Evaluation Data (Object Detection)

COCO2017

#Metrics-bbox_mAP

Data description:

The COCO dataset is a large-scale object detection dataset funded by Microsoft in the United States. It encompasses 80 categories, with over 200,000 annotated images and 1,500,000 target instances. This dataset is sourced from a variety of complex daily scenarios, and its data distribution is relatively balanced. The training set, validation set, and test set contain 118,287, 5,000, and 40,670 images respectively. Since the annotations of the original test set are not publicly available, the original validation set is used as the test set.

Dataset structure:

Amount of source data:

The dataset is split into train(118,287), validation(5,000), test(5,000)

Amount of test data:

All 5,000 test examples from the source dataset test set.

Data detail:

Raw image：RGB image

Bounding box and category annotation

Sample of source dataset:

Raw image：

annotation format：

[{ "image_id": int, "category_id": int, "bbox": [x,y,width,height], "score": float, }]

Citation information:

@inproceedings{lin2014microsoft,
  title={Microsoft coco: Common objects in context},
  author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
  booktitle={Computer vision--ECCV 2014: 13th European conference, zurich, Switzerland, September 6-12, 2014, proceedings, part v 13},
  pages={740--755},
  year={2014},
  organization={Springer}
}

Licensing information：

TERMS OF USE

PASCAL VOC2007

#Metrics-bbox_mAP

Data description:

The PASCAL Visual Object Classes (PASCAL VOC) Challenge is a world - class computer vision challenge. The dataset it provides has had a profound impact on the development of early object detection algorithms. The PASCAL VOC2007 dataset includes 20 categories, with a total of 9,963 annotated images and 24,640 target instances. Among them, the training set, validation set, and test set contain 2,501, 2,510, and 4,952 images respectively.

Dataset structure:

Amount of source data:

The dataset is split into train(2,501), validation(2,501), test(4,952)

Amount of test data:

All 4,952 test examples from the source dataset test set.

Data detail:

Raw image：RGB image

Bounding box and category annotation

Sample of source dataset:

Raw image：

Bounding box and category annotation：

Citation information:

@misc{pascal-voc-2007,
	author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
	title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2007 {(VOC2007)} {R}esults",
	howpublished = "http://www.pascal-network.org/challenges/VOC/voc2007/workshop/index.html"}

Licensing information：

TERMS OF USE