luxdelux7/ForbiddenVision_Models

Custom-trained models for face detection and segmentation across realistic, anime, and NSFW content.

Made for the Forbidden Vision ComfyUI custom nodes

GitHub Repository

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🎯 Why These Models Exist

Traditional face models fail where it matters most for AI art workflows:

Problem	Why It Matters
🎨 Domain-locked	Existing models excel at either anime or realistic—never both
🔞 NSFW blindness	Most models trained only on SFW data break on adult content
👁️‍🗨️ Detail blindness	Most models miss anime eyebrows, real eyelashes etc.
🎲 Generation artifacts	Standard datasets don't include diffusion model quirks and failures

These models solve all 4.

The segmentation model predicts face masks, stylistic eyebrows, eyelashes etc.

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📊 Training Foundation

The Dataset Difference

Built from 14,000+ manually annotated images across the domains that actually matter for AI generation:

🎨 Multi-Domain Coverage SDXL, SD1.5, Pony, Illustrious outputs Curated Danbooru (anime styles) Real photography Full NSFW inclusion (no filtering)

💎 Edge Case Priority ✓ Extreme angles & occlusions ✓ Failed/broken generations ✓ Low-quality artifacts ✓ Unusual expressions & poses ✓ Everything other models ignore

What This Means For You

Traditional models: Trained on clean celebrity faces
         ↓
    Fail on real workflows

These models: Trained on what you actually generate
         ↓
    Work when you need them

One model family. Every domain. Zero compromises.

Model Details

Face Detection (YOLOv11-Small)

Purpose: Primary face detection with high recall

Training Approach:

• After every training run, I ran the model on a new mixed dataset, hardmining failures and improving the dataset until an acceptable performance was reached
• Trained at 640px resolution (inference should use same resolution)

Why YOLOv11-Small instead of nano?
More reliable detection across mixed realistic/anime domains with acceptable speed tradeoff.

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Segmentation (EfficientNet-v2)

Purpose: Precise face mask generation

Training Approach:

• Dataset prepared using the Forbidden Vision YOLO model at 512px resolution
• Iterative hardmine training in multiple phases:
  • Train on the initial 700 samples
  • Evaluate on remaining images to find failure cases
  • Correct failed masks and add them to the dataset
  • Retrain with the expanded dataset
  • Repeat until failure cases drop to near-zero
    (final dataset: 4k+ images)

Features:

• Detects and includes facial features other models ignore, like protruding anime eybrows, realistic eyelashes sticking out of the face etc.
• Glasses and similar are treated as part of the face, even if sticking outside the face shape
• NSFW friendly across both anime, realistic and 3d domains

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Usage

These models are automatically downloaded and used by the Fixer node in ComfyUI Forbidden Vision.

License

Apache 2.0

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Contact

• GitHub: ComfyUI-Forbidden-Vision
• Issues: GitHub Issues
• Support: Ko-fi