Reference:
- https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocoDemo.ipynb
- https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/coco.py
- https://blog.csdn.net/yeyang911/article/details/78675942
Here is my code. But there is still a problem that when I use the function 'showAnns()' to show the instances' annotations of the image, it cannot show the figure though the code run successfully. If you have any solutions, please leave a message in the comment area. Thanks!
1 import matplotlib 2 import numpy as np 3 import skimage.io as io 4 import matplotlib.pyplot as plt 5 import pylab 6 from pycocotools.coco import COCO 7 pylab.rcParams['figure.figsize'] = (8.0, 10.0) # image pixel 8 9 # if skimage.io declares before pycocotools.coco, the backend will be chosen as Qt5Agg 10 # if pycocotools.coco declares before skimage.io, the backend will be chosen as Agg 11 print(matplotlib.get_backend()) 12 13 dataDir = r'G:\MSCOCO 2017\annotations_trainval2017' 14 dataType = r'val2017' 15 annFile = r'{}\annotations\instances_{}.json'.format(dataDir, dataType) 16 17 # initialize COCO api for instance annotations 18 coco = COCO(annotation_file=annFile) # COCO api class that loads COCO annotation file and prepare data structures. 19 # loading annotations into memory... 20 # Done (t=0.80s) 21 # creating index... 22 # index created! 23 24 # print(coco.info()) # Print information about the annotation file. 25 # description: COCO 2017 Dataset 26 # url: http://cocodataset.org 27 # version: 1.0 28 # year: 2017 29 # contributor: COCO Consortium 30 # date_created: 2017/09/01 31 # None 32 33 # display COCO categories and supercategories 34 # coco.loadCats(self, ids=[]): Load cats with the specified ids. 35 cats = coco.loadCats(coco.getCatIds()) 36 # print(cats) 37 # [{'supercategory': 'person', 'id': 1, 'name': 'person'}, 38 # {'supercategory': 'vehicle', 'id': 2, 'name': 'bicycle'}, 39 # {'supercategory': 'vehicle', 'id': 3, 'name': 'car'}, 40 # {...}, {...}, {...}, ... ..., 41 # {'supercategory': 'indoor', 'id': 90, 'name': 'toothbrush'}] 42 nms = [cat['name'] for cat in cats] 43 # print('COCO categories: \n{}\n'.format(' '.join(nms))) 44 # person bicycle car motorcycle airplane ... hair drier toothbrush 45 nms = set([cat['supercategory'] for cat in cats]) 46 # print('COCO supercategories: \n{}'.format(' '.join(nms))) 47 # vehicle person kitchen electronic appliance indoor accessory animal food furniture outdoor sports 48 49 # get all images containing given categories, select one at random 50 catIds = coco.getCatIds(catNms=['person', 'dog', 'skateboard']) 51 # print(catIds) # [1, 18, 41] 52 imgIds = coco.getImgIds(catIds=catIds) # param catIds (int array): get images with all given categories 53 # imgIds = coco.getImgIds(imgIds=[324158]) # param imgIds (int array): get images for given ids 54 index = np.random.randint(0, len(imgIds)) 55 # print('randomly selected imgId: %d' % index) 56 img = coco.loadImgs(imgIds[index])[0] # Load images with specified ids. 57 # print(img) 58 # if index=2, print: 59 # {'license': 2, 'file_name': '000000279278.jpg', 'coco_url': 'http://images.cocodataset.org/val2017/000000279278.jpg', 60 # 'height': 429, 'width': 640, 'date_captured': '2013-11-15 01:07:24', 61 # 'flickr_url': 'http://farm7.staticflickr.com/6101/6275412942_f8dc734c3f_z.jpg', 'id': 279278} 62 63 # load and display image 64 # i = io.imread('%s/image/%s/%s' % (dataDir, dataType, img['file_name'])) 65 # use url to load image 66 # print(img['coco_url']) # http://images.cocodataset.org/val2017/000000279278.jpg 67 i = io.imread(img['coco_url']) 68 plt.axis('off') 69 plt.imshow(i) 70 # print(plt.imshow(i)) # AxesImage(100, 110; 620x770) 71 plt.show() 72 73 # load and display instance annotations 74 plt.imshow(i) 75 plt.axis('off') 76 annIds = coco.getAnnIds(imgIds=img['id'], catIds=catIds, iscrowd=None) 77 anns = coco.loadAnns(annIds) 78 coco.showAnns(anns) 79 80 # initialize COCO api for person keypoints annotations 81 annFile = '{}/annotations/person_keypoints_{}.json'.format(dataDir, dataType) 82 coco_kps = COCO(annFile) 83 84 # load and display keypoints annotations 85 plt.imshow(i) 86 plt.axis('off') 87 ax = plt.gca() 88 annIds = coco_kps.getAnnIds(imgIds=img['id'], catIds=catIds, iscrowd=None) 89 anns = coco_kps.loadAnns(annIds) 90 coco_kps.showAnns(anns) 91 92 # initialize COCO api for caption annotations 93 annFile = '{}/annotations/captions_{}.json'.format(dataDir, dataType) 94 coco_caps = COCO(annFile) 95 96 # load and display caption annotations 97 annIds = coco_caps.getAnnIds(imgIds=img['id']) 98 anns = coco_caps.loadAnns(annIds) 99 coco_caps.showAnns(anns) 100 plt.imshow(i) 101 plt.axis('off') 102 plt.show()
