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!2753 Fix vocdataset/cocodataset docstring problem

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Merge pull request !2753 from xiefangqi/xfq_fix_docstring
pull/2753/MERGE
mindspore-ci-bot 5 years ago committed by Gitee
parent 2fadbb1d04 741154b9b9
commit 3cb531435e
1 changed files with 37 additions and 37 deletions
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mindspore/dataset/engine/datasets.py
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@ -4034,8 +4034,8 @@ class VOCDataset(MappableDataset):
A source dataset for reading and parsing VOC dataset. A source dataset for reading and parsing VOC dataset.
The generated dataset has two columns : The generated dataset has two columns :
task='Detection' : ['image', 'annotation']. task='Detection' : ['image', 'annotation'];
task='Segmentation' : ['image', 'target'] task='Segmentation' : ['image', 'target'].
The shape of both column 'image' and 'target' is [image_size] if decode flag is False, or [H, W, C] The shape of both column 'image' and 'target' is [image_size] if decode flag is False, or [H, W, C]
otherwise. otherwise.
The type of both tensor 'image' and 'target' is uint8. The type of both tensor 'image' and 'target' is uint8.
@ -4070,20 +4070,20 @@ class VOCDataset(MappableDataset):
- False - False
- not allowed - not allowed
Citation of VOC dataset. Citation of VOC dataset.
.. code-block:: .. code-block::
@article{Everingham10, @article{Everingham10,
author = {Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.}, author = {Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.},
title = {The Pascal Visual Object Classes (VOC) Challenge}, title = {The Pascal Visual Object Classes (VOC) Challenge},
journal = {International Journal of Computer Vision}, journal = {International Journal of Computer Vision},
volume = {88}, volume = {88},
year = {2010}, year = {2010},
number = {2}, number = {2},
month = {jun}, month = {jun},
pages = {303--338}, pages = {303--338},
biburl = {http://host.robots.ox.ac.uk/pascal/VOC/pubs/everingham10.html#bibtex}, biburl = {http://host.robots.ox.ac.uk/pascal/VOC/pubs/everingham10.html#bibtex},
howpublished = {http://host.robots.ox.ac.uk/pascal/VOC/voc{year}/index.html}, howpublished = {http://host.robots.ox.ac.uk/pascal/VOC/voc{year}/index.html},
description = {The PASCAL Visual Object Classes (VOC) challenge is a benchmark in visual description = {The PASCAL Visual Object Classes (VOC) challenge is a benchmark in visual
object category recognition and detection, providing the vision and machine object category recognition and detection, providing the vision and machine
@ -4094,8 +4094,8 @@ class VOCDataset(MappableDataset):
Args: Args:
dataset_dir (str): Path to the root directory that contains the dataset. dataset_dir (str): Path to the root directory that contains the dataset.
task (str): Set the task type of reading voc data, now only support "Segmentation" or "Detection" task (str): Set the task type of reading voc data, now only support "Segmentation" or "Detection"
(default="Segmentation") (default="Segmentation").
mode(str): Set the data list txt file to be readed (default="train") mode (str): Set the data list txt file to be readed (default="train").
class_indexing (dict, optional): A str-to-int mapping from label name to index class_indexing (dict, optional): A str-to-int mapping from label name to index
(default=None, the folder names will be sorted alphabetically and each (default=None, the folder names will be sorted alphabetically and each
class will be given a unique index starting from 0). class will be given a unique index starting from 0).
@ -4114,9 +4114,9 @@ class VOCDataset(MappableDataset):
argument should be specified only when num_shards is also specified. argument should be specified only when num_shards is also specified.
Raises: Raises:
RuntimeError: If xml of Annotations is a invalid format RuntimeError: If xml of Annotations is a invalid format.
RuntimeError: If xml of Annotations loss attribution of "object" RuntimeError: If xml of Annotations loss attribution of "object".
RuntimeError: If xml of Annotations loss attribution of "bndbox" RuntimeError: If xml of Annotations loss attribution of "bndbox".
RuntimeError: If sampler and shuffle are specified at the same time. RuntimeError: If sampler and shuffle are specified at the same time.
RuntimeError: If sampler and sharding are specified at the same time. RuntimeError: If sampler and sharding are specified at the same time.
