metadata
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