#!/bin/bash

# YOLOv5 🚀 by Ultralytics, AGPL-3.0 license

# Download COCO 2017 dataset http://cocodataset.org

# Example usage: bash data/scripts/get_coco.sh

# parent

# ├── yolov5

# └── datasets

#     └── coco  ← downloads here

# Arguments (optional) Usage: bash data/scripts/get_coco.sh --train --val --test --segments

if [ "$#" -gt 0 ]; then

  for opt in "$@"; do

    case "${opt}" in

    --train) train=true ;;

    --val) val=true ;;

    --test) test=true ;;

    --segments) segments=true ;;

    esac

  done

else

  train=true

  val=true

  test=false

  segments=false

fi

# Download/unzip labels

d='../datasets' # unzip directory

url=https://github.com/ultralytics/yolov5/releases/download/v1.0/

if [ "$segments" == "true" ]; then

  f='coco2017labels-segments.zip' # 168 MB

else

  f='coco2017labels.zip' # 46 MB

fi

echo 'Downloading' $url$f ' ...'

curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &

# Download/unzip images

d='../datasets/coco/images' # unzip directory

url=http://images.cocodataset.org/zips/

if [ "$train" == "true" ]; then

  f='train2017.zip' # 19G, 118k images

  echo 'Downloading' $url$f '...'

  curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &

fi

if [ "$val" == "true" ]; then

  f='val2017.zip' # 1G, 5k images

  echo 'Downloading' $url$f '...'

  curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &

fi

if [ "$test" == "true" ]; then

  f='test2017.zip' # 7G, 41k images (optional)

  echo 'Downloading' $url$f '...'

  curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &

fi

wait # finish background tasks