This model is nipples detection model for ADetailer / ComfyUI-Impact-Pack extension.
Segmentation: Detects the edges of nipples and areolae
nipples_v2_yolov11s-seg.pt
nipples_yolov8s-seg.pt
BBox: Detects nipples with bounding box.
nipples_yolov8s.pt
Notice:
nipples_yolov8s-seg.pt and nipples_yolov8s.pt are old YOLO model, so ComfyUI with PyTorch 2.6 and later will prevent these models from loading for security reasons.
(In the case of ADetailer, the problem does not occur because ADetailer loads the model with weights_only=False forcibly)
The workaround is as follows:
Use nipples_v2_yolov11s-seg.pt (recommended)
Add model name to <user_directory>/default/ComfyUI-Impact-Subpack/model-whitelist.txt (refer https://github.com/ltdrdata/ComfyUI-Impact-Subpack#model-loading-configuration-related-to-weights_only)
Usage (ADetailer):
Put this model into ADetailer model folder. (in the case of AUTOMATIC1111 and Forge, "models/adetailer")
Relaunch webui.
Enable Adetailer and select this model.
Adjust threshold, denoising and padding as needed.
Usage (ComfyUI):
Install ComfyUI-Impact-Pack and ComfyUI-Impact-Subpack
Put this model into "/models/ultralytics/segm" (Segmentation model) or "/models/ultralytics/bbox" (BBox model)
Relaunch ComfyUI.
Create workflow using UltralyticsDetectorProvider node and Detailer node. (or drop ComfyUI_sample_workflow.png into ComfyUI and modify embedded workflow)
Adjust threshold, denoise, crop_factor, feather and so on as needed.
ADetailer configuration sample:
The recommended values vary depending on the model, character orientation, and breast size.
Detection model confidence threshold: 0.5
Inpaint mask blur: 8-16
Inpaint denoising strength: 0.3-0.4
Inpaint only masked padding, pixels: 48-96
Notes:
BBox model was trained with anime images only, so use for realistic images is not supported.
Segmentation model was trained with anime and realistic images.
If you get "RuntimeWarning: invalid value encountered in cast x_sample = x_sample.astype(np.uint8)" error message and get black masked image (after that, you only get whole black images unless restart webui) using ADetailer, PyTorch 2.7 and cu128, try changing Ultralytics device to CPU. Reference.
Description
Changed the detection model to YOLO11
The number of training and validation images was increased by approximately 2 times.
Changed training target image size from 640 to 1024