保存coco dataset注释为单一文件，并逐一显示所有图片的mask

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 } ] }

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