Add Wan segment example workflows
This commit is contained in:
OnekoSL
@@ -4,9 +4,9 @@ The separate workflow [anima_to_wan2.2_i2v.json](../../pysssss-workflows/anima_t
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The recommended robust continuation path now avoids dynamic ComfyUI loop nodes:
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- [anima_to_wan2.2_segment_start.json](../../pysssss-workflows/anima_to_wan2.2_segment_start.json) renders segment 0 and stores numbered PNG frames.
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- [wan2.2_segment_extend.json](../../pysssss-workflows/wan2.2_segment_extend.json) loads the saved `last_frame.png`, renders one more Wan segment, drops its duplicate first frame, and appends frames to the same run folder.
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- [wan2.2_segment_assemble.json](../../pysssss-workflows/wan2.2_segment_assemble.json) checks the frame sequence and writes the final MP4.
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- [examples/wan22/anima_to_wan2.2_segment_start.json](examples/wan22/anima_to_wan2.2_segment_start.json) renders segment 0 and stores numbered PNG frames.
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- [examples/wan22/wan2.2_segment_extend.json](examples/wan22/wan2.2_segment_extend.json) loads the saved `last_frame.png`, renders one more Wan segment, drops its duplicate first frame, and appends frames to the same run folder.
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- [examples/wan22/wan2.2_segment_assemble.json](examples/wan22/wan2.2_segment_assemble.json) checks the frame sequence and writes the final MP4.
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## Pipeline
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@@ -8,6 +8,7 @@
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- Added the separate `anima_to_wan2.2_i2v.json` pipeline with an Anima keyframe, JoyCaption visual bridge, editable Wan motion instruction, five independent seeds, and verified 17-frame GPU smoke coverage.
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- Added iterative Wan continuation planning, JSON records, and final manifests plus an Easy-Use loop that extends the Anima-to-Wan video by 1-10 segments without duplicate transition frames.
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- Added a robust segmented Wan continuation path with `NukunWan22SegmentStore`, `NukunWan22SegmentLoader`, and `NukunWan22FrameSequenceAssembler`, plus start/extend/assemble workflows that persist PNG frames and assemble the final MP4 without relying on dynamic loop nodes.
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- Added the segmented Wan workflows under `examples/wan22/` so the complete setup is versioned with the custom nodes.
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- Added `4-Prompt Model Cycler Loader (Nukun)` for synchronized four-prompt-per-UNET folder cycles with `increment`, `fixed`, and frontend-randomized model-synchronous seed modes.
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- Added `4-Prompt Checkpoint Cycler Loader (Nukun)` with the same prompt and seed cycles for normal checkpoints with embedded CLIP and VAE outputs.
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- Fixed both 4-prompt cyclers so ComfyUI's automatic seed randomizer is locked to `fixed`; `seed_mode` is now the only seed controller.
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@@ -77,6 +77,8 @@ The main node set and core examples work with a standard ComfyUI installation. T
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- `NukunHiResFixTiled` - display name `HiResFix Tiled (Nukun)`, category `Nukun/Sampling`
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- `NukunTiledHiResFixAdvanced` - display name `Tiled HiRes Fix Advanced (Nukun)`, category `Nukun/Sampling`
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Wan 2.2 example workflows live in `examples/wan22/`, including the segmented Anima-to-Wan start, extension, and final assembly workflows.
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## Checkpoint Cycler Loader
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This node replaces the common `PrimitiveNode` plus `Checkpoint Loader w/Name (WLSH)` pattern.
