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大数据-各类图像数据集下载地址_2014 train images 国内下载地址

2014 train images 国内下载地址

各类图像数据集下载地址

反代加速请参见另一篇

COCO

Images
  1. 官网
  2. https://cocodataset.org/#home
  3. 2014 Train images [83K/13GB]:
  4. http://images.cocodataset.org/zips/train2014.zip
  5. 2014 Val images [41K/6GB]:
  6. http://images.cocodataset.org/zips/val2014.zip
  7. 2014 Test images [41K/6GB]:
  8. http://images.cocodataset.org/zips/test2014.zip
  9. 2015 Test images [81K/12GB]:
  10. http://images.cocodataset.org/zips/test2015.zip
  11. 2017 Train images [118K/18GB]:
  12. http://images.cocodataset.org/zips/train2017.zip
  13. 2017 Val images [5K/1GB]:
  14. http://images.cocodataset.org/zips/val2017.zip
  15. 2017 Test images [41K/6GB]:
  16. http://images.cocodataset.org/zips/test2017.zip
  17. 2017 Unlabeled images [123K/19GB]:
  18. http://images.cocodataset.org/zips/unlabeled2017.zip

Annotations

  1. 2014 Train/Val annotations [241MB]:
  2. http://images.cocodataset.org/annotations/annotations_trainval2014.zip
  3. 2014 Testing Image info [1MB]:
  4. http://images.cocodataset.org/annotations/image_info_test2014.zip
  5. 2015 Testing Image info [2MB]:
  6. http://images.cocodataset.org/annotations/image_info_test2015.zip
  7. 2017 Train/Val annotations [241MB]:
  8. http://images.cocodataset.org/annotations/annotations_trainval2017.zip
  9. 2017 Stuff Train/Val annotations [1.1GB]:
  10. http://images.cocodataset.org/annotations/stuff_annotations_trainval2017.zip
  11. 2017 Panoptic Train/Val annotations [821MB]:
  12. http://images.cocodataset.org/annotations/panoptic_annotations_trainval2017.zip
  13. 2017 Testing Image info [1MB]:
  14. http://images.cocodataset.org/annotations/image_info_test2017.zip
  15. 2017 Unlabeled Image info [4MB]:
  16. http://images.cocodataset.org/annotations/image_info_unlabeled2017.zip

KITTI

官网

  1. http://www.cvlibs.net/datasets/kitti/
  2. left color images of object data set (12 GB):
  3. https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_image_2.zip
  4. right color images, if you want to use stereo information (12 GB):
  5. https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_image_3.zip
  6. Velodyne point clouds, if you want to use laser information (29 GB):
  7. https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_velodyne.zip
  8. training labels of object data set (5 MB):
  9. https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_label_2.zip

MPII

官网

  1. http://human-pose.mpi-inf.mpg.de/#download
  2. Images (12.9 GB)
  3. https://datasets.d2.mpi-inf.mpg.de/andriluka14cvpr/mpii_human_pose_v1.tar.gz
  4. Annotations (12.5 MB)
  5. https://datasets.d2.mpi-inf.mpg.de/andriluka14cvpr/mpii_human_pose_v1_u12_2.zip

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