images(self, image_paths, width, height, upscale_method, divisible_by, img_compression): + results = [] + valid_paths = [p.strip() for p in image_paths.split("\n") if p.strip()] + + # Track the dimensions of the first processed image + first_target_w, first_target_h = None, None + + for path in valid_paths: + try: + # Resolve full path + full_path = path + if not os.path.exists(full_path): + full_path = os.path.join(folder_paths.get_input_directory(), path) + + if not os.path.exists(full_path): + print(f"Warning: Image path not found: {path}") + continue + + image = Image.open(full_path) + image = ImageOps.exif_transpose(image) + image = image.convert("RGB") + + orig_w, orig_h = image.size + target_w, target_h = width, height + + if target_w == 0 and target_h == 0: + target_w, target_h = orig_w, orig_h + elif target_w == 0: + target_w = int(orig_w * (target_h / orig_h)) + elif target_h == 0: + target_h = int(orig_h * (target_w / orig_w)) + + # Divisible by constraint + target_w = (target_w // divisible_by) * divisible_by + target_h = (target_h // divisible_by) * divisible_by + + # To prevent torch.cat errors, ALL images in the batch must match the dimensions + # of the first successfully loaded image. + if first_target_w is None: + first_target_w, first_target_h = target_w, target_h + else: + target_w, target_h = first_target_w, first_target_h + + if target_w != orig_w or target_h != orig_h: + resample = Image.LANCZOS if upscale_method == "lanczos" else Image.BILINEAR + image = image.resize((target_w, target_h), resample=resample) + + # Compression + if img_compression > 0: + img_byte_arr = io.BytesIO() + image.save(img_byte_arr, format="JPEG", quality=max(1, 100 - img_compression)) + image = Image.open(img_byte_arr) + + image_np = np.array(image).astype(np.float32) / 255.0 + results.append(torch.from_numpy(image_np)[None,]) + except Exception as e: + print(f"Error loading {path}: {e}") + + # Combine all successfully loaded images into a single batched tensor for multi_output + if len(results) > 0: + multi_output = torch.cat(results, dim=0) + else: + # Fallback empty tensor if no valid paths + multi_output = torch.zeros((1, 64, 64, 3)) + results = [multi_output] + + # Pad individual outputs exactly to length 50 as defined in RETURN_TYPES + padded_results = results + [torch.zeros((1, 64, 64, 3))] * (50 - len(results)) + + # Return the multi batch output first, followed by the individual padded items + return (multi_output, *padded_results[:50]) \ No newline at end of file