proj-airi/games-balatro-2024-card-corner-classifier

Balatro (2024, game) card-corner classifier

This model classifies cropped Balatro card corners into rank and suit labels. It is a small shared-backbone CNN, not an Ultralytics YOLO classifier.

ONNX Interface

The exported ONNX model is available at:

onnx/model.onnx

Input:

images: float32[batch, 3, 64, 64]

Outputs:

rank_logits: float32[batch, 13]
suit_logits: float32[batch, 4]

Rank label order:

A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K

Suit label order:

spades, hearts, clubs, diamonds

Training Run

The recovered local training run is stored at:

runs/classify/card-corner-cnn/mps-aug-weighted-seed2-latest

The run includes args.json, metrics.json, PyTorch checkpoints, and a copy of the exported ONNX model under onnx/model.onnx.

Best validation metrics from the recovered run:

rank_accuracy: 0.8387096774193549
suit_accuracy: 1.0
exact_accuracy: 0.8387096774193549

Export

Use the export utility to regenerate the ONNX artifact from a checkpoint:

pixi run python cli/export-card-corner-classifier-onnx.py \
  --checkpoint runs/classify/card-corner-cnn/mps-aug-weighted-seed2-latest/card-corner-classifier-best.pt \
  --output models/games-balatro-2024-card-corner-classifier/onnx/model.onnx

Publish

After authenticating with Hugging Face, upload this model directory as the model repository root:

pixi run python - <<'PY'
from huggingface_hub import HfApi

repo_id = 'proj-airi/games-balatro-2024-card-corner-classifier'
folder = 'models/games-balatro-2024-card-corner-classifier'

api = HfApi()
api.create_repo(repo_id=repo_id, repo_type='model', exist_ok=True)
api.upload_folder(
    repo_id=repo_id,
    repo_type='model',
    folder_path=folder,
    commit_message='Add Balatro card-corner CNN ONNX model',
)
PY