├── LICENSE ├── README.md ├── coco_train2017.html ├── eda_coco_style.ipynb └── voc12_train.html /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2020 Sai Vikas 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## Exploratory Data Analysis on MS COCO style datasets. 2 | 3 | [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) 4 | 5 | 6 | This repo mainly contains a jupyter notebook in which some basic Exploratory Data Analysis (EDA) is performed on MS COCO. While EDA is widely used for categorical data, I haven't seen a lot of repos doing EDA for object detection datasets, which is the reason I created this repo. 7 | 8 | ### Contents: 9 | - eda_coco_style.ipynb 10 | - coco_train2017.html (EDA results on MS COCO 2017 - train) 11 | - voc2012.html (EDA results on VOC 2012) 12 | 13 | ### Features: 14 | - Some basic high level statistics 15 | - Distribution of objects across images 16 | - Class wise distribution of objects 17 | - Observing average bounding box sizes for each class 18 | - Viewing random images 19 | 20 | ### Notes: 21 | 22 | Used [this tool ](https://github.com/yukkyo/voc2coco) to convert PASCAL VOC XML style datasets to MS COCO style JSONs. 23 | 24 | ### Maintainers: 25 | 26 | This tool is developed and maintained by [Vikas Desai](https://svdesai.github.io) (me). 27 | 28 | 29 | 30 | 31 | 32 | 33 | --------------------------------------------------------------------------------