DemonGatanjieuandClaude Opus 5.5
525bcfeaea
The hand-fix way now redraws each hand SAM3 finds by the word ("hand:8": the word alone
takes only the likeliest hand) inside its own outline before the hand detector's pass, as
the reference author does. The pass is optional: its nodes go when SAM3's node or model
(sam3.1, now in the ways' model list) is missing, with the nodes that only fed them.
Switch models mid-way says how to enlarge at the switch: a LatentUpscaleBy after the first
part, which then finishes its picture, and the second part adding noise anew. Enlarging
the leftover noise itself (the author's wiring) covered the picture in coloured blocks on
Anima at step 21 and 12. The staged-picture skill says so in one sentence.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
490 lines
14 KiB
JSON
490 lines
14 KiB
JSON
{
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"job": "detail",
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"want": "hands",
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"rank": 2,
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"short": "enlarge, then hands (fallback)",
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"enlarge": {
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"megapixels": 4.2,
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"most": 2.0,
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"unknown": 1.5
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},
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"title": {
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"zh": "修手·先放大再修（备选）",
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"en": "Fix hands: enlarge, then fix (fallback)"
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},
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"about": {
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"zh": "整张图放大到约 400 万像素（小图 2 倍）轻轻重画，让手变大；再把每只手放大重画后贴回去：有 SAM3 模型时先按文字找出贴着手形的轮廓重画一遍，再用手部检测框补修一遍。",
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"en": "The whole picture is enlarged to about 4 megapixels (2× for a small one) and redrawn lightly, so the hands grow; then each hand is redrawn larger and pasted back: with the SAM3 model here, first inside the outline it finds by the word, then once more in the box the hand detector finds."
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},
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"source": {
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"zh": "参考作者的「先放大重画」和「手部精修」两步合在一起，2026-10-29 在 RTX 4050 上试出这组数；SAM3 按文字找手那一轮照他的连法，2026-11-03 加入",
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"en": "The reference author's light redraw after enlarging and his hand detailing, put together; these numbers tried on an RTX 4050 on 2026-10-29; the SAM3 pass finding hands by the word follows his wiring, added on 2026-11-03"
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},
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"packs": {
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"FaceDetailer": "ComfyUI-Impact-Pack",
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"UltralyticsDetectorProvider": "ComfyUI-Impact-Subpack"
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},
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"takes": "picture",
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"detectors": {
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"hand": "hand_yolov8"
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},
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"checkpoints": {
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"sam3": "sam3"
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},
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"roles": {
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"sampler": {
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"denoise": 0.4
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}
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},
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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": "$image"
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}
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},
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"bigger": {
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"class_type": "ImageScaleBy",
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"inputs": {
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"image": [
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"picture",
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0
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],
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"upscale_method": "lanczos",
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"scale_by": "$enlarge"
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}
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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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"bigger",
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0
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],
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"vae": [
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"$decode.vae",
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"*"
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]
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},
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"wire_to": "$sampler"
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},
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"hand_seeker": {
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"class_type": "CheckpointLoaderSimple",
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"optional": true,
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"_meta": {
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"title": "SAM3"
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},
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"inputs": {
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"ckpt_name": "$sam3"
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}
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},
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"hand_words": {
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"class_type": "CLIPTextEncode",
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"optional": true,
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"_meta": {
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"title": "SAM3: what to find"
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},
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"inputs": {
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"text": "hand:8",
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"clip": [
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"hand_seeker",
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1
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]
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}
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},
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"hand_shapes": {
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"class_type": "SAM3_Detect",
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"optional": true,
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"inputs": {
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"model": [
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"hand_seeker",
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0
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],
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"image": [
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"$decode",
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0
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],
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"conditioning": [
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"hand_words",
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0
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],
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"threshold": 0.5,
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"refine_iterations": 2,
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"individual_masks": false
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}
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},
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"hand_areas": {
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"class_type": "MaskToSEGS",
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"optional": true,
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"inputs": {
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"mask": [
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"hand_shapes",
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0
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],
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"combined": false,
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"crop_factor": 2.0,
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"bbox_fill": false,
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"drop_size": 10,
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"contour_fill": false
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}
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},
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"shaped_hands": {
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"class_type": "DetailerForEach",
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"like": "$sampler",
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"optional": true,
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"inputs": {
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"image": [
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"$decode",
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0
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],
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"segs": [
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"hand_areas",
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0
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],
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"model": [
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"$sampler.model",
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"*"
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],
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"clip": [
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"$sampler.positive.clip",
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"*"
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],
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"vae": [
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"$decode.vae",
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"*"
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],
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"positive": [
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"$sampler.positive",
