language:
- en
- multilingual
license: mit
tags:
- YOLO
- ONNX
- onnxruntime
datasets:
- proj-airi/games-balatro-2024-ui-detection
base_model: Ultralytics/YOLO11
Balatro (2024, game) YOLO UI detection
This project is part of (and also associate to) the Project AIRI, we aim to build a LLM-driven VTuber like Neuro-sama (subscribe if you didn't!) if you are interested in, please do give it a try on live demo.
Who are we?
We are a group of currently non-funded talented people made up with computer scientists, experts in multi-modal fields, designers, product managers, and popular open source contributors who loves the goal of where we are heading now.
| Basic | Multiple card types | Description | Crowded cards |
|---|---|---|---|
 |
 |
 |
 |
Training
We trained this model on our own datasets labelled with n<1k images using Label Studio with YOLOv11n as the base model, it's available on HuggingFace as well: proj-airi/games-balatro-2024-ui-detection.
The training was performed on a single NVIDIA 4080Super GPU with 16GB VRAM, the loss optimized well and converged within set 2000 epochs.
Citation
If you find our works useful for your research, please consider citing:
@misc{proj_airi_game_ai_models_balatro_2024_yolo_ui_detection_2025,
title = {Balatro (2024, game) YOLO UI detection},
author = {Project AIRI Team, Neko Ayaka, Makito, Rainbow Bird},
howpublished = {\url{https://huggingface.co/proj-airi/games-balatro-2024-yolo-ui-detection}},
year = {2025}
}
License
This model is licensed under the MIT.