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:
- 0b41bc62728e3879e4e6847c585b0103fb4e22320b9a7f6f3f42474df45ac2bc
- Size of remote file:
- 267 kB
- SHA256:
- 8d01af4ebce4a90b87734310a69461c07f5164b544543b119291b6a638e502aa
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