# ==========================================================
#   Object Detection Dataset - YOLO Configuration
# ==========================================================
#   Project: Object Detection Dataset
#   Category: Image Data / Computer Vision
#   Format: YOLOv5/YOLOv8 Compatible
#   
# ==========================================================
#   Developer Information
# ==========================================================
#   Website: https://rskworld.in
#   Founder: Molla Samser
#   Designer & Tester: Rima Khatun
#   Email: help@rskworld.in
#   Phone: +91 93305 39277
#   
#   © 2026 RSK World - All Rights Reserved
# ==========================================================

# Dataset paths
path: ./  # dataset root directory
train: train/images  # train images (relative to 'path')
val: valid/images  # val images (relative to 'path')
test:  # test images (optional)

# Number of classes
nc: 10

# Class names
names:
  0: person
  1: car
  2: dog
  3: cat
  4: bicycle
  5: motorcycle
  6: bus
  7: truck
  8: bird
  9: chair

# Dataset information
# Total images: 1000+
# Training set: 800 images (80%)
# Validation set: 200 images (20%)
# Total annotations: 5000+

# Usage with YOLOv8:
# yolo train model=yolov8n.pt data=data.yaml epochs=100 imgsz=640

# Usage with YOLOv5:
# python train.py --img 640 --batch 16 --epochs 100 --data data.yaml --weights yolov5s.pt