DemonGatanjieuandClaude Opus 5.5
8b51dffd2b
OpenPose misread anime characters; DWPose (torch detector: the onnx one found nobody with this onnxruntime-gpu) reads a single anime character down to face and fingers. A crowded, heavily stylised picture can still come out empty, so both control blocks keep their map as a PreviewImage the AI sees in run_status's previews, and their next step says what to do when it is empty. Live on the isolated 8199 ComfyUI: DWPose followed a hand-behind-head pose (64 s); the three-elf picture stays unreadable for both readers. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
155 lines
4.8 KiB
JSON
155 lines
4.8 KiB
JSON
{
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"job": "follow",
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"rank": 1,
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"short": "its pose",
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"title": {
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"zh": "照着姿势画",
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"en": "Follow a pose"
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},
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"about": {
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"zh": "你递给 AI 一张图，AMB 读出人物姿势（DWPose），用和你底模对得上的控制网让新图摆出这个姿势。 DWPose 认二次元人物也准，连脸和手指都标；人物挤成一团、画风很浓的图可能认不出，这时用「照着构图画」。 画布上是 Anima 模型时，自动改用 Anima 专用的 LLLite 控制网（需要 ComfyUI-Anima-LLLite）。",
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"en": "From a picture you hand the AI, Anomalous reads the pose (DWPose) and steers the picture with a ControlNet that fits your model. DWPose reads anime characters too, face and fingers included; a crowded or very stylised picture may come out empty, then use Follow a layout. On an Anima model it uses an Anima ControlNet-LLLite instead (needs ComfyUI-Anima-LLLite)."
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},
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"source": {
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"zh": "参考工作流的「底图控制网」组",
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"en": "The reference workflow's ControlNet group"
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},
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"packs": {
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"DWPreprocessor": "comfyui_controlnet_aux"
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},
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"takes": "reference",
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"control": "pose",
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"nodes": {
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"reference": {
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"class_type": "LoadImage",
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"inputs": {
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"image": "$image"
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}
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},
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"pose": {
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"class_type": "DWPreprocessor",
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"inputs": {
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"image": [
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"reference",
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0
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],
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"detect_hand": "enable",
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"detect_body": "enable",
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"detect_face": "enable",
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"resolution": 1024,
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"bbox_detector": "yolox_l.torchscript.pt",
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"pose_estimator": "dw-ll_ucoco_384_bs5.torchscript.pt",
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"scale_stick_for_xinsr_cn": "disable"
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}
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},
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"controlnet": {
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"class_type": "ControlNetLoader",
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"inputs": {
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"control_net_name": "$controlnet"
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}
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},
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"steer": {
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"class_type": "ControlNetApplyAdvanced",
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"inputs": {
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"positive": [
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"$sampler.positive",
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"*"
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],
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"negative": [
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"$sampler.negative",
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"*"
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],
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"control_net": [
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"controlnet",
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0
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],
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"image": [
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"pose",
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0
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],
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"vae": [
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"$decode.vae",
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"*"
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],
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"strength": 0.8,
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"start_percent": 0.0,
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"end_percent": 0.8
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},
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"wire_to": "$sampler"
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},
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"look": {
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"class_type": "PreviewImage",
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"inputs": {
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"images": [
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"pose",
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0
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]
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}
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}
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},
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"after": "run_workflow: the picture now takes that pose (strength 0.8, for the first 80% of the steps; lower either for a looser pose). The prompt still says who and what: change it if it fights the pose. Its pose skeleton is among the run's previews: if it is empty or wrong (a crowded or very stylised picture), try control_depth.",
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"variants": {
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"anima": {
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"packs": {
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"DWPreprocessor": "comfyui_controlnet_aux",
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"AnimaLLLiteApply_sdscripts": "ComfyUI-Anima-LLLite"
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},
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"control": null,
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"lllite": "pose",
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"nodes": {
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"reference": {
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"class_type": "LoadImage",
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"inputs": {
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"image": "$image"
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}
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},
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"pose": {
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"class_type": "DWPreprocessor",
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"inputs": {
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"image": [
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"reference",
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0
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],
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"detect_hand": "enable",
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"detect_body": "enable",
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"detect_face": "enable",
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"resolution": 1024,
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"bbox_detector": "yolox_l.torchscript.pt",
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"pose_estimator": "dw-ll_ucoco_384_bs5.torchscript.pt",
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"scale_stick_for_xinsr_cn": "disable"
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}
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},
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"steer": {
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"class_type": "AnimaLLLiteApply_sdscripts",
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"inputs": {
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"model": [
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"$sampler.model",
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"*"
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],
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"lllite_name": "$lllite",
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"image": [
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"pose",
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0
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],
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"strength": 1.0,
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"start_percent": 0.0,
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"end_percent": 1.0,
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"preserve_wrapper": true
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},
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"wire_to": "$sampler"
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},
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"look": {
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"class_type": "PreviewImage",
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"inputs": {
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"images": [
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"pose",
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0
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]
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}
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}
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},
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"after": "On this Anima model an Anima ControlNet-LLLite steers it, more gently than an SDXL ControlNet: say in the prompt what the picture shows (how many people, what they do), or the prompt wins. Strength 1.0 for all the steps; up to 1.5 holds it closer. run_workflow. Its pose skeleton is among the run's previews: if it is empty or wrong (a crowded or very stylised picture), try control_depth."
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}
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}
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}
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