Instructions to use beanyzoldyck/tiktok-watermark-yolo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use beanyzoldyck/tiktok-watermark-yolo with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("beanyzoldyck/tiktok-watermark-yolo") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
TikTok Watermark Detection โ YOLOv11
A fine-tuned YOLOv11n model for detecting TikTok watermarks in video frames and images.
Model Details
- Base model: YOLOv11n (
yolo11n.pt) - Task: Object detection (single class โ TikTok watermark)
- Input size: 640ร640
- Format: PyTorch (.pt)
Usage
from ultralytics import YOLO
model = YOLO("beanyzoldyck/tiktok-watermark-yolo")
results = model.predict("video.mp4", conf=0.10)
for result in results:
for box in result.boxes:
x1, y1, x2, y2 = box.xyxy[0].tolist()
conf = box.conf[0].item()
print(f"Watermark detected at ({x1:.0f}, {y1:.0f}, {x2:.0f}, {y2:.0f}) conf={conf:.4f}")
Training
Trained with Ultralytics YOLO on a curated TikTok watermark dataset using yolo11n as the base checkpoint. Default training configuration: 640px image size.
Intended Use
Detecting TikTok watermarks for content moderation, video processing pipelines, and research purposes.
- Downloads last month
- 7