---
license: mit
tags:
- yolo
- object-detection
- watermark-detection
library_name: ultralytics
pipeline_tag: object-detection
---

# YOLO11x – Fine-tuned Watermark Detector

This is a **fine-tuned YOLO11x model for watermark & logo detection**, built upon the original **fancyfeast/joycaption-watermark-detection** model (by fancyfeast). I further trained it on a custom dataset for improved performance.

---

##  Model Details

| Feature        | Value                             |
|----------------|-----------------------------------|
| Base checkpoint | `fancyfeast/joycaption-watermark-detection` |
| Input size     | 1280 × 1280                      |
| Framework      | PyTorch / Ultralytics YOLO11x     |

## Installation

```bash
pip install ultralytics opencv-python
```

## Usage

### Python
```python
from ultralytics import YOLO
import cv2

# Load model
model = YOLO("corzent/yolo11x_watermark_detection")

# Run inference
results = model("test.jpg", conf=0.35)

# Visualize
annotated = results[0].plot()
cv2.imwrite("result.jpg", annotated)
```

### CLI
```bash
yolo predict model=your-username/wm_yolo11_ft source="test.jpg" conf=0.3
```

## Results

| Metric   | Value  |
|----------|--------|
| Precision| 0.896  |
| Recall   | 0.883  |
| mAP@50   | 0.900  |
| mAP@50-95| 0.686  |

## Model Info

- Base model: YOLO11x  
- Trained on: custom watermark/logo dataset

## License

This model is provided for **research and educational purposes only**.  
Do not use for removing watermarks from copyrighted content.

---
🤝 Created by Corzent