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Update comments header (ultralytics#4184)
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glenn-jocher authored Jul 27, 2021
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4 changes: 2 additions & 2 deletions data/Argoverse_HD.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by 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/
# YOLOv5 πŸš€ example usage: python train.py --data Argoverse_HD.yaml
# Example usage: python train.py --data Argoverse_HD.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/GlobalWheat2020.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# Global Wheat 2020 dataset http://www.global-wheat.com/
# YOLOv5 πŸš€ example usage: python train.py --data GlobalWheat2020.yaml
# Example usage: python train.py --data GlobalWheat2020.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/Objects365.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# Objects365 dataset https://www.objects365.org/
# YOLOv5 πŸš€ example usage: python train.py --data Objects365.yaml
# Example usage: python train.py --data Objects365.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/SKU-110K.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19
# YOLOv5 πŸš€ example usage: python train.py --data SKU-110K.yaml
# Example usage: python train.py --data SKU-110K.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/VOC.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC
# YOLOv5 πŸš€ example usage: python train.py --data VOC.yaml
# Example usage: python train.py --data VOC.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/VisDrone.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# VisDrone2019-DET dataset https://github.com/VisDrone/VisDrone-Dataset
# YOLOv5 πŸš€ example usage: python train.py --data VisDrone.yaml
# Example usage: python train.py --data VisDrone.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/coco.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# COCO 2017 dataset http://cocodataset.org
# YOLOv5 πŸš€ example usage: python train.py --data coco.yaml
# Example usage: python train.py --data coco.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/coco128.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by 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 πŸš€ example usage: python train.py --data coco128.yaml
# Example usage: python train.py --data coco128.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/scripts/download_weights.sh
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#!/bin/bash
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# Download latest models from https://github.com/ultralytics/yolov5/releases
# YOLOv5 πŸš€ example usage: bash path/to/download_weights.sh
# Example usage: bash path/to/download_weights.sh
# parent
# └── yolov5
# β”œβ”€β”€ yolov5s.pt ← downloads here
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4 changes: 2 additions & 2 deletions data/scripts/get_coco.sh
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#!/bin/bash
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# Download COCO 2017 dataset http://cocodataset.org
# YOLOv5 πŸš€ example usage: bash data/scripts/get_coco.sh
# Example usage: bash data/scripts/get_coco.sh
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/scripts/get_coco128.sh
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#!/bin/bash
# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# Download COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
# YOLOv5 πŸš€ example usage: bash data/scripts/get_coco128.sh
# Example usage: bash data/scripts/get_coco128.sh
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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4 changes: 2 additions & 2 deletions data/xView.yaml
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# Copyright Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# YOLOv5 πŸš€ by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# xView 2018 dataset https://challenge.xviewdataset.org
# -------- DOWNLOAD DATA MANUALLY from URL above and unzip to 'datasets/xView' before running train command! --------
# YOLOv5 πŸš€ example usage: python train.py --data xView.yaml
# Example usage: python train.py --data xView.yaml
# parent
# β”œβ”€β”€ yolov5
# └── datasets
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