Instructions to use scchess/smallvision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use scchess/smallvision with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("scchess/smallvision") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
SmallVision โ 2D Chess OCR Models
Finetuned YOLO and RF-DETR weights for detecting chessboards, pieces, orientation markers, and last-move tiles in 2D chess screenshots.
Derived from AndrewSpano/2d-chess-ocr.
Files
| File | Backend | Size |
|---|---|---|
yolo26m-finetuned.pt |
YOLO | ~42 MB |
yolo26m-finetuned.onnx |
YOLO ONNX | ~78 MB |
yolo26n-finetuned.pt |
YOLO | ~5 MB |
yolo26n-finetuned.onnx |
YOLO ONNX | ~10 MB |
rfdetr-l-finetuned.pth |
RF-DETR-L | ~129 MB |
rfdetr-2xl-finetuned.pth |
RF-DETR-2XL | ~484 MB |
Usage
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="scchess/smallvision",
filename="yolo26m-finetuned.pt",
repo_type="model",
)
See SmallVision for the full inference workflow.
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