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Includes 30 custom nodes committed directly, 7 Civitai-exclusive loras stored via Git LFS, and a setup script that installs all dependencies and downloads HuggingFace-hosted models on vast.ai. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
55 lines
3.3 KiB
Markdown
55 lines
3.3 KiB
Markdown
# ComfyUI-Impact-Subpack
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This node pack provides nodes that complement the [ComfyUI Impact Pack](https://github.com/ltdrdata/ComfyUI-Impact-Pack), such as the UltralyticsDetectorProvider.
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## Nodes
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* `UltralyticsDetectorProvider` - Loads the Ultralystics model to provide SEGM_DETECTOR, BBOX_DETECTOR.
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- Unlike `MMDetDetectorProvider`, for segm models, `BBOX_DETECTOR` is also provided.
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- The various models available in UltralyticsDetectorProvider can be downloaded through **ComfyUI-Manager**.
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## Ultralytics models
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* When using ultralytics models, save them separately in `models/ultralytics/bbox` and `models/ultralytics/segm` depending on the type of model. Many models can be downloaded by searching for `ultralytics` in the Model Manager of ComfyUI-Manager.
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* huggingface.co/Bingsu/[adetailer](https://huggingface.co/Bingsu/adetailer/tree/main) - You can download face, people detection models, and clothing detection models.
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* ultralytics/[assets](https://github.com/ultralytics/assets/releases/) - You can download various types of detection models other than faces or people.
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* civitai/[adetailer](https://civitai.com/search/models?sortBy=models_v5&query=adetailer) - You can download various types detection models....Many models are associated with NSFW content.
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## Paths
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* In `extra_model_paths.yaml`, you can add the following entries:
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- `ultralytics_bbox` - Specifies the paths for bbox YOLO models.
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- `ultralytics_segm` - Specifies the paths for segm YOLO models.
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- `ultralytics` - Allows the presence of `bbox/` and `segm/` subdirectories.
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## Model loading configuration related to `weights_only`
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* Loading model files can involve executing code, so if malicious code is embedded in a model, it can pose a security risk. For this reason, PyTorch 2.6 and later have introduced features for safer model loading. The issue is that older model files, which were created without such safe loading (weights_only) restrictions, may occasionally fail to load properly.
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* By listing the paths of models deemed safe in `<user_directory>/default/ComfyUI-Impact-Subpack/model-whitelist.txt`, those specific models will have weights_only disabled, allowing them to be loaded without restriction.
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* `<user_directory>`: typically located at ComfyUI/user.
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## How To Install?
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### Install via ComfyUI-Manager (Recommended)
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* Search `ComfyUI Impact Subpack` in ComfyUI-Manager and click `Install` button.
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### Manual Install (Not Recommended)
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1. `cd custom_nodes`
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2. `git clone https://github.com/ltdrdata/ComfyUI-Impact-Subpack`
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3. `cd ComfyUI-Impact-Subpack`
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4. `pip install -r requirements.txt`
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* **IMPORTANT**:
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* You must install it within the Python environment where ComfyUI is running.
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* For the portable version, use `<installed path>\python_embeded\python.exe -m pip` instead of `pip`. For a `venv`, activate the `venv` first and then use `pip`.
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5. Restart ComfyUI
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## Credits
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ComfyUI/[ComfyUI](https://github.com/comfyanonymous/ComfyUI) - A powerful and modular stable diffusion GUI.
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Bing-su/[adetailer](https://github.com/Bing-su/adetailer/) - This repository provides an object detection model and features based on Ultralystics.
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huggingface/Bingsu/[adetailer](https://huggingface.co/Bingsu/adetailer/tree/main) - This repository offers various models based on Ultralystics.
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* You can download other models supported by the UltralyticsDetectorProvider from here.
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