Object Detection
ultralytics
ONNX
yolo11
onnxruntime
playing-cards
card-detection
blackjack
Eval Results (legacy)
Instructions to use sroot/cards_day_1.onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use sroot/cards_day_1.onnx with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("sroot/cards_day_1.onnx") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
| license: agpl-3.0 | |
| library_name: ultralytics | |
| pipeline_tag: object-detection | |
| base_model: Ultralytics/YOLO11 | |
| tags: | |
| - object-detection | |
| - yolo11 | |
| - onnx | |
| - onnxruntime | |
| - playing-cards | |
| - card-detection | |
| - blackjack | |
| model-index: | |
| - name: cards_day_1 | |
| results: | |
| - task: | |
| type: object-detection | |
| dataset: | |
| name: LGD frozen video holdout (117 frames, private) | |
| type: private | |
| metrics: | |
| - type: recall | |
| value: 0.680 | |
| name: pip recall @ threshold 50, code-aware | |
| - type: precision | |
| value: 0.604 | |
| name: precision proxy | |