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

pip install ultralytics opencv-python

Usage

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

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

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