Object Detection
ultralytics
ONNX
yolo11
onnxruntime
casino-chips
chip-detection
casino
live-game-defender
Eval Results (legacy)
Instructions to use sroot/lgd-chips-gen1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use sroot/lgd-chips-gen1 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-chips-gen1") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "classes": [ | |
| "chip_black", | |
| "chip_white", | |
| "chip_green", | |
| "chip_red", | |
| "chip_pink" | |
| ], | |
| "counts": { | |
| "train": { | |
| "pos": 627, | |
| "neg": 138, | |
| "empty_avail": 138 | |
| }, | |
| "val": { | |
| "pos": 39, | |
| "neg": 26, | |
| "empty_avail": 51 | |
| } | |
| }, | |
| "class_instances": { | |
| "chip_pink": 51, | |
| "chip_black": 1831, | |
| "chip_white": 54 | |
| }, | |
| "map50_internal": 0.9682, | |
| "map50_95_internal": 0.6432, | |
| "val_video": "output", | |
| "epochs": 60, | |
| "seconds": 260.0 | |
| } |