coco与voc数据集下载与准备

coco与voc数据集下载

在远程服务器上测试目标检测算法需要用到测试集，最常用的是coco2014/2017和voc07/12数据集。
coco数据集的地址为http://cocodataset.org/#download
voc和coco的镜像为https://pjreddie.com/projects/pascal-voc-dataset-mirror/
本文做一次记录，方便以后使用。
具体的文件夹结构与detectron2相似：

voc

VOC_ROOT
|__ VOC2007
    |_ JPEGImages
    |_ Annotations
    |_ ImageSets
    |_ SegmentationClass
|__ VOC2012
    |_ JPEGImages
    |_ Annotations
    |_ ImageSets
    |_ SegmentationClass
|__ ...

mkdir voc && cd voc
# voc 2012
wget http://pjreddie.com/media/files/VOCtrainval_11-May-2012.tar && tar -xvf VOCtrainval_11-May-2012.tar && rm VOCtrainval_11-May-2012.tar 
wget http://pjreddie.com/media/files/VOC2012test.tar && tar -xvf VOC2012test.tar && rm VOC2012test.tar 
mv VOCdevkit/VOC2012/ ./ 

# voc 2007
wget http://pjreddie.com/media/files/VOCtrainval_06-Nov-2007.tar && tar -xvf VOCtrainval_06-Nov-2007.tar && rm VOCtrainval_06-Nov-2007.tar
wget http://pjreddie.com/media/files/VOCtest_06-Nov-2007.tar && tar -xvf VOCtest_06-Nov-2007.tar  && rm VOCtest_06-Nov-2007.tar 
mv VOCdevkit/VOC2007/ ./
rm -rf VOCdevkit

coco

COCO_ROOT
|__ annotations
    |_ instances_valminusminival2014.json
    |_ instances_minival2014.json
    |_ instances_train2014.json
    |_ instances_val2014.json
    |_ ...
|__ train2014
    |_ <im-1-name>.jpg
    |_ ...
    |_ <im-N-name>.jpg
|__ val2014
    |_ <im-1-name>.jpg
    |_ ...
    |_ <im-N-name>.jpg
|__ ...

# coco2017 train118k val5k
wget -c http://images.cocodataset.org/zips/train2017.zip &&
unzip train2017.zip && rm train2017.zip &&
wget -c http://images.cocodataset.org/annotations/annotations_trainval2017.zip &&
unzip annotations_trainval2017.zip && rm annotations_trainval2017.zip &&
wget -c http://images.cocodataset.org/zips/val2017.zip &&
unzip val2017.zip &&  rm val2017.zip

# coco2014 train83k val 41k
wget http://images.cocodataset.org/zips/train2014.zip && unzip train2014.zip && rm train2014.zip
wget http://images.cocodataset.org/zips/val2014.zip && unzip val2014.zip && rm val2014.zip
wget http://images.cocodataset.org/annotations/annotations_trainval2014.zip && unzip annotations_trainval2014.zip && rm annotations_trainval2014.zip

## 5k image 'minival' subset and val2014 (set) minus minival (~35k images)
wget https://dl.dropboxusercontent.com/s/s3tw5zcg7395368/instances_valminusminival2014.json.zip?dl=0 && unzip instances_valminusminival2014.json.zip?dl=0  
mv instances_valminusminival2014.json annotations/ && rm instances_valminusminival2014.json.zip?dl=0  
wget https://dl.dropboxusercontent.com/s/o43o90bna78omob/instances_minival2014.json.zip?dl=0 &&  unzip instances_minival2014.json.zip?dl=0
mv instances_minival2014.json annotations/ && rm instances_minival2014.json.zip?dl=0

coco2014也有镜像

## mirror
wget https://pjreddie.com/media/files/train2014.zip  && unzip train2014.zip && rm train2014.zip 
wget https://pjreddie.com/media/files/val2014.zip  && unzip val2014.zip && rm val2014.zip 
wget https://pjreddie.com/media/files/instances_train-val2014.zip && unzip instances_train-val2014.zip && rm instances_train-val2014.zip