🃏 PokerVision

PokerVision is a computer-vision project that detects and classifies playing cards in real time using a YOLO-based model.
It combines synthetic dataset generation, YOLO training, and live detection through a webcam.

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🚀 Features

• 🎨 Synthetic dataset generator with realistic card positioning and lighting
• 🧠 YOLOv8/YOLO11-based card detection and classification
• 💻 Real-time webcam inference at ~30 FPS
• 🃏 Support for normal, inverted, and real card variants
• 🔄 Easy retraining and dataset regeneration

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📂 Project Structure

PokerVision/
├── data/
│   ├── backgrounds/        # Background images for synthetic data
│   ├── generated/          # Auto-generated images (ignored by git)
│   ├── raw_cards/          # Source card images (normal, inverted, real)
│   └── yolo_dataset/       # YOLO-formatted dataset (train/val images & labels)
│
├── runs/                   # YOLO training results (ignored by git)
├── src/
│   ├── dataset_gen/        # Dataset generation scripts
│   ├── realtime/           # Real-time detection (webcam_demo.py)
│   ├── training/           # (Future) model training utils
│   └── utils/              # Shared helper functions
│
├── weights/                # Model checkpoints (ignored by git)
├── cards.yaml              # YOLO dataset config
├── requirements.txt        # Python dependencies
├── .gitignore
└── README.md

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🧩 Installation

1️⃣ Clone the repo

git clone https://github.com/Yufan3/PokerVision.git
cd PokerVision

2️⃣ Create a Conda environment

conda create -n pokervision python=3.10 -y
conda activate pokervision

3️⃣ Install dependencies

pip install -r requirements.txt

4️⃣ Verify GPU setup

python -m src.utils.check_cuda

🧠 Dataset Generation

Generate a synthetic dataset by combining random backgrounds and card variants:
python -m src.dataset_gen.generate_dataset

The generated data and YOLO labels will appear under:

data/generated/
data/yolo_dataset/

🏋️‍♂️ Model Training Train a YOLO model using your dataset:

yolo detect train model=yolo11s.pt data=cards.yaml epochs=100 imgsz=640 batch=16 device=0

After training, the best weights will be saved at:

runs/detect/train*/weights/best.pt

🎥 Real-Time Detection Run live card detection using your webcam:

python src/realtime/webcam_demo.py
Press Q to exit the window.

🪪 License

This project is open-source under the MIT License. See LICENSE for details.