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: 640ร—640
  • 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.

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