提交 8b38e6f4 authored 作者: Glenn Jocher's avatar Glenn Jocher

update dataset comments

上级 1b1681ba
# COCO 2017 dataset http://cocodataset.org
# Download command: bash yolov5/data/get_coco2017.sh
# Train command: python train.py --data ./data/coco.yaml
# Dataset should be placed next to yolov5 folder:
# Train command: python train.py --data coco.yaml
# Default dataset location is next to /yolov5:
# /parent_folder
# /coco
# /yolov5
# train and val datasets (image directory or *.txt file with image paths)
# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
train: ../coco/train2017.txt # 118k images
val: ../coco/val2017.txt # 5k images
test: ../coco/test-dev2017.txt # 20k images for submission to https://competitions.codalab.org/competitions/20794
......
# COCO 2017 dataset http://cocodataset.org - first 128 training images
# Download command: python -c "from yolov5.utils.google_utils import gdrive_download; gdrive_download('1n_oKgR81BJtqk75b00eAjdv03qVCQn2f','coco128.zip')"
# Train command: python train.py --data ./data/coco128.yaml
# Dataset should be placed next to yolov5 folder:
# Download command: python -c "from yolov5.utils.google_utils import *; gdrive_download('1n_oKgR81BJtqk75b00eAjdv03qVCQn2f', 'coco128.zip')"
# Train command: python train.py --data coco128.yaml
# Default dataset location is next to /yolov5:
# /parent_folder
# /coco128
# /yolov5
# train and val datasets (image directory or *.txt file with image paths)
train: ../coco128/images/train2017/
val: ../coco128/images/train2017/
# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
train: ../coco128/images/train2017/ # 128 images
val: ../coco128/images/train2017/ # 128 images
# number of classes
nc: 80
......
#!/bin/bash
# COCO 2017 dataset http://cocodataset.org
# Download command: bash yolov5/data/get_coco2017.sh
# Train command: python train.py --data ./data/coco.yaml
# Dataset should be placed next to yolov5 folder:
# Train command: python train.py --data coco.yaml
# Default dataset location is next to /yolov5:
# /parent_folder
# /coco
# /yolov5
# Download labels from Google Drive, accepting presented query
filename="coco2017labels.zip"
fileid="1cXZR_ckHki6nddOmcysCuuJFM--T-Q6L"
......
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC/
# Download command: bash ./data/get_voc.sh
# Train command: python train.py --data voc.yaml
# Dataset should be placed next to yolov5 folder:
# Default dataset location is next to /yolov5:
# /parent_folder
# /VOC
# /yolov5
start=`date +%s`
# handle optional download dir
......
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC/
# Download command: bash ./data/get_voc.sh
# Train command: python train.py --data voc.yaml
# Dataset should be placed next to yolov5 folder:
# Default dataset location is next to /yolov5:
# /parent_folder
# /VOC
# /yolov5
# train and val datasets (image directory or *.txt file with image paths)
train: ../VOC/images/train/
val: ../VOC/images/val/
# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
train: ../VOC/images/train/ # 16551 images
val: ../VOC/images/val/ # 4952 images
# number of classes
nc: 20
......
Markdown 格式
0%
您添加了 0 到此讨论。请谨慎行事。
请先完成此评论的编辑!
注册 或者 后发表评论