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---
license: apache-2.0
tags:
- steganography
- image-classification
- onnx
- computer-vision
library_name: transformers
pipeline_tag: image-classification
datasets:
- custom
metrics:
- accuracy
- f1
- auc
---
# Model Card: Starlight Unified Model 2025
## Model Overview
- **Task**: Detection / Extraction
- **Architecture**: Unified CNN-based Encoder-Decoder with Residual Blocks
- **Input**: 256x256 RGB/RGBA or metadata
- **Output**:
- Detector: sigmoid probability
- Extractor: variable-length byte sequence
## Training
- **Dataset**: Combined submissions (grok, gemini, claude, chatgpt, sample)
- **Epochs**: 50
- **Batch Size**: 16
- **Optimizer**: Adam
- **Loss**: BCE + MSE (detector), CrossEntropy (extractor)
## Performance
| Metric | Value |
|--------|-------|
| Accuracy | 96.3% |
| AUC-ROC | 0.996 |
| F1 Score | 0.982 |
| Extraction BER | 0.003 |
## Steganography Coverage
- `lsb`, `alpha`, `dct`, `exif`, `eoi`, `palette`
## Inference Speed
- CPU: 12 ms/image
- GPU: 2.1 ms/image
## License
- Model: Apache 2.0
- Code: MIT
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