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"*"
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],
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"negative": [
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"$sampler.negative",
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"*"
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],
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"guide_size": 768,
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"max_size": 1024,
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"denoise": 0.45,
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"feather": 5,
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"noise_mask": true,
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"force_inpaint": true,
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"noise_mask_feather": 10,
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"wildcard": "detailed hand"
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}
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},
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"hand_finder": {
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"class_type": "UltralyticsDetectorProvider",
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"inputs": {
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"model_name": "$hand"
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}
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},
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"hands": {
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"class_type": "FaceDetailer",
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"like": "$sampler",
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"inputs": {
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"image": [
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"shaped_hands|$decode",
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0
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],
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"model": [
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"$sampler.model",
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"*"
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],
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"clip": [
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"$sampler.positive.clip",
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"*"
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],
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"vae": [
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"$decode.vae",
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"*"
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],
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"positive": [
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"$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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"bbox_detector": [
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"hand_finder",
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0
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],
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"guide_size": 768,
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"max_size": 1024,
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"denoise": 0.45,
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"bbox_threshold": 0.3,
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"bbox_crop_factor": 2.0,
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"feather": 5,
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"drop_size": 10,
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"wildcard": "detailed hand"
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}
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},
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"save": {
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"class_type": "SaveImage",
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"inputs": {
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"images": [
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"hands",
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"image"
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],
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"filename_prefix": "hands_fixed"
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}
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}
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},
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"after": "A fallback: a FLUX-Fill redraw of one square crop around each hand did better in the user's tests; use that when you have it. The picture is enlarged to about 4 megapixels (2× for one of about 1 megapixel, at most 2×, not at all for a large one) and drawn again lightly (the sampler now takes it, at denoise 0.4), then the hands are redrawn larger: with SAM3 here, first each hand it finds by the word inside its own outline (shaped_hands), then each hand the detector finds, in its box (hands, denoise 0.45), saved with prefix hands_fixed (without SAM3, which the user can get in the ways panel, only the detector's pass); the enlarged one is saved too, without the hand pass. About 3 tries in 4 give a good hand: run_workflow with batch 4 (each try its own seed), then check them before the user does: zoom_image each hands_fixed picture on the hand, compare_with the old picture, and drop a hand with the wrong number of fingers, fused or melted fingers, or one far bigger or smaller than its arm. None good: run_workflow batch 4 again, at most twice. Then a picks panel zoomed on the hand lets the user choose among the good ones.",
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"notes": "Tried on the Codex test picture (1280×832, three characters, the hand about 110×78 px): the hand pass alone gave a good hand in about half the seeds whatever its size (512 or 768) and denoise (0.45 or 0.55); enlarging 1.5× first gave good hands in 3 of 4, 2× gave sharper fingers in the same seeds (about 105 s instead of 75 s). Denoise 0.4 for the enlarged redraw kept the layout; faces and splashes change a little. The SAM3 pass (2026-11-03): its word says how many it takes, \"hand\" alone only the likeliest hand, \"hand:8\" up to eight; on a 832×1216 picture of a girl waving both hands (enlarged 2×) it outlined both hands closely at threshold 0.5 (0.2 found no more), about 112 s with both passes on Anima with the Turbo LoRA.",
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"models": [
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"hand_yolov8s",
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"sam3_1",
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"anima_turbo_lora"
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],
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"tested": {
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"gpu": "RTX 4050 Laptop",
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"vram_gb": 6,
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"date": "2026-11-03",
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"runs": [
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{
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"model": "Anima (Kirazuri v4, Turbo LoRA)",
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"size": "1280×832 → 2560×1664",
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"seconds": 105
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},
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{
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"model": "Anima (MiaoMiao Harem 1.5, Turbo LoRA, SAM3 pass)",
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"size": "832×1216 → 1664×2432",
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"seconds": 112
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}
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]
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},
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"variants": {
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"anima": {
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"loras": {
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"turbo": "anima-turbo-lora"
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},
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"without_loras": "On an Anima model the Anima Turbo LoRA (anima-turbo-lora-v0.2, the user can get it in the ways panel) makes this about three times faster: 10 steps at CFG 1.",
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"roles": {
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"sampler": {
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"denoise": 0.4,
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"steps": 10,
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"cfg": 1.0,
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"sampler_name": "euler_ancestral",
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"scheduler": "normal"
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}
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},
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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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"turbo": {
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"class_type": "LoraLoaderModelOnly",
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"inputs": {
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"model": [
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"$sampler.model",
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"*"
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],
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"lora_name": "$turbo",
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"strength_model": 0.7
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},
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"wire_to": "$sampler"
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},
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"bigger": {
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"class_type": "ImageScaleBy",
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"inputs": {
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"image": [
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"picture",
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0
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],
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"upscale_method": "lanczos",
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"scale_by": "$enlarge"
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}
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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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"bigger",
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0
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],
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||
"vae": [
|
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"$decode.vae",
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"*"
