保存coco dataset注释为单一文件，并逐一显示所有图片的mask

大意：

官方的例子只显示 一张图片，我需要逐一显示，并且官方的那个JSON文件太大了，我把注释文件分开存储，每张图片一个注释文件，另行保存在一个叫coco的文件夹中，

#
# windows version cocoapi
# https://github.com/philferriere/cocoapi
#
#
from pycocotools.coco import COCO
import numpy as np
import skimage.io as io
import json
import os

import matplotlib as mpl
mpl.use('TkAgg')
import pylab
import matplotlib.rcsetup as rcsetup
pylab.rcParams['figure.figsize'] = (8.0, 10.0)

#dataDir='..'
#dataType='val2017'
#dataDir='F:/BigData/msCoco2014'
#dataType='val2014'

dataDir='F:/BigData/msCoco2017'
dataType='val2017'
annFile='{}/annotations/instances_{}.json'.format(dataDir,dataType)

# initialize COCO api for instance annotations
coco=COCO(annFile)

# display COCO categories and supercategories
catIds = coco.getCatIds()
cats = coco.loadCats(catIds)
#print the names out
nms=[cat['name'] for cat in cats] 
print('COCO categories: \n{}\n'.format(' '.join(nms)))
#print the supercat out
nms = set([cat['supercategory'] for cat in cats])
print('COCO supercategories: \n{}'.format(' '.join(nms)))

# recursively display all images and its masks
imgIds = coco.getImgIds()
for id in imgIds: 
    annIds = coco.getAnnIds([id], catIds=catIds, iscrowd=None)
    anns = coco.loadAnns(annIds)
    imgIds = coco.getImgIds(imgIds = [id])
    img = coco.loadImgs(imgIds[0])[0]
    file_name_ext=img['file_name']
    (filename,extension) = os.path.splitext(file_name_ext)
    file_path = "coco/" + filename + ".json"
    data = {"annotations":anns}
    with open(file_path, 'w') as result_file:
        json.dump(data, result_file)
    I = io.imread('%s/%s/%s'%(dataDir,dataType,img['file_name']))
    mpl.pyplot.imshow(I)
    mpl.pyplot.axis('off')
    coco.showAnns(anns)

顺带再提一下coco数据集中各个参数的解释吧，一般的参数望文即可生义，只需要注意的是iscrowd，这个值为0 即表示polygon,注意，单个的对象（iscrowd=0)可能需要多个polygon来表示，比如某个对象在图像中被挡住了一部分。而iscrowd=1时，segmentation使用的就是RLE格式。

具体样式和解释参数官方文档：https://cocodataset.org/#format-data

如果是自己定义的数据集，采用coco数据格式的话，各个id到底有什么用也是需要注意的地方。

{
  "type": "instances",
  "images": [
    {
      "file_name": "0.jpg",
      "height": 600,
      "width": 800,
      "id": 0                    ----> image_id
    }
  ],
  "categories": [
    {
      "supercategory": "none",   ----> supercategory can be anything
      "name": "date",
      "id": 0                    ----> category_id
    },
    {
      "supercategory": "none",
      "name": "hazelnut",
      "id": 2
    },
    {
      "supercategory": "none",
      "name": "fig",
      "id": 1
    }
  ],
  "annotations": [
    {
      "id": 1,                  ----> annotation id (each annotation has a unique id)
      "bbox": [
        100,
        116,
        140,
        170
      ],
      "image_id": 0,
      "segmentation": [],
      "ignore": 0,
      "area": 23800,
      "iscrowd": 0,
      "category_id": 0
    },
    {
      "id": 2,
      "bbox": [
        321,
        320,
        142,
        102
      ],
      "image_id": 0,
      "segmentation": [],
      "ignore": 0,
      "area": 14484,
      "iscrowd": 0,
      "category_id": 0
    }
  ]
}