Object Detection
ultralytics
PyTorch
English
yolov12
watermark-detection
dinov3
vision-transformer
Eval Results (legacy)
Instructions to use corzent/yolov12x-dino3-watermark-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use corzent/yolov12x-dino3-watermark-detection with ultralytics:
from ultralytics import YOLOvv12 model = YOLOvv12.from_pretrained("corzent/yolov12x-dino3-watermark-detection") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- ff0cd06d57bf00b282530ef76a8b5b24dbd009a63f5b8cfc63436fdc24b1692f
- Size of remote file:
- 160 kB
- SHA256:
- 0a5e83d3208cc2b8c0aa5c2ce1605074b3d93123c5623255a743fe91ddeb57b3
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