---
title: FracAtlas YOLACT+
emoji: 🦴
colorFrom: red
colorTo: gray
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: Fracture detection and segmentation on X-ray images using YOLACT+ with ResNet-18 backbone, trained on the FracAtlas dataset.
---

# FracAtlas Fracture Detection — YOLACT+ (ResNet-18)

Instance segmentation model for bone fracture detection on X-ray images.

## Model

- **Architecture:** YOLACT+ with ResNet-18 backbone
- **Neck:** Feature Pyramid Network (FPN, 5 levels)
- **Prototypes:** 32 mask prototypes
- **Input size:** 550×550

## Dataset

[FracAtlas](https://figshare.com/articles/dataset/The_dataset/22363012)

| Split | Fractured | Non-fractured | Total |
|-------|-----------|---------------|-------|
| Train | 500 | 500 | 1000 |
| Val   | 100 | 100 | 200  |
| Test  | 100 | 100 | 200  |

## Training

- **Epochs:** 200
- **Optimizer:** AdamW (lr=5e-5, weight_decay=5e-4)
- **Scheduler:** Cosine decay with 5-epoch warmup
- **Loss:** Focal classification + SmoothL1 box + BCE mask

## Results (Validation Set)

| Metric | Value |
|--------|-------|
| Precision | 0.5328 |
| Recall | 0.5422 |
| F1 Score | 0.5374 |
| Avg IoU | 0.9405 |

## Author

Muhammad Adil — MS Data Science, Information Technology University (ITU) Lahore, Pakistan  
GitHub: [Adil6312](https://github.com/Adil6312)

## License

Apache 2.0