Unverified Commit f8e11483 authored by Glenn Jocher's avatar Glenn Jocher Committed by GitHub
Browse files

Update dataset headers (#4162)

parent 8acb5734
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# Argoverse-HD dataset (ring-front-center camera) http://www.cs.cmu.edu/~mengtial/proj/streaming/
# Train command: python train.py --data Argoverse_HD.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/Argoverse
# /yolov5
# YOLOv5 🚀 example usage: python train.py --data Argoverse_HD.yaml
# parent
# ├── yolov5
# └── datasets
# └── Argoverse ← downloads here
# 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, ..]
......
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# Global Wheat 2020 dataset http://www.global-wheat.com/
# Train command: python train.py --data GlobalWheat2020.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/GlobalWheat2020
# /yolov5
# YOLOv5 🚀 example usage: python train.py --data GlobalWheat2020.yaml
# parent
# ├── yolov5
# └── datasets
# └── GlobalWheat2020 ← downloads here
# 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, ..]
......
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# Objects365 dataset https://www.objects365.org/
# Train command: python train.py --data Objects365.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/Objects365
# /yolov5
# YOLOv5 🚀 example usage: python train.py --data Objects365.yaml
# parent
# ├── yolov5
# └── datasets
# └── Objects365 ← downloads here
# 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, ..]
......
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19
# Train command: python train.py --data SKU-110K.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/SKU-110K
# /yolov5
# YOLOv5 🚀 example usage: python train.py --data SKU-110K.yaml
# parent
# ├── yolov5
# └── datasets
# └── SKU-110K ← downloads here
# 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, ..]
......
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC/
# Train command: python train.py --data VOC.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/VOC
# /yolov5
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC
# YOLOv5 🚀 example usage: python train.py --data VOC.yaml
# parent
# ├── yolov5
# └── datasets
# └── VOC ← downloads here
# 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, ..]
......
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# VisDrone2019-DET dataset https://github.com/VisDrone/VisDrone-Dataset
# Train command: python train.py --data VisDrone.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/VisDrone
# /yolov5
# YOLOv5 🚀 example usage: python train.py --data VisDrone.yaml
# parent
# ├── yolov5
# └── datasets
# └── VisDrone ← downloads here
# 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, ..]
......
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# COCO 2017 dataset http://cocodataset.org
# Train command: python train.py --data coco.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/coco
# /yolov5
# YOLOv5 🚀 example usage: python train.py --data coco.yaml
# parent
# ├── yolov5
# └── datasets
# └── coco ← downloads here
# 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, ..]
......
# COCO 2017 dataset http://cocodataset.org - first 128 training images
# Train command: python train.py --data coco128.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/coco128
# /yolov5
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
# YOLOv5 🚀 example usage: python train.py --data coco128.yaml
# parent
# ├── yolov5
# └── datasets
# └── coco128 ← downloads here
# 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, ..]
......
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# xView 2018 dataset https://challenge.xviewdataset.org
# ----> NOTE: DOWNLOAD DATA MANUALLY from URL above and unzip to /datasets/xView before running train command below
# Train command: python train.py --data xView.yaml
# Default dataset location is next to YOLOv5:
# /parent
# /datasets/xView
# /yolov5
# -------- DOWNLOAD DATA MANUALLY from URL above and unzip to 'datasets/xView' before running train command! --------
# YOLOv5 🚀 example usage: python train.py --data xView.yaml
# parent
# ├── yolov5
# └── datasets
# └── xView ← downloads here
# 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, ..]
......
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