Playing Cards Detection with YoloV8

This repo uses YoloV8 to detect Playing Cards from image (52 classes)

Environments and Dependencies

Python 3.8.16

Install requirements

pip install -r requirements.txt

Data

Dataset can be found here

Config

The dataset YAML is the same standard YOLOv5 YAML format. See the YOLOv5 Train Custom Data tutorial for full details.

Modify path or add config with format .yaml in data_config (Refer here for more information)

Sample playing_cards.yaml

path: ./data/ 
train: train/images # dataset root dir
val: valid/images # train images (relative to 'path')
test: test/images # val images (relative to 'path')

# Classes
names: 
  0: '10C'
  1: '10D'
  2: '10H'
  3: '10S'
  4: '2C'
  ...

Train

Training with CLI

yolo task=detect \
     mode=train \
     model=yolov8s.pt \
     data=./data_config/playing_cards.yaml \
     epochs=10 \
     batch=32 \
     device=0 \
     imgsz=416

See a full list of available yolo arguments in the YOLOv8 Docs.

Experiment results

With 10 epochs for each experiments

Models	mAP50	mAP50:95	Size
yolov8s	0.99498	0.95681	22.0MB

Detect

Simply download pretrained weight and run

yolo task=detect mode=predict model="./yolov8s_playing_cards.pt" source="./assets/test.jpg"

And you will get the result

Input Image	Result Image

Easy infer

For easy infer and get information, run

python infer.py

Reference

ultralytics

PD-Mera/Playing-Cards-Detection