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Load Diff
@@ -0,0 +1,212 @@
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{
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"last_node_id": 3,
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"last_link_id": 2,
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"nodes": [
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{
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"id": 1,
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"type": "NukunWan22FrameSequenceAssembler",
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"pos": [
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-240,
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-120
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],
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"size": [
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500,
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310
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],
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"flags": {},
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"order": 0,
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"mode": 0,
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"inputs": [
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{
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"localized_name": "run_id",
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"name": "run_id",
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"type": "STRING",
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"widget": {
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"name": "run_id"
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},
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"link": null
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},
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{
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"localized_name": "fps",
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"name": "fps",
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"type": "FLOAT",
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"widget": {
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"name": "fps"
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},
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"link": null
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},
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{
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"localized_name": "filename",
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"name": "filename",
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"type": "STRING",
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"widget": {
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"name": "filename"
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},
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"link": null
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},
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{
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"localized_name": "codec",
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"name": "codec",
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"type": "COMBO",
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"widget": {
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"name": "codec"
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},
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"link": null
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},
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{
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"localized_name": "quality",
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"name": "quality",
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"type": "INT",
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"widget": {
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"name": "quality"
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},
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"link": null
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},
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{
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"localized_name": "overwrite",
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"name": "overwrite",
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"type": "BOOLEAN",
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"widget": {
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"name": "overwrite"
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},
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"link": null
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}
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],
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"outputs": [
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{
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"localized_name": "video_path",
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"name": "video_path",
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"type": "STRING",
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"links": null
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},
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{
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"localized_name": "total_frames",
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"name": "total_frames",
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"type": "INT",
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"links": null
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},
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{
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"localized_name": "duration",
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"name": "duration",
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"type": "FLOAT",
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"links": null
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},
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{
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"localized_name": "manifest_json",
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"name": "manifest_json",
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"type": "STRING",
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"links": null
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},
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{
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"localized_name": "report",
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"name": "report",
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"type": "STRING",
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"links": [
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1
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]
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}
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],
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"title": "Frames ? finales MP4",
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"properties": {
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"aux_id": "OnekoSL/Nukun_ComfyUI_Nodes",
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"Node name for S&R": "NukunWan22FrameSequenceAssembler",
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"ue_properties": {
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"widget_ue_connectable": {},
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"version": "7.8",
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"input_ue_unconnectable": {}
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}
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},
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"widgets_values": [
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"wan_run_001",
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16,
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"final",
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"libx264",
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8,
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true
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]
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},
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{
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"id": 2,
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"type": "PreviewAny",
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"pos": [
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340,
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-90
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],
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"size": [
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300,
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],
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"flags": {},
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"order": 1,
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"mode": 0,
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"inputs": [
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{
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"localized_name": "source",
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"name": "source",
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"type": "*",
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"link": 1
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}
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],
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"outputs": [],
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"title": "Assemble Bericht",
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"properties": {
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"Node name for S&R": "PreviewAny",
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"aux_id": "rgthree-comfy",
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"ue_properties": {
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"version": "7.8",
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"widget_ue_connectable": {},
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"input_ue_unconnectable": {}
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}
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},
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"widgets_values": [
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null,
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null,
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null
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]
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},
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{
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"id": 3,
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"type": "Note",
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"pos": [
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-240,
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],
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"size": [
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720,
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],
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"flags": {},
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"order": 2,
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"mode": 0,
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"inputs": [],
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"outputs": [],
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"title": "Bedienung ? Assemble",
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"properties": {},
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"widgets_values": [
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"Wenn genug Segmente im Run-Ordner liegen, diesen Workflow queuen.\n\nEr pr?ft frames/frame_000000.png ... ohne L?cken und schreibt output/wan_runs/<run_id>/videos/<filename>.mp4.\n\nKein externer ffmpeg-PATH n?tig: die Node nutzt das lokal installierte imageio_ffmpeg-Bundle."
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]
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}
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],
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"links": [
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[
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1,
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1,
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4,
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2,
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0,
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"STRING"
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]
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],
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"groups": [],
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"config": {},
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"extra": {
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"ds": {
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"scale": 1,
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"offset": [
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0,
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0
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]
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}
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},
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"version": 0.4
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}
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File diff suppressed because it is too large
Load Diff
@@ -4,7 +4,8 @@ from pathlib import Path
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COMFY_ROOT = Path(__file__).resolve().parents[3]
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WORKFLOW_DIR = COMFY_ROOT / "pysssss-workflows"
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PACKAGE_ROOT = Path(__file__).resolve().parents[1]
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WORKFLOW_DIR = PACKAGE_ROOT / "examples" / "wan22"
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class WorkflowJson:
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