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dermaintel-face-parsing
PayamFard123/dermaintel-face-parsing
dermaintel-face-parsing is a machine learning model from PayamFard123. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This is a BiSeNet-based face parsing model trained on CelebAMask-HQ dataset. Used for accurate hair segmentation in the DermaIntel application.
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Public
Updated Jan 26, 2026
Repo size
53.2 MB
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.onnx53.2 MB · 100%
At a glance
- License
- mit
- Access
- Public
- Created
- Jan 26, 2026
- Updated
- Jan 26, 2026
- SHA
- c1c5fd39
Model card
From the Hugging Face model README
BiSeNet Face Parsing Model (Hair Segmentation)
This is a BiSeNet-based face parsing model trained on CelebAMask-HQ dataset. Used for accurate hair segmentation in the DermaIntel application.
Model Details
- Architecture: BiSeNet with ResNet-18 backbone
- Format: ONNX
- Input Size: 512x512 RGB
- Classes: 19 facial components
Class Labels
| Index | Label |
|---|---|
| 0 | background |
| 1 | skin |
| 2 | l_brow |
| 3 | r_brow |
| 4 | l_eye |
| 5 | r_eye |
| 6 | eye_g (glasses) |
| 7 | l_ear |
| 8 | r_ear |
| 9 | ear_r (earring) |
| 10 | nose |
| 11 | mouth |
| 12 | u_lip |
| 13 | l_lip |
| 14 | neck |
| 15 | neck_l |
| 16 | cloth |
| 17 | hair |
| 18 | hat |
Usage
from huggingface_hub import hf_hub_download
import onnxruntime as ort
# Download model
model_path = hf_hub_download(
repo_id="PayamFard123/dermaintel-face-parsing",
filename="resnet18.onnx"
)
# Load model
session = ort.InferenceSession(model_path)
Original Source
Model weights from: https://github.com/yakhyo/face-parsing
- License
- mit
- Created
- Jan 26, 2026
- Updated
- Jan 26, 2026