ComfyUI - 视觉基础任务检测(Detection) 和分割(Segmentation) 的 Impact-Pack 流程教程

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SXM

在 ComfyUI 的 Impact-Pack 插件中，检测(Detection) 是 YOLO v8 系列，分割(Segmentation) 是 SAM 的第1个版本，目前不支持最新版本，实现基础的检测与分割任务，实现人物与物体的分割。

ComfyUI：https://github.com/comfyanonymous/ComfyUI

1. 模型准备

Load Image 节点，上传图像位于：

[your folder]/ComfyUI/input

SAM 模型：位于 ComfyUI/models/sams，HuggingFace 的下载路径：

wget https://huggingface.co/segments-arnaud/sam_vit_h/resolve/main/sam_vit_h_4b8939.pth

模型大小：

ComfyUI/models/sams
├── [358M]  sam_vit_b_01ec64.pth
└── [2.4G]  sam_vit_h_4b8939.pth

YOLO 模型位于 ComfyUI/models/ultralytics，即：

ComfyUI/models/ultralytics
├── [4.0K]  bbox
│   ├── [ 50M]  face_yolov8m.pt
│   └── [ 21M]  hand_yolov8s.pt
└── [4.0K]  segm
    ├── [ 23M]  deepfashion2_yolov8s-seg.pt
    ├── [ 52M]  face_yolov8m-seg_60.pt
    ├── [6.5M]  hair_yolov8n-seg_60.pt
    └── [ 52M]  person_yolov8m-seg.pt

下载路径：https://huggingface.co/Bingsu/adetailer/tree/main

2. 任务流程

YOLO 的检测和分割流程：
Det&Seg
YOLO + SAM 的检测和分割流程：

SAM

两类流程的效果对比，左侧是 YOLO 的效果，右侧是使用 SAM 的效果，轮廓更加清晰：

流程 Json：

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