# Ultralytics YOLOv5 🚀, AGPL-3.0 license
# COCO128 dataset https://www.kaggle.com/datasets/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
# Example usage: python train.py --data coco128.yaml
# parent
# ├── yolov5
# └── datasets
#     └── coco128  ← downloads here (7 MB)

# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco128 # dataset root dir
train: images/train2017 # train images (relative to 'path') 128 images
val: images/train2017 # val images (relative to 'path') 128 images
test: # test images (optional)

# Classes
names:
  0: love
  1: ok
  2: quiet
#  3: motorcycle
#  4: airplane
#  5: bus
#  6: train
#  7: truck
#  8: boat
#  9: traffic light
#  10: fire hydrant
#  11: stop sign
#  12: parking meter
#  13: bench
#  14: bird
#  15: cat
#  16: dog
#  17: horse
#  18: sheep
#  19: cow
#  20: elephant
#  21: bear
#  22: zebra
#  23: giraffe
#  24: backpack
#  25: umbrella
#  26: handbag
#  27: tie
#  28: suitcase
#  29: frisbee
#  30: skis
#  31: snowboard
#  32: sports ball
#  33: kite
#  34: baseball bat
#  35: baseball glove
#  36: skateboard
#  37: surfboard
#  38: tennis racket
#  39: bottle
#  40: wine glass
#  41: cup
#  42: fork
#  43: knife
#  44: spoon
#  45: bowl
#  46: banana
#  47: apple
#  48: sandwich
#  49: orange
#  50: broccoli
#  51: carrot
#  52: hot dog
#  53: pizza
#  54: donut
#  55: cake
#  56: chair
#  57: couch
#  58: potted plant
#  59: bed
#  60: dining table
#  61: toilet
#  62: tv
#  63: laptop
#  64: mouse
#  65: remote
#  66: keyboard
#  67: cell phone
#  68: microwave
#  69: oven
#  70: toaster
#  71: sink
#  72: refrigerator
#  73: book
#  74: clock
#  75: vase
#  76: scissors
#  77: teddy bear
#  78: hair drier
#  79: toothbrush

# Download script/URL (optional)
#download: https://github.com/ultralytics/assets/releases/download/v0.0.0/coco128.zip