Object Detection
ultralytics
ONNX
yolo11
onnxruntime
playing-cards
card-detection
casino
live-game-defender
Eval Results (legacy)
Instructions to use sroot/lgd-cards-gen3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use sroot/lgd-cards-gen3 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/lgd-cards-gen3") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
File size: 1,009 Bytes
87d9dca | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | train:
- /home/novakj/projects/casino-table-monitor/vision/data/rf_ow27d_v4/train/images
- /home/novakj/projects/casino-table-monitor/vision/runs/finetune/video-campaign-2/dataset/images/train
- /home/novakj/projects/casino-table-monitor/vision/data/video_real/images/train
- /home/novakj/projects/casino-table-monitor/vision/data/video_real_day2/images/train
val:
- /home/novakj/projects/casino-table-monitor/vision/data/video_real/images/val
- /home/novakj/projects/casino-table-monitor/vision/data/video_real_day2/images/val
names:
0: 10C
1: 10D
2: 10H
3: 10S
4: 2C
5: 2D
6: 2H
7: 2S
8: 3C
9: 3D
10: 3H
11: 3S
12: 4C
13: 4D
14: 4H
15: 4S
16: 5C
17: 5D
18: 5H
19: 5S
20: 6C
21: 6D
22: 6H
23: 6S
24: 7C
25: 7D
26: 7H
27: 7S
28: 8C
29: 8D
30: 8H
31: 8S
32: 9C
33: 9D
34: 9H
35: 9S
36: AC
37: AD
38: AH
39: AS
40: JC
41: JD
42: JH
43: JS
44: KC
45: KD
46: KH
47: KS
48: QC
49: QD
50: QH
51: QS
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