# Songdo Vision dataset: http://dx.doi.org/10.5281/zenodo.13828408

# Configuration file for YOLOv5, YOLOv8, or YOLOv11 training.
# This file defines the paths to your data, the number of classes, and class names.

# Dataset directory structure (example):
# ├── yolo           # Implementation of YOLOv5, YOLOv8, or YOLOv11
# │   └── data.yaml  # Configuration file
# └── datasets
#     └── songdo_vision ← place here (~15 GB)
#         ├── train
#         │   ├── images  # Training images (4,335 .jpg files)
#         │   │   ├── 0001.jpg
#         │   │   ├── 0002.jpg
#         │   │   ├── ...
#         │   └── labels  # Training labels in YOLO format (4,335 .txt files)
#         │       ├── 0001.txt
#         │       ├── 0002.txt
#         │       ├── ...
#         └── test
#             ├── images  # Test images (1,084 .jpg files)
#             │   ├── 00027.jpg
#             │   ├── 00040.jpg
#             │   ├── ...
#             └── labels  # Test labels in YOLO format (1,084 .txt files)
#                 ├── 00027.txt
#                 ├── 00040.txt
#                 ├── ...

# Dataset information
path: ../datasets/songdo_vision  # Root directory of the dataset

train: train/images  # Path to training images (relative to 'path')
val: test/images  # Path to validation images (relative to 'path').
test: test/images  # Path to test images (relative to 'path')

# Class information
nc: 4  # Number of classes
names: ['car', 'bus', 'truck', 'motorcycle']  # List of class names