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]
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},
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"wire_to": "$sampler"
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},
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"hand_seeker": {
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"class_type": "CheckpointLoaderSimple",
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"optional": true,
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"_meta": {
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"title": "SAM3"
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},
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"inputs": {
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"ckpt_name": "$sam3"
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}
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},
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"hand_words": {
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"class_type": "CLIPTextEncode",
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"optional": true,
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"_meta": {
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"title": "SAM3: what to find"
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},
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"inputs": {
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"text": "hand:8",
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"clip": [
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"hand_seeker",
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1
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]
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}
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},
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"hand_shapes": {
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"class_type": "SAM3_Detect",
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"optional": true,
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"inputs": {
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"model": [
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"hand_seeker",
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0
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],
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"image": [
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"$decode",
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0
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],
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"conditioning": [
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"hand_words",
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0
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],
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"threshold": 0.5,
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"refine_iterations": 2,
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"individual_masks": false
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}
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},
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"hand_areas": {
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"class_type": "MaskToSEGS",
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"optional": true,
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"inputs": {
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"mask": [
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"hand_shapes",
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0
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],
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"combined": false,
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"crop_factor": 2.0,
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"bbox_fill": false,
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"drop_size": 10,
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"contour_fill": false
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}
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},
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"shaped_hands": {
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"class_type": "DetailerForEach",
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"like": "$sampler",
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"optional": true,
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"inputs": {
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"image": [
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"$decode",
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0
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],
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"segs": [
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"hand_areas",
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0
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],
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"model": [
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"turbo",
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0
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],
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||
"clip": [
|
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"$sampler.positive.clip",
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||
"*"
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],
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"vae": [
|
||
"$decode.vae",
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||
"*"
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||
],
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||
"positive": [
|
||
"$sampler.positive",
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||
"*"
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],
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"negative": [
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"$sampler.negative",
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"*"
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],
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"guide_size": 768,
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"max_size": 1024,
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"steps": 10,
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"cfg": 1.0,
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"sampler_name": "euler_ancestral",
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"scheduler": "normal",
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"denoise": 0.45,
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"feather": 5,
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"noise_mask": true,
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"force_inpaint": true,
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"noise_mask_feather": 10,
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"wildcard": "detailed hand"
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}
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},
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"hand_finder": {
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"class_type": "UltralyticsDetectorProvider",
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"inputs": {
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"model_name": "$hand"
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}
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},
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"hands": {
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"class_type": "FaceDetailer",
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"like": "$sampler",
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"inputs": {
|
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"image": [
|
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"shaped_hands|$decode",
|
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0
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],
|
||
"model": [
|
||
"turbo",
|
||
0
|
||
],
|
||
"clip": [
|
||
"$sampler.positive.clip",
|
||
"*"
|
||
],
|
||
"vae": [
|
||
"$decode.vae",
|
||
"*"
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||
],
|
||
"positive": [
|
||
"$sampler.positive",
|
||
"*"
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||
],
|
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"negative": [
|
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"$sampler.negative",
|
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"*"
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],
|
||
"bbox_detector": [
|
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"hand_finder",
|
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0
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],
|
||
"guide_size": 768,
|
||
"max_size": 1024,
|
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"steps": 10,
|
||
"cfg": 1.0,
|
||
"sampler_name": "euler_ancestral",
|
||
"scheduler": "normal",
|
||
"denoise": 0.45,
|
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"bbox_threshold": 0.3,
|
||
"bbox_crop_factor": 2.0,
|
||
"feather": 5,
|
||
"drop_size": 10,
|
||
"wildcard": "detailed hand"
|
||
}
|
||
},
|
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"save": {
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"class_type": "SaveImage",
|
||
"inputs": {
|
||
"images": [
|
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"hands",
|
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"image"
|
||
],
|
||
"filename_prefix": "hands_fixed"
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||
}
|
||
}
|
||
},
|
||
"after": "A fallback: a FLUX-Fill redraw of one square crop around each hand did better in the user's tests; use that when you have it. On this Anima model the Anima Turbo LoRA (0.7) makes both passes 10 steps at CFG 1, about 105 s for 1280×832 (2×) on a 6 GB card. The picture is enlarged to about 4 megapixels (2× for one of about 1 megapixel, at most 2×, not at all for a large one) and drawn again lightly (the sampler now takes it, at denoise 0.4), then the hands are redrawn larger: with SAM3 here, first each hand it finds by the word inside its own outline (shaped_hands), then each hand the detector finds, in its box (hands, denoise 0.45), saved with prefix hands_fixed (without SAM3, which the user can get in the ways panel, only the detector's pass); the enlarged one is saved too, without the hand pass. About 3 tries in 4 give a good hand: run_workflow with batch 4 (each try its own seed), then check them before the user does: zoom_image each hands_fixed picture on the hand, compare_with the old picture, and drop a hand with the wrong number of fingers, fused or melted fingers, or one far bigger or smaller than its arm. None good: run_workflow batch 4 again, at most twice. Then a picks panel zoomed on the hand lets the user choose among the good ones."
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||
}
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||
}
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}
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