Object Detection
ultralytics
ONNX
PyTorch
comfyui
face-detection
face-segmentation
image-segmentation
Instructions to use vdaular/ForbiddenVision_Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use vdaular/ForbiddenVision_Models with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("vdaular/ForbiddenVision_Models", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download config.json from vdaular/ForbiddenVision_Models: direct link, hf CLI and curl.
- Browser
- Download file 629 Bytes
-
https://huggingface.co/vdaular/ForbiddenVision_Models/resolve/main/config.json
- Command line
-
hf download hf://vdaular/ForbiddenVision_Models/config.json
-
curl -L -o config.json https://huggingface.co/vdaular/ForbiddenVision_Models/resolve/main/config.json
629 Bytes
| { | |
| "model_name": "ForbiddenVision Face Detection & Segmentation", | |
| "version": "1.0.0", | |
| "models": { | |
| "face_detection": { | |
| "file": "ForbiddenVision_face_detect_v1.pt", | |
| "architecture": "YOLO11s", | |
| "precision": 0.996, | |
| "recall": 1.0, | |
| "training_data": "14k+ mixed-domain images" | |
| }, | |
| "face_segmentation": { | |
| "file": "ForbiddenVision_face_segment_v1.pth", | |
| "architecture": "TimmUniversalEncoder (tf_efficientnetv2_s.in21k_ft_in1k)", | |
| "training_data": "4k+ mixed-domain images" | |
| } | |
| }, | |
| "usage": "Designed for ComfyUI via ForbiddenVision node pack", | |
| "license": "Apache-2.0" | |
| } |