| Name | DL | Torrents | Total Size | Computer Vision [edit] | 79 | 1.41TB | 696 | 0 |
fast-ai-coco (10 files)
 val2017.zip | 815.59MB |
| annotations_trainval2017.zip | 252.91MB |
| train2017.zip | 19.34GB |
| test2017.zip | 6.65GB |
| stuff_annotations_trainval2017.zip | 1.15GB |
| panoptic_annotations_trainval2017.zip | 860.73MB |
| image_info_unlabeled2017.zip | 4.90MB |
| image_info_test2017.zip | 1.14MB |
| coco_sample.tgz | 3.25GB |
| unlabeled2017.zip | 20.13GB |
Type: Dataset
Tags: fastai
Bibtex:
Tags: fastai
Bibtex:
@article{,
title= {COCO 2017},
keywords= {fastai},
journal= {},
author= {TY Lin, 2014},
year= {},
url= {http://cocodataset.org/},
license= {},
abstract= {Probably the most widely used dataset today for object localization is COCO: Common Objects in Context. Provided here are all the files from the 2017 version, along with an additional subset dataset created by fast.ai. Details of each COCO dataset is available from the COCO dataset page. The fast.ai subset contains all images that contain one of five selected categories, restricting objects to just those five categories; the categories are: chair couch tv remote book vase.},
superseded= {},
terms= {}
}
