Downloads · 30 days
1.6K
11% of all-time downloads
corzent/yolo11x_watermark_detection
yolo11x_watermark_detection is a object detection model from corzent. Use it when you need objects located in an image. It is set up for ultralytics. The card lists the license as mit.
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 perform…
Downloads · 30 days
1.6K
11% of all-time downloads
All-time downloads
13.7K
Public
Repo size
118 MB
Likes
17
Public
Click a slice to open those files.
.pt114 MB · 97%
From the Hugging Face model README
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.
| Feature | Value |
|---|---|
| Base checkpoint | fancyfeast/joycaption-watermark-detection |
| Input size | 1280 × 1280 |
| Framework | PyTorch / Ultralytics YOLO11x |
pip install ultralytics opencv-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)
yolo predict model=your-username/wm_yolo11_ft source="test.jpg" conf=0.3
| Metric | Value |
|---|---|
| Precision | 0.896 |
| Recall | 0.883 |
| mAP@50 | 0.900 |
| mAP@50-95 | 0.686 |
This model is provided for research and educational purposes only.
Do not use for removing watermarks from copyrighted content.
🤝 Created by Corzent