Codermay/airbus_rle_to_coco

Kaggle airbus

制作COCO数据集

本代码是针对Kaggle比赛 Airbus Ship Detection Challenge 制作的RLE-->COCO 数据集转换工具;

主要有以下几个功能：

1. 数据集中存在大量的负样本，将其删除，只保留存在实例的图片
2. airbus提供的数据是RLE格式的，将其转化为COCO数据集格式，得到标准的.json标注文件
3. 筛选出不好的标注文件

Make COCO Dateset

This code is for Kaggle competiton Airbus Ship Detection Challenge, which can help you transform RLE into COCO annotations. It has 3 main functions:

1. Delete useless images without ships;
2. Transform RLE into COCO annotations;
3. Store bad annotations into folder ../tmp/bad_anns;

File structure

airbus_dataset
├─input                                     # dataset and annotations
│  ├─annotations            		
│  │  └─ instances_ships_train2018.json     # .json, which will be generated by us
│  │
│  ├─ships_train2018                        # ship pictures
│  │  ├─ 000d42241.jpg
│  │  ├─ 000e6378b.jpg
│  │  └─ xxx.jpg
│  │
│  └─train_ship_segmentations_v2.csv        # annotations in RLE style
│
├─airbus_rle_to_coco                        # here we are
│  ├─ 0_airbus_delete_empty_im.py           # delete images without ships
│  ├─ 0_csv_show_RLE.py                     # show annotations in RLE style
│  ├─ 1_ships_to_coco.py                    # turn RLE into COCO
│  └─ 2_pycoco_API_Demo.ipynb               # show annotations in COCO style 
│
└─tmp                                       # bad annotations

Installation

1、install pycocotool

git clone https://github.com/waleedka/coco
cd coco/PythonAPI
make
python setup.py install

2、install pycococreator

pip install git+git://github.com/waspinator/pycococreator.git@0.2.0

3、install pandas and something others

pip install pandas

Step

1. run 0_airbus_delete_empty_im.py, which can delete empty images without ships

2. run 0_csv_show_RLE.py, which can show dataset in RLE style

3. run 1_ships_to_coco.py, which generates .json file. Here is a finished one:

   instances_ships_train2018.json

4. run 2_pycoco_API_Demo.ipynb, which can show dataset in COCO style