DemonGatanjieuandClaude Opus 5.5
88eaa77472
Codex's hand tests (2026-10-29): at denoise 0.55-0.75 the repainted hand
filled its whole mark and came out too big, at 0.4 it kept its size. The
crop-and-stitch block now repaints at 0.45 (the built-in one at 0.5), and
its next step and the inpaint note tell the AI to mark tightly, keep the
strength low, make 4 tries and let the user pick.
Slider and picks blocks take a zoom {x, y, w, h}: every picture shows
only that part, enlarged, from the picture itself. The checks of block
parts move to ai_panel_parts.py (ai_panels.py was at the 600-line line).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
73 lines
1.8 KiB
JSON
73 lines
1.8 KiB
JSON
{
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"job": "repaint",
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"rank": 3,
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"short": "built-in nodes",
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"title": {
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"zh": "局部重绘·官方节点",
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"en": "Repaint: built-in nodes"
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},
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"about": {
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"zh": "只用 ComfyUI 自带的节点重画圈出的地方，没装别的包时用。",
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"en": "ComfyUI's own nodes only: for when the packs above are missing."
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},
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"source": {
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"zh": "ComfyUI 官方的局部重绘做法",
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"en": "ComfyUI's own way to inpaint"
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},
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"packs": {},
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"takes": "inpaint",
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"nodes": {
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"picture": {
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"class_type": "LoadImage",
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"inputs": {
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"image": "$image"
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}
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},
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"soft": {
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"class_type": "DifferentialDiffusion",
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"inputs": {
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"model": [
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"$sampler.model",
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"*"
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]
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},
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"wire_to": "$sampler"
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},
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"encode": {
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"class_type": "VAEEncode",
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"inputs": {
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"pixels": [
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"picture",
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0
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],
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"vae": [
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"$decode.vae",
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"*"
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]
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}
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},
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"area": {
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"class_type": "SetLatentNoiseMask",
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"inputs": {
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"samples": [
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"encode",
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0
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],
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"mask": [
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"picture",
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1
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]
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},
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"wire_to": "$sampler"
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}
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},
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"roles": {
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"sampler": {
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"denoise": 0.5
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}
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},
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"after": "The sampler repaints only the area, at denoise 0.5 so it keeps the picture's look (higher changes more). The marked area's size becomes the size of what is painted there: mark tightly around it (a hand, not the arm beside it). Keep denoise 0.35-0.5 to fix something and keep its size and pose; 0.7 and up paints a new thing that fills the whole mark. Hands and faces vary a lot from seed to seed: run_workflow with batch 4 and let the user pick, rather than judging one. Then run_workflow.",
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"models": [],
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"tested": {}
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}
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