RuntimeError: If num_shards is specified but shard_id is None. RuntimeError: If num_shards is specified but shard_id is None.
@ -4230,10 +4230,10 @@ class CocoDataset(MappableDataset):
""" """
A source dataset for reading and parsing COCO dataset. A source dataset for reading and parsing COCO dataset.
CocoDataset support four kinds of task: CocoDataset support four kinds of task: 2017 Train/Val/Test Detection, Keypoints, Stuff, Panoptic.
2017 Train/Val/Test Detection, Keypoints, Stuff, Panoptic.
The generated dataset has multi-columns : The generated dataset has multi-columns :
- task='Detection', column: [['image', dtype=uint8], ['bbox', dtype=float32], ['category_id', dtype=uint32], - task='Detection', column: [['image', dtype=uint8], ['bbox', dtype=float32], ['category_id', dtype=uint32],
['iscrowd', dtype=uint32]]. ['iscrowd', dtype=uint32]].
- task='Stuff', column: [['image', dtype=uint8], ['segmentation',dtype=float32], ['iscrowd',dtype=uint32]]. - task='Stuff', column: [['image', dtype=uint8], ['segmentation',dtype=float32], ['iscrowd',dtype=uint32]].
@ -4271,35 +4271,35 @@ class CocoDataset(MappableDataset):
- False - False
- not allowed - not allowed
Citation of Coco dataset. Citation of Coco dataset.
.. code-block:: .. code-block::
@article{DBLP:journals/corr/LinMBHPRDZ14, @article{DBLP:journals/corr/LinMBHPRDZ14,
author = {Tsung{-}Yi Lin and Michael Maire and Serge J. Belongie and author = {Tsung{-}Yi Lin and Michael Maire and Serge J. Belongie and
Lubomir D. Bourdev and Ross B. Girshick and James Hays and Lubomir D. Bourdev and Ross B. Girshick and James Hays and
Pietro Perona and Deva Ramanan and Piotr Doll{\'{a}}r and C. Lawrence Zitnick}, Pietro Perona and Deva Ramanan and Piotr Doll{\'{a}}r and C. Lawrence Zitnick},
title = {Microsoft {COCO:} Common Objects in Context}, title = {Microsoft {COCO:} Common Objects in Context},
journal = {CoRR}, journal = {CoRR},
volume = {abs/1405.0312}, volume = {abs/1405.0312},
year = {2014}, year = {2014},
url = {http://arxiv.org/abs/1405.0312}, url = {http://arxiv.org/abs/1405.0312},
archivePrefix = {arXiv}, archivePrefix = {arXiv},
eprint = {1405.0312}, eprint = {1405.0312},
timestamp = {Mon, 13 Aug 2018 16:48:13 +0200}, timestamp = {Mon, 13 Aug 2018 16:48:13 +0200},
biburl = {https://dblp.org/rec/journals/corr/LinMBHPRDZ14.bib}, biburl = {https://dblp.org/rec/journals/corr/LinMBHPRDZ14.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}, bibsource = {dblp computer science bibliography, https://dblp.org},
description = {COCO is a large-scale object detection, segmentation, and captioning dataset. description = {COCO is a large-scale object detection, segmentation, and captioning dataset.
It contains 91 common object categories with 82 of them having more than 5,000 It contains 91 common object categories with 82 of them having more than 5,000
labeled instances. In contrast to the popular ImageNet dataset, COCO has fewer labeled instances. In contrast to the popular ImageNet dataset, COCO has fewer
categories but more instances per category.} categories but more instances per category.}
} }
Args: Args:
dataset_dir (str): Path to the root directory that contains the dataset. dataset_dir (str): Path to the root directory that contains the dataset.
annotation_file (str): Path to the annotation json. annotation_file (str): Path to the annotation json.
task (str): Set the task type of reading coco data, now support 'Detection'/'Stuff'/'Panoptic'/'Keypoint' task (str): Set the task type of reading coco data, now support 'Detection'/'Stuff'/'Panoptic'/'Keypoint'
(default='Detection') (default='Detection').
num_samples (int, optional): The number of images to be included in the dataset num_samples (int, optional): The number of images to be included in the dataset
(default=None, all images). (default=None, all images).
num_parallel_workers (int, optional): Number of workers to read the data num_parallel_workers (int, optional): Number of workers to read the data

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