マッティングとは？
マッティング（Image Matting）は、グリーンバック撮影のような特別な準備なしに、普通の写真や画像から前景と背景を分離するタスクです。
いわゆる「背景除去サービス」の多くは、このマッティング技術をベースにしています。
髪の毛のような細かい部分も、できるだけ自然に切り抜くのがマッティングの目標です。単純な2値マスク（白黒だけ）ではなく、アルファマットと呼ばれる半透明の情報も含めたマスクを生成します。
BiRefNet
BiRefNetは前景抽出用のモデルファミリーで、背景除去・マット生成に特化した高精度モデルです。
軽量で高性能なので、マッティングならBiRefNetを選んでおけば間違いないです。
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"last_node_id": 5,
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"nodes": [
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"type": "LoadImage",
"pos": [
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"size": [
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"flags": {},
"order": 0,
"mode": 0,
"inputs": [],
"outputs": [
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"links": [
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},
{
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"type": "MASK",
"links": null
}
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"properties": {
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"widgets_values": [
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"mode": 0,
"inputs": [
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"outputs": [],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.76",
"Node name for S&R": "PreviewImage"
},
"widgets_values": []
},
{
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"type": "BiRefNetRMBG",
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"size": [
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"flags": {},
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"inputs": [
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"outputs": [
{
"name": "IMAGE",
"type": "IMAGE",
"links": [
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]
},
{
"name": "MASK",
"type": "MASK",
"links": null
},
{
"name": "MASK_IMAGE",
"type": "IMAGE",
"links": null
}
],
"properties": {
"cnr_id": "comfyui-rmbg",
"ver": "2.9.4",
"Node name for S&R": "BiRefNetRMBG"
},
"widgets_values": [
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"color": "#232",
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"links": [
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"groups": [],
"config": {},
"extra": {
"ds": {
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"offset": [
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},
"frontendVersion": "1.34.3",
"VHS_latentpreview": false,
"VHS_latentpreviewrate": 0,
"VHS_MetadataImage": true,
"VHS_KeepIntermediate": true
},
"version": 0.4
}
いくつか派生モデルがありますが、まずはgeneralから試してみてください。人物・物体・動物など、幅広い対象に対応しています。
SDMatte
SDMatteは、Stable Diffusionの知識を利用したマッティングモデルです。
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"size": [
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"flags": {},
"order": 0,
"mode": 0,
"inputs": [],
"outputs": [
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"links": [
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},
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}
],
"properties": {
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"ver": "0.3.76",
"Node name for S&R": "LoadImage",
"image": "clipspace/clipspace-painted-masked-1764669141236.png [input]"
},
"widgets_values": [
"clipspace/clipspace-painted-masked-1764669141236.png [input]",
"image"
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{
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"type": "PreviewImage",
"pos": [
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"size": [
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"flags": {},
"order": 3,
"mode": 0,
"inputs": [
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"name": "images",
"type": "IMAGE",
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}
],
"outputs": [],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.76",
"Node name for S&R": "PreviewImage"
},
"widgets_values": []
},
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"pos": [
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"inputs": [
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"outputs": [],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.76",
"Node name for S&R": "PreviewImage"
},
"widgets_values": []
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{
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"type": "AILab_SDMatte",
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"size": [
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"flags": {},
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"inputs": [
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"name": "image",
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}
],
"outputs": [
{
"name": "IMAGE",
"type": "IMAGE",
"links": [
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]
},
{
"name": "MASK",
"type": "MASK",
"links": null
},
{
"name": "MASK_IMAGE",
"type": "IMAGE",
"links": null
}
],
"properties": {
"cnr_id": "comfyui-rmbg",
"ver": "2.9.4",
"Node name for S&R": "AILab_SDMatte"
},
"widgets_values": [
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"color": "#232",
"bgcolor": "#353"
}
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"links": [
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"groups": [],
"config": {},
"extra": {
"ds": {
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"offset": [
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},
"frontendVersion": "1.34.3",
"VHS_latentpreview": false,
"VHS_latentpreviewrate": 0,
"VHS_MetadataImage": true,
"VHS_KeepIntermediate": true
},
"version": 0.4
}
BiRefNetと同じように前景切り抜きもできますが、ガラス瓶・液体・薄い布など、透けて見えるものもある程度扱えるのが特徴です。
拡散ベースの運命として計算コストは高いですが、透明・半透明のオブジェクト、毛先といった極細のものを切り抜きたいときは試してみてください。