# Medical Skin Anatomy &amp; Clothing Segmenter (YOLOv8-seg)This is a YOLOv8m-seg (instance segmentation) model trained to detect and segment 15 anatomical regions and clothing coverage states. It is designed for use in content moderation pipelines, medical imaging research, or with the ADetailer extension in Stable Diffusion (Automatic1111 / ComfyUI) to automatically mask or inpaint specific regions of the body.---### ⚠️ Important Note on Class NamesFor platform compliance, the class names are published with neutral/medical terminology. The internal model names are different. If you load the weights <code>.pt</code> or <code>.onnx</code>) directly in Python, you can print the original class names using <code>model.names</code>.### Classes (15 total):* 0: body_f* 1: pelvis_m* 2: face_f* 3: pelvis_f* 4: gluteus_f* 5: body_m* 6: chest_f* 7: lower_pelvis_f* 8: covered_chest_f* 9: covered_pelvis_f* 10: face_m* 11: covered_gluteus_f* 12: chest_m* 13: gluteus_m* 14: lower_pelvis_m---### 🚀 How to use with ADetailer (Stable Diffusion)1. Download the <code>yolo_v5_best.pt</code> file.2. Put the file inside your <code>stable-diffusion-webui/models/adetailer/</code> folder.3. In the WebUI, enable ADetailer and select <code>yolo_v5_best.pt</code>.4. Configure your mask settings based on the class indexes above to inpaint or censor specific areas.

Sam Vision - Medical Skin Anatomy & Clothing Segmenter (YOLOv8-seg)

Initial release of the YOLOv8m-seg weights for ADetailer usage.

Files with SHA256: b227494e2c33d93a43f337462f1ad40b8d02471cb8bc71d48ac07e17761cb358