Tracefy is an advanced AI-powered system that transforms rough criminal sketches and descriptive text prompts into realistic facial images. Built for forensic and law enforcement applications, Tracefy leverages cutting-edge generative models to modernize suspect identification and accelerate investigations.
Tracefy bridges the gap between victim/witness memory and actionable visual evidence using a multi-stage AI pipeline involving sketch refinement and text-guided image generation.
Input: User-drawn outline sketch + natural language description
Output: High-resolution photorealistic facial image
https://github.com/user-attachments/assets/135e0008-9b91-470f-ba7c-ac142a291200
Sketch-to-Image Translation
Converts rough outlines into high-resolution face images.
Dual Conditioning
Fuses geometry (sketch) with semantic cues (text) to guide image generation.
Real-Time Inference
GPU-accelerated pipeline for fast, web-based generation.
User Interface
React.js frontend with secure, role-based access (RBAC).
Bias Mitigation
Built-in fairness monitoring to ensure demographic balance.
Law Enforcement Tools
Secure dashboard to manage sketches, generation history, and retrievals.
Sketch Refinement
Uses a CycleGAN-based model for line cleanup and style normalization.
Image Generation
Integrates refined sketch and user prompt using:
Prompt Iteration
Interactive session flow for refining and improving generated faces.
| Task | Model |
|---|---|
| Sketch Cleanup | CycleGAN |
| Image Generation | FLUX.1-dev + ControlNet |
| Fine-tuning | LoRA (Low-Rank Adaptation) |
| Layer | Technology |
|---|---|
| Frontend | React.js |
| Backend | Flask (Python) |
| ML Framework | PyTorch, TensorFlow |
| Data Storage | MySQL, MongoDB |
| Model Infra | Google Colab, Hugging Face |
| Metric | Purpose |
|---|---|
| Canny Edge Similarity | Structural accuracy measurement |
| Perceptual Hash (pHash) | Visual resemblance scoring |
| Hamming Distance | Quantifies binary differences in hashes |
Tracefy is a B2G (Business-to-Government) solution. Target sectors include:
Tracefy is developed for academic and public safety purposes. For licensing or usage inquiries, please contact the authors.
Jupyter Notebook
60.3%
Python
28.8%
Shell
4.1%
HTML
3.5%
CSS
1.9%
Tracefy is an advanced AI-powered system that transforms rough criminal sketches and descriptive text prompts into realistic facial images. Built for forensic and law enforcement applications, Tracefy leverages cutting-edge generative models to modernize suspect identification and accelerate investigations.
Tracefy bridges the gap between victim/witness memory and actionable visual evidence using a multi-stage AI pipeline involving sketch refinement and text-guided image generation.
Input: User-drawn outline sketch + natural language description
Output: High-resolution photorealistic facial image
https://github.com/user-attachments/assets/135e0008-9b91-470f-ba7c-ac142a291200
Sketch-to-Image Translation
Converts rough outlines into high-resolution face images.
Dual Conditioning
Fuses geometry (sketch) with semantic cues (text) to guide image generation.
Real-Time Inference
GPU-accelerated pipeline for fast, web-based generation.
User Interface
React.js frontend with secure, role-based access (RBAC).
Bias Mitigation
Built-in fairness monitoring to ensure demographic balance.
Law Enforcement Tools
Secure dashboard to manage sketches, generation history, and retrievals.
Sketch Refinement
Uses a CycleGAN-based model for line cleanup and style normalization.
Image Generation
Integrates refined sketch and user prompt using:
Prompt Iteration
Interactive session flow for refining and improving generated faces.
| Task | Model |
|---|---|
| Sketch Cleanup | CycleGAN |
| Image Generation | FLUX.1-dev + ControlNet |
| Fine-tuning | LoRA (Low-Rank Adaptation) |
| Layer | Technology |
|---|---|
| Frontend | React.js |
| Backend | Flask (Python) |
| ML Framework | PyTorch, TensorFlow |
| Data Storage | MySQL, MongoDB |
| Model Infra | Google Colab, Hugging Face |
| Metric | Purpose |
|---|---|
| Canny Edge Similarity | Structural accuracy measurement |
| Perceptual Hash (pHash) | Visual resemblance scoring |
| Hamming Distance | Quantifies binary differences in hashes |
Tracefy is a B2G (Business-to-Government) solution. Target sectors include:
Tracefy is developed for academic and public safety purposes. For licensing or usage inquiries, please contact the authors.
Jupyter Notebook
60.3%
Python
28.8%
Shell
4.1%
HTML
3.5%
CSS
1.9%